1
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Leśniewski M, Pyrka M, Czaplewski C, Co NT, Jiang Y, Gong Z, Tang C, Liwo A. Assessment of Two Restraint Potentials for Coarse-Grained Chemical-Cross-Link-Assisted Modeling of Protein Structures. J Chem Inf Model 2024; 64:1377-1393. [PMID: 38345917 PMCID: PMC10900291 DOI: 10.1021/acs.jcim.3c01890] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2023] [Revised: 01/20/2024] [Accepted: 01/22/2024] [Indexed: 02/27/2024]
Abstract
The influence of distance restraints from chemical cross-link mass spectroscopy (XL-MS) on the quality of protein structures modeled with the coarse-grained UNRES force field was assessed by using a protocol based on multiplexed replica exchange molecular dynamics, in which both simulated and experimental cross-link restraints were employed, for 23 small proteins. Six cross-links with upper distance boundaries from 4 Å to 12 Å (azido benzoic acid succinimide (ABAS), triazidotriazine (TATA), succinimidyldiazirine (SDA), disuccinimidyl adipate (DSA), disuccinimidyl glutarate (DSG), and disuccinimidyl suberate (BS3)) and two types of restraining potentials ((i) simple flat-bottom Lorentz-like potentials dependent on side chain distance (all cross-links) and (ii) distance- and orientation-dependent potentials determined based on molecular dynamics simulations of model systems (DSA, DSG, BS3, and SDA)) were considered. The Lorentz-like potentials with properly set parameters were found to produce a greater number of higher-quality models compared to unrestrained simulations than the MD-based potentials, because the latter can force too long distances between side chains. Therefore, the flat-bottom Lorentz-like potentials are recommended to represent cross-link restraints. It was also found that significant improvement of model quality upon the introduction of cross-link restraints is obtained when the sum of differences of indices of cross-linked residues exceeds 150.
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Affiliation(s)
- Mateusz Leśniewski
- Faculty
of Chemistry, University of Gdańsk, Fahrenheit Union of Universities, ul. Wita Stwosza 63, 80-308 Gdańsk, Poland
| | - Maciej Pyrka
- Faculty
of Chemistry, University of Gdańsk, Fahrenheit Union of Universities, ul. Wita Stwosza 63, 80-308 Gdańsk, Poland
- Department
of Physics and Biophysics, University of
Warmia and Mazury, ul. Oczapowskiego 4, 10-719 Olsztyn, Poland
| | - Cezary Czaplewski
- Faculty
of Chemistry, University of Gdańsk, Fahrenheit Union of Universities, ul. Wita Stwosza 63, 80-308 Gdańsk, Poland
| | - Nguyen Truong Co
- Faculty
of Chemistry, University of Gdańsk, Fahrenheit Union of Universities, ul. Wita Stwosza 63, 80-308 Gdańsk, Poland
| | - Yida Jiang
- College
of Chemistry and Molecular Engineering & Center for Quantitative
Biology & PKU-Tsinghua Center for Life Sciences & Beijing
National Laboratory for Molecular Sciences, Peking University, Beijing 100871, China
| | - Zhou Gong
- Innovation
Academy of Precision Measurement Science and Technology, Chinese Academy of Sciences, 30 W. Xiao Hong Shan, Wuhan 430071, China
| | - Chun Tang
- College
of Chemistry and Molecular Engineering & Center for Quantitative
Biology & PKU-Tsinghua Center for Life Sciences & Beijing
National Laboratory for Molecular Sciences, Peking University, Beijing 100871, China
| | - Adam Liwo
- Faculty
of Chemistry, University of Gdańsk, Fahrenheit Union of Universities, ul. Wita Stwosza 63, 80-308 Gdańsk, Poland
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2
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Lensink MF, Brysbaert G, Raouraoua N, Bates PA, Giulini M, Honorato RV, van Noort C, Teixeira JMC, Bonvin AMJJ, Kong R, Shi H, Lu X, Chang S, Liu J, Guo Z, Chen X, Morehead A, Roy RS, Wu T, Giri N, Quadir F, Chen C, Cheng J, Del Carpio CA, Ichiishi E, Rodriguez‐Lumbreras LA, Fernandez‐Recio J, Harmalkar A, Chu L, Canner S, Smanta R, Gray JJ, Li H, Lin P, He J, Tao H, Huang S, Roel‐Touris J, Jimenez‐Garcia B, Christoffer CW, Jain AJ, Kagaya Y, Kannan H, Nakamura T, Terashi G, Verburgt JC, Zhang Y, Zhang Z, Fujuta H, Sekijima M, Kihara D, Khan O, Kotelnikov S, Ghani U, Padhorny D, Beglov D, Vajda S, Kozakov D, Negi SS, Ricciardelli T, Barradas‐Bautista D, Cao Z, Chawla M, Cavallo L, Oliva R, Yin R, Cheung M, Guest JD, Lee J, Pierce BG, Shor B, Cohen T, Halfon M, Schneidman‐Duhovny D, Zhu S, Yin R, Sun Y, Shen Y, Maszota‐Zieleniak M, Bojarski KK, Lubecka EA, Marcisz M, Danielsson A, Dziadek L, Gaardlos M, Gieldon A, Liwo A, Samsonov SA, Slusarz R, Zieba K, Sieradzan AK, Czaplewski C, Kobayashi S, Miyakawa Y, Kiyota Y, Takeda‐Shitaka M, Olechnovic K, Valancauskas L, Dapkunas J, Venclovas C, Wallner B, Yang L, Hou C, He X, Guo S, Jiang S, Ma X, Duan R, Qui L, Xu X, Zou X, Velankar S, Wodak SJ. Impact of AlphaFold on structure prediction of protein complexes: The CASP15-CAPRI experiment. Proteins 2023; 91:1658-1683. [PMID: 37905971 PMCID: PMC10841881 DOI: 10.1002/prot.26609] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Revised: 09/22/2023] [Accepted: 09/28/2023] [Indexed: 11/02/2023]
Abstract
We present the results for CAPRI Round 54, the 5th joint CASP-CAPRI protein assembly prediction challenge. The Round offered 37 targets, including 14 homodimers, 3 homo-trimers, 13 heterodimers including 3 antibody-antigen complexes, and 7 large assemblies. On average ~70 CASP and CAPRI predictor groups, including more than 20 automatics servers, submitted models for each target. A total of 21 941 models submitted by these groups and by 15 CAPRI scorer groups were evaluated using the CAPRI model quality measures and the DockQ score consolidating these measures. The prediction performance was quantified by a weighted score based on the number of models of acceptable quality or higher submitted by each group among their five best models. Results show substantial progress achieved across a significant fraction of the 60+ participating groups. High-quality models were produced for about 40% of the targets compared to 8% two years earlier. This remarkable improvement is due to the wide use of the AlphaFold2 and AlphaFold2-Multimer software and the confidence metrics they provide. Notably, expanded sampling of candidate solutions by manipulating these deep learning inference engines, enriching multiple sequence alignments, or integration of advanced modeling tools, enabled top performing groups to exceed the performance of a standard AlphaFold2-Multimer version used as a yard stick. This notwithstanding, performance remained poor for complexes with antibodies and nanobodies, where evolutionary relationships between the binding partners are lacking, and for complexes featuring conformational flexibility, clearly indicating that the prediction of protein complexes remains a challenging problem.
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Affiliation(s)
- Marc F. Lensink
- Univ. Lille, CNRS, UMR8576 – UGSF – Unité de Glycobiologie Structurale et FonctionnelleLilleFrance
| | - Guillaume Brysbaert
- Univ. Lille, CNRS, UMR8576 – UGSF – Unité de Glycobiologie Structurale et FonctionnelleLilleFrance
| | - Nessim Raouraoua
- Univ. Lille, CNRS, UMR8576 – UGSF – Unité de Glycobiologie Structurale et FonctionnelleLilleFrance
| | - Paul A. Bates
- Biomolecular Modeling LaboratoryThe Francis Crick InstituteLondonUK
| | - Marco Giulini
- Bijvoet Center for Biomolecular Research, Faculty of Science – ChemistryUtrecht UniversityUtrechtThe Netherlands
| | - Rodrigo V. Honorato
- Bijvoet Center for Biomolecular Research, Faculty of Science – ChemistryUtrecht UniversityUtrechtThe Netherlands
| | - Charlotte van Noort
- Bijvoet Center for Biomolecular Research, Faculty of Science – ChemistryUtrecht UniversityUtrechtThe Netherlands
| | - Joao M. C. Teixeira
- Bijvoet Center for Biomolecular Research, Faculty of Science – ChemistryUtrecht UniversityUtrechtThe Netherlands
| | - Alexandre M. J. J. Bonvin
- Bijvoet Center for Biomolecular Research, Faculty of Science – ChemistryUtrecht UniversityUtrechtThe Netherlands
| | - Ren Kong
- Institute of Bioinformatics and Medical Engineering, School of Electrical and Information EngineeringJiangsu University of TechnologyChangzhouChina
| | - Hang Shi
- Institute of Bioinformatics and Medical Engineering, School of Electrical and Information EngineeringJiangsu University of TechnologyChangzhouChina
| | - Xufeng Lu
- Institute of Bioinformatics and Medical Engineering, School of Electrical and Information EngineeringJiangsu University of TechnologyChangzhouChina
| | - Shan Chang
- Institute of Bioinformatics and Medical Engineering, School of Electrical and Information EngineeringJiangsu University of TechnologyChangzhouChina
| | - Jian Liu
- Dept. of Electrical Engineering and Computer ScienceUniversity of MissouriColumbiaMissouriUSA
| | - Zhiye Guo
- Dept. of Electrical Engineering and Computer ScienceUniversity of MissouriColumbiaMissouriUSA
| | - Xiao Chen
- Dept. of Electrical Engineering and Computer ScienceUniversity of MissouriColumbiaMissouriUSA
| | - Alex Morehead
- Dept. of Electrical Engineering and Computer ScienceUniversity of MissouriColumbiaMissouriUSA
| | - Raj S. Roy
- Dept. of Electrical Engineering and Computer ScienceUniversity of MissouriColumbiaMissouriUSA
| | - Tianqi Wu
- Dept. of Electrical Engineering and Computer ScienceUniversity of MissouriColumbiaMissouriUSA
| | - Nabin Giri
- Dept. of Electrical Engineering and Computer ScienceUniversity of MissouriColumbiaMissouriUSA
| | - Farhan Quadir
- Dept. of Electrical Engineering and Computer ScienceUniversity of MissouriColumbiaMissouriUSA
| | - Chen Chen
- Dept. of Electrical Engineering and Computer ScienceUniversity of MissouriColumbiaMissouriUSA
| | - Jianlin Cheng
- Dept. of Electrical Engineering and Computer ScienceUniversity of MissouriColumbiaMissouriUSA
| | | | - Eichiro Ichiishi
- International University of Health and Welfare (IUHV Hospital)Nasushiobara‐CityJapan
| | - Luis A. Rodriguez‐Lumbreras
- Instituto de Ciencias de la Vida y del Vino (ICVV)CSIC ‐ Universidad de La Rioja ‐ Gobierno de La RiojaLogronoSpain
- Barcelona Supercomputing Center (BSC)BarcelonaSpain
| | - Juan Fernandez‐Recio
- Instituto de Ciencias de la Vida y del Vino (ICVV)CSIC ‐ Universidad de La Rioja ‐ Gobierno de La RiojaLogronoSpain
- Barcelona Supercomputing Center (BSC)BarcelonaSpain
| | - Ameya Harmalkar
- Dept. of Chemical and Biomolecular EngineeringJohns Hopkins UniversityBaltimoreMarylandUSA
| | - Lee‐Shin Chu
- Dept. of Chemical and Biomolecular EngineeringJohns Hopkins UniversityBaltimoreMarylandUSA
| | - Sam Canner
- Dept. of Chemical and Biomolecular EngineeringJohns Hopkins UniversityBaltimoreMarylandUSA
| | - Rituparna Smanta
- Dept. of Chemical and Biomolecular EngineeringJohns Hopkins UniversityBaltimoreMarylandUSA
| | - Jeffrey J. Gray
- Dept. of Chemical and Biomolecular EngineeringJohns Hopkins UniversityBaltimoreMarylandUSA
- Program in Molecular BiophysicsJohns Hopkins UniversityBaltimoreMarylandUSA
| | - Hao Li
- School of PhysicsHuazhong University of Science and TechnologyWuhanChina
| | - Peicong Lin
- School of PhysicsHuazhong University of Science and TechnologyWuhanChina
| | - Jiahua He
- School of PhysicsHuazhong University of Science and TechnologyWuhanChina
| | - Huanyu Tao
- School of PhysicsHuazhong University of Science and TechnologyWuhanChina
| | - Sheng‐You Huang
- School of PhysicsHuazhong University of Science and TechnologyWuhanChina
| | - Jorge Roel‐Touris
- Protein Design and Modeling Lab, Dept. of Structural BiologyMolecular Biology Institute of Barcelona (IBMB‐CSIC)BarcelonaSpain
| | | | | | - Anika J. Jain
- Dept. of Biological SciencesPurdue UniversityWest LafayetteIndianaUSA
| | - Yuki Kagaya
- Dept. of Biological SciencesPurdue UniversityWest LafayetteIndianaUSA
| | - Harini Kannan
- Dept. of Biological SciencesPurdue UniversityWest LafayetteIndianaUSA
- Dept. of Biotechnology, Bhupat and Jyoti Mehta School of BiosciencesIndian Institute of Technology MadrasChennaiIndia
| | - Tsukasa Nakamura
- Dept. of Biological SciencesPurdue UniversityWest LafayetteIndianaUSA
| | - Genki Terashi
- Dept. of Biological SciencesPurdue UniversityWest LafayetteIndianaUSA
| | - Jacob C. Verburgt
- Dept. of Biological SciencesPurdue UniversityWest LafayetteIndianaUSA
| | - Yuanyuan Zhang
- Dept. of Computer SciencePurdue UniversityWest LafayetteIndianaUSA
| | - Zicong Zhang
- Dept. of Computer SciencePurdue UniversityWest LafayetteIndianaUSA
| | - Hayato Fujuta
- Dept. of Biotechnology, Bhupat and Jyoti Mehta School of BiosciencesIndian Institute of Technology MadrasChennaiIndia
| | | | - Daisuke Kihara
- Dept. of Computer SciencePurdue UniversityWest LafayetteIndianaUSA
- Dept. of Biological SciencesPurdue UniversityWest LafayetteIndianaUSA
| | | | | | | | | | | | | | | | - Surendra S. Negi
- Sealy Center for Structural Biology and Molecular BiophysicsUniversity of Texas Medical BranchGalvestonTexasUSA
| | | | | | - Zhen Cao
- King Abdullah University of Science and Technology (KAUST)Saudi Arabia
| | - Mohit Chawla
- King Abdullah University of Science and Technology (KAUST)Saudi Arabia
| | - Luigi Cavallo
- King Abdullah University of Science and Technology (KAUST)Saudi Arabia
- Department of Chemistry and BiologyUniversity of SalernoFiscianoItaly
| | | | - Rui Yin
- University of Maryland Institute for Bioscience and Biotechnology ResearchRockvilleMarylandUSA
- Dept. of Cell Biology and Molecular GeneticsUniversity of MarylandCollege ParkMarylandUSA
| | - Melyssa Cheung
- University of Maryland Institute for Bioscience and Biotechnology ResearchRockvilleMarylandUSA
- Dept. of Chemistry and BiochemistryUniversity of MarylandCollege ParkMarylandUSA
| | - Johnathan D. Guest
- University of Maryland Institute for Bioscience and Biotechnology ResearchRockvilleMarylandUSA
- Dept. of Cell Biology and Molecular GeneticsUniversity of MarylandCollege ParkMarylandUSA
| | - Jessica Lee
- University of Maryland Institute for Bioscience and Biotechnology ResearchRockvilleMarylandUSA
- Dept. of Cell Biology and Molecular GeneticsUniversity of MarylandCollege ParkMarylandUSA
| | - Brian G. Pierce
- University of Maryland Institute for Bioscience and Biotechnology ResearchRockvilleMarylandUSA
- Dept. of Cell Biology and Molecular GeneticsUniversity of MarylandCollege ParkMarylandUSA
| | - Ben Shor
- School of Computer Science and EngineeringThe Hebrew University of JerusalemJerusalemIsrael
| | - Tomer Cohen
- School of Computer Science and EngineeringThe Hebrew University of JerusalemJerusalemIsrael
| | - Matan Halfon
- School of Computer Science and EngineeringThe Hebrew University of JerusalemJerusalemIsrael
| | | | - Shaowen Zhu
- Department of Electrical and Computer EngineeringTexas A&M UniversityCollege StationTexasUSA
| | - Rujie Yin
- Department of Electrical and Computer EngineeringTexas A&M UniversityCollege StationTexasUSA
| | - Yuanfei Sun
- Department of Electrical and Computer EngineeringTexas A&M UniversityCollege StationTexasUSA
| | - Yang Shen
- Department of Electrical and Computer EngineeringTexas A&M UniversityCollege StationTexasUSA
- Department of Computer Science and EngineeringTexas A&M UniversityCollege StationTexasUSA
- Institute of Biosciences and Technology and Department of Translational Medical SciencesTexas A&M UniversityHoustonTexasUSA
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Yuta Miyakawa
- School of PharmacyKitasato UniversityMinato‐kuTokyoJapan
| | - Yasuomi Kiyota
- School of PharmacyKitasato UniversityMinato‐kuTokyoJapan
| | | | - Kliment Olechnovic
- Institute of Biotechnology, Life Sciences CenterVilnius UniversityVilniusLithuania
| | - Lukas Valancauskas
- Institute of Biotechnology, Life Sciences CenterVilnius UniversityVilniusLithuania
| | - Justas Dapkunas
- Institute of Biotechnology, Life Sciences CenterVilnius UniversityVilniusLithuania
| | - Ceslovas Venclovas
- Institute of Biotechnology, Life Sciences CenterVilnius UniversityVilniusLithuania
| | - Bjorn Wallner
- Bioinformatics Division, Department of Physics, Chemistry, and BiologyLinkoping UniversityLinköpingSweden
| | - Lin Yang
- National Key Laboratory of Science and Technology on Advanced Composites in Special Environments, Center for Composite Materials and StructuresHarbin Institute of TechnologyHarbinChina
- School of Aerospace, Mechanical and Mechatronic EngineeringThe University of SydneyNew South WalesAustralia
| | - Chengyu Hou
- School of Electronics and Information EngineeringHarbin Institute of TechnologyHarbinChina
| | - Xiaodong He
- National Key Laboratory of Science and Technology on Advanced Composites in Special Environments, Center for Composite Materials and StructuresHarbin Institute of TechnologyHarbinChina
- Shenzhen STRONG Advanced Materials Research Institute Col, LtdShenzhenPeople's Republic of China
| | - Shuai Guo
- National Key Laboratory of Science and Technology on Advanced Composites in Special Environments, Center for Composite Materials and StructuresHarbin Institute of TechnologyHarbinChina
| | - Shenda Jiang
- National Key Laboratory of Science and Technology on Advanced Composites in Special Environments, Center for Composite Materials and StructuresHarbin Institute of TechnologyHarbinChina
| | - Xiaoliang Ma
- National Key Laboratory of Science and Technology on Advanced Composites in Special Environments, Center for Composite Materials and StructuresHarbin Institute of TechnologyHarbinChina
| | - Rui Duan
- Dalton Cardiovascular Research CenterUniversity of MissouriColumbiaMissouriUSA
| | - Liming Qui
- Dalton Cardiovascular Research CenterUniversity of MissouriColumbiaMissouriUSA
| | - Xianjin Xu
- Dalton Cardiovascular Research CenterUniversity of MissouriColumbiaMissouriUSA
| | - Xiaoqin Zou
- Dalton Cardiovascular Research CenterUniversity of MissouriColumbiaMissouriUSA
- Dept. of Physics and AstronomyUniversity of MissouriColumbiaMissouriUSA
- Dept. of BiochemistryUniversity of MissouriColumbiaMissouriUSA
- Institute for Data Science and InformaticsUniversity of MissouriColumbiaMissouriUSA
| | - Sameer Velankar
- Protein Data Bank in Europe, European Molecular Biology LaboratoryEuropean Bioinformatics Institute (EMBL‐EBI)HinxtonCambridgeUK
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3
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Lipska A, Sieradzan AK, Atmaca S, Czaplewski C, Liwo A. Toward Consistent Physics-Based Modeling of Local Backbone Structures and Chirality Change of Proteins in Coarse-Grained Approaches. J Phys Chem Lett 2023; 14:9824-9833. [PMID: 37889895 PMCID: PMC10641867 DOI: 10.1021/acs.jpclett.3c01988] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Revised: 10/23/2023] [Accepted: 10/24/2023] [Indexed: 10/29/2023]
Abstract
A reliable representation of local interactions is critical for the accuracy of modeling protein structure and dynamics at both the all-atom and coarse-grained levels. The development of local (mainly torsional) potentials was focused on careful parametrization of the predetermined (usually Fourier) formulas rather than on their physics-based derivation. In this Perspective we discuss the state-of-the-art methods for modeling local interactions, including the scale-consistent theory developed in our laboratory, which implies that the coarse-grained torsional potentials inseparably depend on the virtual-bond angles adjacent to a given dihedral and that multitorsional terms should be considered. We extend the treatment to split the residue-based torsional potentials into the site-based regular and improper torsional potentials. These considerations are illustrated with the revised torsional potentials and improper-torsional potentials involving the l-alanine residue and the improper-torsional potential corresponding to serine-residue enantiomerization. Applications of the new approach in coarse-grained modeling and revising all-atom force fields are discussed.
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Affiliation(s)
- Agnieszka
G. Lipska
- Centre
of Informatics Tri-city Academic Supercomputer and Network (CI TASK), Gdańsk University of Technology, Fahrenheit
Union of Universities in Gdańsk, ul. G. Narutowicza 11/12, 80-233 Gdańsk, Poland
| | - Adam K. Sieradzan
- Centre
of Informatics Tri-city Academic Supercomputer and Network (CI TASK), Gdańsk University of Technology, Fahrenheit
Union of Universities in Gdańsk, ul. G. Narutowicza 11/12, 80-233 Gdańsk, Poland
- Faculty
of Chemistry, University of Gdańsk,
Fahrenheit Union of Universities, ul. Wita Stwosza 63, 80-308 Gdańsk, Poland
| | - Sümeyye Atmaca
- Kocaeli
University, Institute of Science,
Umuttepe Yerleşkesi, 41001 İzmit/Kocaeli̇, Türkiye
| | - Cezary Czaplewski
- Centre
of Informatics Tri-city Academic Supercomputer and Network (CI TASK), Gdańsk University of Technology, Fahrenheit
Union of Universities in Gdańsk, ul. G. Narutowicza 11/12, 80-233 Gdańsk, Poland
- Faculty
of Chemistry, University of Gdańsk,
Fahrenheit Union of Universities, ul. Wita Stwosza 63, 80-308 Gdańsk, Poland
| | - Adam Liwo
- Centre
of Informatics Tri-city Academic Supercomputer and Network (CI TASK), Gdańsk University of Technology, Fahrenheit
Union of Universities in Gdańsk, ul. G. Narutowicza 11/12, 80-233 Gdańsk, Poland
- Faculty
of Chemistry, University of Gdańsk,
Fahrenheit Union of Universities, ul. Wita Stwosza 63, 80-308 Gdańsk, Poland
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4
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Borges-Araújo L, Patmanidis I, Singh AP, Santos LHS, Sieradzan AK, Vanni S, Czaplewski C, Pantano S, Shinoda W, Monticelli L, Liwo A, Marrink SJ, Souza PCT. Pragmatic Coarse-Graining of Proteins: Models and Applications. J Chem Theory Comput 2023; 19:7112-7135. [PMID: 37788237 DOI: 10.1021/acs.jctc.3c00733] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/05/2023]
Abstract
The molecular details involved in the folding, dynamics, organization, and interaction of proteins with other molecules are often difficult to assess by experimental techniques. Consequently, computational models play an ever-increasing role in the field. However, biological processes involving large-scale protein assemblies or long time scale dynamics are still computationally expensive to study in atomistic detail. For these applications, employing coarse-grained (CG) modeling approaches has become a key strategy. In this Review, we provide an overview of what we call pragmatic CG protein models, which are strategies combining, at least in part, a physics-based implementation and a top-down experimental approach to their parametrization. In particular, we focus on CG models in which most protein residues are represented by at least two beads, allowing these models to retain some degree of chemical specificity. A description of the main modern pragmatic protein CG models is provided, including a review of the most recent applications and an outlook on future perspectives in the field.
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Affiliation(s)
- Luís Borges-Araújo
- Molecular Microbiology and Structural Biochemistry (MMSB, UMR 5086), CNRS, University of Lyon, 7 Passage du Vercors, 69007 Lyon, France
| | - Ilias Patmanidis
- Department of Chemistry, Aarhus University, Langelandsgade 140, 8000 Aarhus C, Denmark
- Groningen Biomolecular Sciences and Biotechnology Institute and Zernike Institute for Advanced Materials, University of Groningen, Nijenborgh 7, 9747 AG Groningen, The Netherlands
| | - Akhil P Singh
- Department of Biology, University of Fribourg, Chemin du Musée 10, Fribourg CH-1700, Switzerland
| | - Lucianna H S Santos
- Biomolecular Simulations Group, Institut Pasteur de Montevideo, Montevideo 11400, Uruguay
| | - Adam K Sieradzan
- Faculty of Chemistry, University of Gdansk, Wita Stwosza 63, 80-308 Gdansk, Poland
| | - Stefano Vanni
- Department of Biology, University of Fribourg, Chemin du Musée 10, Fribourg CH-1700, Switzerland
- Institut de Pharmacologie Moléculaire et Cellulaire, Université Côte d'Azur, Inserm, CNRS, 06560 Valbonne, France
| | - Cezary Czaplewski
- Faculty of Chemistry, University of Gdansk, Wita Stwosza 63, 80-308 Gdansk, Poland
| | - Sergio Pantano
- Biomolecular Simulations Group, Institut Pasteur de Montevideo, Montevideo 11400, Uruguay
| | - Wataru Shinoda
- Research Institute for Interdisciplinary Science, Okayama University, 3-1-1 Tsushima-naka, Kita, Okayama 700-8530, Japan
| | - Luca Monticelli
- Molecular Microbiology and Structural Biochemistry (MMSB, UMR 5086), CNRS, University of Lyon, 7 Passage du Vercors, 69007 Lyon, France
| | - Adam Liwo
- Faculty of Chemistry, University of Gdansk, Wita Stwosza 63, 80-308 Gdansk, Poland
| | - Siewert J Marrink
- Groningen Biomolecular Sciences and Biotechnology Institute and Zernike Institute for Advanced Materials, University of Groningen, Nijenborgh 7, 9747 AG Groningen, The Netherlands
| | - Paulo C T Souza
- Molecular Microbiology and Structural Biochemistry (MMSB, UMR 5086), CNRS, University of Lyon, 7 Passage du Vercors, 69007 Lyon, France
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5
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Schulze C, Danielsson A, Liwo A, Huster D, Samsonov SA, Penk A. Ligand binding of interleukin-8: a comparison of glycosaminoglycans and acidic peptides. Phys Chem Chem Phys 2023; 25:24930-24947. [PMID: 37694394 DOI: 10.1039/d3cp02457a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
Recognition and binding of regulatory proteins to glycosaminoglycans (GAGs) from the extracellular matrix is a process of high biological importance. The interaction between negatively charged sulfate or carboxyl groups of the GAGs and clusters of basic amino acids on the protein is crucial in this binding process and it is believed that electrostatics represent the key factor for this interaction. However, given the rather undirected nature of electrostatics, it is important to achieve a clear understanding of its role in protein-GAG interactions and how specificity and selectivity in these systems can be achieved, when the classical key-lock binding motif is not applicable. Here, we compare protein binding of a highly charged heparin (HP) hexasaccharide with four de novo designed decapeptides of varying negative net charge. The charge density of these peptides was comparable to typical GAGs of the extracellular matrix. We used the regulatory protein interleukin-8 (IL-8) because its interactions with GAGs are well described. All four peptide ligands bind to the same epitope of IL-8 but show much weaker binding affinity as revealed in 1H-15N HSQC NMR titration experiments. Complementary molecular docking and molecular dynamics simulations revealed further atomistic details of the interaction mode of GAG versus peptide ligands. Overall, similar contributions to the binding energy and hydrogen bond formation are determined for HP and the highly charged peptides, suggesting that the entropic loss of the peptides upon binding likely account for the remarkably different affinity of GAG versus peptide ligands to IL-8.
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Affiliation(s)
- Christian Schulze
- Institute for Medical Physics and Biophysics, University of Leipzig, Härtelstr. 16/18, 04107 Leipzig, Germany.
| | - Annemarie Danielsson
- Faculty of Chemistry, University of Gdańsk, Fahrenheit Union of Universities, ul. Wita Stwosza 63, 80-308 Gdańsk, Poland.
| | - Adam Liwo
- Faculty of Chemistry, University of Gdańsk, Fahrenheit Union of Universities, ul. Wita Stwosza 63, 80-308 Gdańsk, Poland.
| | - Daniel Huster
- Institute for Medical Physics and Biophysics, University of Leipzig, Härtelstr. 16/18, 04107 Leipzig, Germany.
| | - Sergey A Samsonov
- Faculty of Chemistry, University of Gdańsk, Fahrenheit Union of Universities, ul. Wita Stwosza 63, 80-308 Gdańsk, Poland.
| | - Anja Penk
- Institute for Medical Physics and Biophysics, University of Leipzig, Härtelstr. 16/18, 04107 Leipzig, Germany.
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6
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Danielsson A, Samsonov SA, Liwo A, Sieradzan AK. Extension of the SUGRES-1P Coarse-Grained Model of Polysaccharides to Heparin. J Chem Theory Comput 2023; 19:6023-6036. [PMID: 37587433 PMCID: PMC10500997 DOI: 10.1021/acs.jctc.3c00511] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Indexed: 08/18/2023]
Abstract
Heparin is an unbranched periodic polysaccharide composed of negatively charged monomers and involved in key biological processes, including anticoagulation, angiogenesis, and inflammation. Its structure and dynamics have been studied extensively using experimental as well as theoretical approaches. The conventional approach of computational chemistry applied to the analysis of biomolecules is all-atom molecular dynamics, which captures the interactions of individual atoms by solving Newton's equation of motion. An alternative is molecular dynamics simulations using coarse-grained models of biomacromolecules, which offer a reduction of the representation and consequently enable us to extend the time and size scale of simulations by orders of magnitude. In this work, we extend the UNIfied COarse-gRaiNed (UNICORN) model of biological macromolecules developed in our laboratory to heparin. We carried out extensive tests to estimate the optimal weights of energy terms of the effective energy function as well as the optimal Debye-Hückel screening factor for electrostatic interactions. We applied the model to study unbound heparin molecules of polymerization degree ranging from 6 to 68 residues. We compare the obtained coarse-grained heparin conformations with models obtained from X-ray diffraction studies of heparin. The SUGRES-1P force field was able to accurately predict the general shape and global characteristics of heparin molecules.
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Affiliation(s)
- Annemarie Danielsson
- Faculty of Chemistry, University
of Gdansk, ul. Wita Stwosza 63, 80-308 Gdańsk, Poland
| | - Sergey A. Samsonov
- Faculty of Chemistry, University
of Gdansk, ul. Wita Stwosza 63, 80-308 Gdańsk, Poland
| | - Adam Liwo
- Faculty of Chemistry, University
of Gdansk, ul. Wita Stwosza 63, 80-308 Gdańsk, Poland
| | - Adam K. Sieradzan
- Faculty of Chemistry, University
of Gdansk, ul. Wita Stwosza 63, 80-308 Gdańsk, Poland
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7
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Ocetkiewicz KM, Czaplewski C, Krawczyk H, Lipska AG, Liwo A, Proficz J, Sieradzan AK, Czarnul P. UNRES-GPU for Physics-Based Coarse-Grained Simulations of Protein Systems at Biological Time- and Size-Scales. Bioinformatics 2023:btad391. [PMID: 37338530 DOI: 10.1093/bioinformatics/btad391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 06/05/2023] [Accepted: 06/19/2023] [Indexed: 06/21/2023]
Abstract
SUMMARY The UNRES package for coarse-grained simulations, which has recently been optimized to treat large protein systems, has been implemented on Graphical Processor Units. An over 100-time speed up of the GPU code (run on an NVIDIA A100) with respect to the sequential code and an 8.5 speed-up with respect to the parallel (OpenMP) code (run on 32 cores of 2 AMD EPYC 7313 CPUs) has been achieved for large proteins (with size over 10,000 residues). Due to the averaging over the fine-grain degrees of freedom, 1 time unit of UNRES simulations is equivalent to about 1,000 time units of laboratory time, therefore millisecond time scale of large protein systems can be reached with the UNRES-GPU code. AVAILABILITY AND IMPLEMENTATION The complete source code of UNRES-GPU can be downloaded from https://projects.task.gda.pl/eurohpcpl-public/unres. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Krzysztof M Ocetkiewicz
- Centre of Informatics Tri-city Academic Supercomputer and Network (CI TASK), Gdańsk University of Technology, Fahrenheit Union of Universities in Gdańsk, Gdańsk, 80-233, Poland
| | - Cezary Czaplewski
- Centre of Informatics Tri-city Academic Supercomputer and Network (CI TASK), Gdańsk University of Technology, Fahrenheit Union of Universities in Gdańsk, Gdańsk, 80-233, Poland
- Faculty of Chemistry, University of Gdańsk, Fahrenheit Union of Universities in Gdańsk, Gdańsk, 80-309, Poland
| | - Henryk Krawczyk
- Centre of Informatics Tri-city Academic Supercomputer and Network (CI TASK), Gdańsk University of Technology, Fahrenheit Union of Universities in Gdańsk, Gdańsk, 80-233, Poland
- Faculty of Electronics, Telecommunications and Informatics, Gdańsk University of Technology, Fahrenheit Union of Universities in Gdańsk, Gdańsk, 80-233, Poland
| | - Agnieszka G Lipska
- Centre of Informatics Tri-city Academic Supercomputer and Network (CI TASK), Gdańsk University of Technology, Fahrenheit Union of Universities in Gdańsk, Gdańsk, 80-233, Poland
| | - Adam Liwo
- Centre of Informatics Tri-city Academic Supercomputer and Network (CI TASK), Gdańsk University of Technology, Fahrenheit Union of Universities in Gdańsk, Gdańsk, 80-233, Poland
- Faculty of Chemistry, University of Gdańsk, Fahrenheit Union of Universities in Gdańsk, Gdańsk, 80-309, Poland
| | - Jerzy Proficz
- Centre of Informatics Tri-city Academic Supercomputer and Network (CI TASK), Gdańsk University of Technology, Fahrenheit Union of Universities in Gdańsk, Gdańsk, 80-233, Poland
| | - Adam K Sieradzan
- Centre of Informatics Tri-city Academic Supercomputer and Network (CI TASK), Gdańsk University of Technology, Fahrenheit Union of Universities in Gdańsk, Gdańsk, 80-233, Poland
- Faculty of Chemistry, University of Gdańsk, Fahrenheit Union of Universities in Gdańsk, Gdańsk, 80-309, Poland
| | - Paweł Czarnul
- Faculty of Electronics, Telecommunications and Informatics, Gdańsk University of Technology, Fahrenheit Union of Universities in Gdańsk, Gdańsk, 80-233, Poland
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8
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Liwo A, Pyrka M, Czaplewski C, Peng X, Niemi AJ. Long-Time Dynamics of Selected Molecular-Motor Components Using a Physics-Based Coarse-Grained Approach. Biomolecules 2023; 13:941. [PMID: 37371521 DOI: 10.3390/biom13060941] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Revised: 05/26/2023] [Accepted: 05/30/2023] [Indexed: 06/29/2023] Open
Abstract
Molecular motors are essential for the movement and transportation of macromolecules in living organisms. Among them, rotatory motors are particularly efficient. In this study, we investigated the long-term dynamics of the designed left-handed alpha/alpha toroid (PDB: 4YY2), the RBM2 flagellum protein ring from Salmonella (PDB: 6SD5), and the V-type Na+-ATPase rotor in Enterococcus hirae (PDB: 2BL2) using microcanonical and canonical molecular dynamics simulations with the coarse-grained UNRES force field, including a lipid-membrane model, on a millisecond laboratory time scale. Our results demonstrate that rotational motion can occur with zero total angular momentum in the microcanonical regime and that thermal motions can be converted into net rotation in the canonical regime, as previously observed in simulations of smaller cyclic molecules. For 6SD5 and 2BL2, net rotation (with a ratcheting pattern) occurring only about the pivot of the respective system was observed in canonical simulations. The extent and direction of the rotation depended on the initial conditions. This result suggests that rotatory molecular motors can convert thermal oscillations into net rotational motion. The energy from ATP hydrolysis is required probably to set the direction and extent of rotation. Our findings highlight the importance of molecular-motor structures in facilitating movement and transportation within living organisms.
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Affiliation(s)
- Adam Liwo
- Faculty of Chemistry, University of Gdańsk, Fahrenheit Union of Universities, Wita Stwosza 63, 80-308 Gdańsk, Poland
| | - Maciej Pyrka
- Faculty of Chemistry, University of Gdańsk, Fahrenheit Union of Universities, Wita Stwosza 63, 80-308 Gdańsk, Poland
- Department of Physics and Biophysics, University of Warmia and Mazury, ul. Oczapowskiego 4, 10-719 Olsztyn, Poland
| | - Cezary Czaplewski
- Faculty of Chemistry, University of Gdańsk, Fahrenheit Union of Universities, Wita Stwosza 63, 80-308 Gdańsk, Poland
| | - Xubiao Peng
- Center for Quantum Technology Research, Key Laboratory of Advanced Optoelectronic Quantum Architecture and Measurements (MOE), School of Physics, Beijing Institute of Technology, Beijing 100081, China
| | - Antti J Niemi
- Nordita, Stockholm University and Uppsala University, Roslagstullsbacken 23, SE-106 91 Stockholm, Sweden
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9
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Lipska AG, Sieradzan AK, Czaplewski C, Lipińska AD, Ocetkiewicz KM, Proficz J, Czarnul P, Krawczyk H, Liwo A. Long-time scale simulations of virus-like particles from three human-norovirus strains. J Comput Chem 2023; 44:1470-1483. [PMID: 36799410 DOI: 10.1002/jcc.27087] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 12/22/2022] [Accepted: 01/29/2023] [Indexed: 02/18/2023]
Abstract
The dynamics of the virus like particles (VLPs) corresponding to the GII.4 Houston, GII.2 SMV, and GI.1 Norwalk strains of human noroviruses (HuNoV) that cause gastroenteritis was investigated by means of long-time (about 30 μs in the laboratory timescale) molecular dynamics simulations with the coarse-grained UNRES force field. The main motion of VLP units turned out to be the bending at the junction between the P1 subdomain (that sits in the VLP shell) and the P2 subdomain (that protrudes outside) of the major VP1 protein, this resulting in a correlated wagging motion of the P2 subdomains with respect to the VLP surface. The fluctuations of the P2 subdomain were found to be more pronounced and the P2 domain made a greater angle with the normal to the VLP surface for the GII.2 strain, which could explain the inability of this strain to bind the histo-blood group antigens (HBGAs).
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Affiliation(s)
- Agnieszka G Lipska
- Centre of Informatics Tri-city Academic Supercomputer and Network (CI TASK), Gdańsk University of Technology, Fahrenheit Union of Universities in Gdańsk, Gdańsk, Poland
| | - Adam K Sieradzan
- Centre of Informatics Tri-city Academic Supercomputer and Network (CI TASK), Gdańsk University of Technology, Fahrenheit Union of Universities in Gdańsk, Gdańsk, Poland.,Faculty of Chemistry, University of Gdańsk, Fahrenheit Union of Universities in Gdańsk, Gdańsk, Poland
| | - Cezary Czaplewski
- Centre of Informatics Tri-city Academic Supercomputer and Network (CI TASK), Gdańsk University of Technology, Fahrenheit Union of Universities in Gdańsk, Gdańsk, Poland.,Faculty of Chemistry, University of Gdańsk, Fahrenheit Union of Universities in Gdańsk, Gdańsk, Poland
| | - Andrea D Lipińska
- Laboratory of Virus Molecular Biology, Intercollegiate Faculty of Biotechnology, University of Gdańsk and Medical University of Gdańsk, Fahrenheit Union of Universities in Gdańsk, Gdańsk, Poland
| | - Krzysztof M Ocetkiewicz
- Centre of Informatics Tri-city Academic Supercomputer and Network (CI TASK), Gdańsk University of Technology, Fahrenheit Union of Universities in Gdańsk, Gdańsk, Poland
| | - Jerzy Proficz
- Centre of Informatics Tri-city Academic Supercomputer and Network (CI TASK), Gdańsk University of Technology, Fahrenheit Union of Universities in Gdańsk, Gdańsk, Poland
| | - Paweł Czarnul
- Faculty of Electronics, Telecommunications and Informatics, Gdańsk University of Technology, Fahrenheit Union of Universities in Gdańsk, Gdańsk, Poland
| | - Henryk Krawczyk
- Centre of Informatics Tri-city Academic Supercomputer and Network (CI TASK), Gdańsk University of Technology, Fahrenheit Union of Universities in Gdańsk, Gdańsk, Poland.,Faculty of Electronics, Telecommunications and Informatics, Gdańsk University of Technology, Fahrenheit Union of Universities in Gdańsk, Gdańsk, Poland
| | - Adam Liwo
- Centre of Informatics Tri-city Academic Supercomputer and Network (CI TASK), Gdańsk University of Technology, Fahrenheit Union of Universities in Gdańsk, Gdańsk, Poland.,Faculty of Chemistry, University of Gdańsk, Fahrenheit Union of Universities in Gdańsk, Gdańsk, Poland
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10
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Sieradzan AK, Sans-Duñó J, Lubecka EA, Czaplewski C, Lipska AG, Leszczyński H, Ocetkiewicz KM, Proficz J, Czarnul P, Krawczyk H, Liwo A. Optimization of parallel implementation of UNRES package for coarse-grained simulations to treat large proteins. J Comput Chem 2023; 44:602-625. [PMID: 36378078 DOI: 10.1002/jcc.27026] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Revised: 09/19/2022] [Accepted: 10/17/2022] [Indexed: 11/16/2022]
Abstract
We report major algorithmic improvements of the UNRES package for physics-based coarse-grained simulations of proteins. These include (i) introduction of interaction lists to optimize computations, (ii) transforming the inertia matrix to a pentadiagonal form to reduce computing and memory requirements, (iii) removing explicit angles and dihedral angles from energy expressions and recoding the most time-consuming energy/force terms to minimize the number of operations and to improve numerical stability, (iv) using OpenMP to parallelize those sections of the code for which distributed-memory parallelization involves unfavorable computing/communication time ratio, and (v) careful memory management to minimize simultaneous access of distant memory sections. The new code enables us to run molecular dynamics simulations of protein systems with size exceeding 100,000 amino-acid residues, reaching over 1 ns/day (1 μs/day in all-atom timescale) with 24 cores for proteins of this size. Parallel performance of the code and comparison of its performance with that of AMBER, GROMACS and MARTINI 3 is presented.
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Affiliation(s)
- Adam K Sieradzan
- Faculty of Chemistry, University of Gdańsk, Fahrenheit Union of Universities in Gdańsk, Gdańsk, Poland.,Centre of Informatics Tri-city Academic Supercomputer and Network (CI TASK), Gdańsk University of Technology, Fahrenheit Union of Universities in Gdańsk, Gdańsk, Poland
| | - Jordi Sans-Duñó
- Department of Chemistry, University of Lleida, Lleida, Spain
| | - Emilia A Lubecka
- Faculty of Electronics, Telecommunication and Informatics, Gdańsk University of Technology, Fahrenheit Union of Universities in Gdańsk, Gdańsk, Poland
| | - Cezary Czaplewski
- Faculty of Chemistry, University of Gdańsk, Fahrenheit Union of Universities in Gdańsk, Gdańsk, Poland.,Centre of Informatics Tri-city Academic Supercomputer and Network (CI TASK), Gdańsk University of Technology, Fahrenheit Union of Universities in Gdańsk, Gdańsk, Poland
| | - Agnieszka G Lipska
- Faculty of Chemistry, University of Gdańsk, Fahrenheit Union of Universities in Gdańsk, Gdańsk, Poland.,Centre of Informatics Tri-city Academic Supercomputer and Network (CI TASK), Gdańsk University of Technology, Fahrenheit Union of Universities in Gdańsk, Gdańsk, Poland
| | - Henryk Leszczyński
- Faculty of Mathematics, Physics and Informatics, University of Gdańsk, Fahrenheit Union of Universities in Gdańsk, Gdańsk, Poland
| | - Krzysztof M Ocetkiewicz
- Centre of Informatics Tri-city Academic Supercomputer and Network (CI TASK), Gdańsk University of Technology, Fahrenheit Union of Universities in Gdańsk, Gdańsk, Poland
| | - Jerzy Proficz
- Centre of Informatics Tri-city Academic Supercomputer and Network (CI TASK), Gdańsk University of Technology, Fahrenheit Union of Universities in Gdańsk, Gdańsk, Poland
| | - Paweł Czarnul
- Faculty of Electronics, Telecommunication and Informatics, Gdańsk University of Technology, Fahrenheit Union of Universities in Gdańsk, Gdańsk, Poland
| | - Henryk Krawczyk
- Centre of Informatics Tri-city Academic Supercomputer and Network (CI TASK), Gdańsk University of Technology, Fahrenheit Union of Universities in Gdańsk, Gdańsk, Poland.,Faculty of Electronics, Telecommunication and Informatics, Gdańsk University of Technology, Fahrenheit Union of Universities in Gdańsk, Gdańsk, Poland
| | - Adam Liwo
- Faculty of Chemistry, University of Gdańsk, Fahrenheit Union of Universities in Gdańsk, Gdańsk, Poland.,Centre of Informatics Tri-city Academic Supercomputer and Network (CI TASK), Gdańsk University of Technology, Fahrenheit Union of Universities in Gdańsk, Gdańsk, Poland
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11
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Chen SJ, Hassan M, Jernigan RL, Jia K, Kihara D, Kloczkowski A, Kotelnikov S, Kozakov D, Liang J, Liwo A, Matysiak S, Meller J, Micheletti C, Mitchell JC, Mondal S, Nussinov R, Okazaki KI, Padhorny D, Skolnick J, Sosnick TR, Stan G, Vakser I, Zou X, Rose GD. Opinion: Protein folds vs. protein folding: Differing questions, different challenges. Proc Natl Acad Sci U S A 2023; 120:e2214423119. [PMID: 36580595 PMCID: PMC9910419 DOI: 10.1073/pnas.2214423119] [Citation(s) in RCA: 23] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Affiliation(s)
- Shi-Jie Chen
- Department of Physics, Department of Biochemistry, and Institute for Data Science and Informatics, University of Missouri, Columbia, MO65211
| | - Mubashir Hassan
- The Steve and Cindy Rasmussen Institute for Genomic Medicine, Nationwide Children’s Hospital, Columbus, OH43205
| | - Robert L. Jernigan
- Bioinformatics and Computational Biology Program and Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, IA50011
| | - Kejue Jia
- Bioinformatics and Computational Biology Program and Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology Iowa State University, Ames, IA50011
| | - Daisuke Kihara
- Department of Biological Sciences, Department of Computer Science Purdue University, West Lafayette, IN79075
| | - Andrzej Kloczkowski
- Department of Pediatrics, The Steve and Cindy Rasmussen Institute for Genomic Medicine, Nationwide Children’s Hospital, The Ohio State University, Columbus, OH43205
| | - Sergei Kotelnikov
- Department of Applied Mathematics and Statistics, Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY11794
| | - Dima Kozakov
- Frey Family Foundation, Department of Applied Mathematics and Statistics, Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY11794
| | - Jie Liang
- Richard and Loan Hill Dept of Biomedical Engineering, University of Illinois at Chicago, Chicago, IL60607
| | - Adam Liwo
- Faculty of Chemistry, University of Gdansk, Fahrenheit Union of Universities, ul. Wita Stwosza 63, Gdansk80-308, Poland
| | - Silvina Matysiak
- Fischell Department of Bioengineering, University of Maryland, College Park, MD20742
| | - Jarek Meller
- University of Cincinnati & Cincinnati Children’s Hospital Medical Center, Cincinnati, OH45229
| | - Cristian Micheletti
- SISSA - International School for Advanced Studies, Via Bonomea 265, TriesteI-34136, Italy
| | | | | | - Ruth Nussinov
- Computational Structural Biology Section, National Laboratory for Cancer Research in the Cancer Innovation Laboratory, National Cancer Institute, Frederick, MD21702
- Department of Human Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv69978, Israel
| | - Kei-ichi Okazaki
- Research Center for Computational Science, Institute for Molecular Science, Okazaki, Aichi444-8585, Japan
| | - Dzmitry Padhorny
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY11794
| | - Jeffrey Skolnick
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA30332
| | - Tobin R. Sosnick
- Department of Biochemistry and Molecular Biology, University of Chicago, Chicago, IL60637
| | - George Stan
- Department of Chemistry, University of Cincinnati, Cincinnati, OH45221
| | - Ilya Vakser
- Computational Biology Program and Center for Computational Biology, Department of Molecular Biosciences, The University of Kansas, Lawrence, KS66045
| | - Xiaoqin Zou
- Department of Physics and Astronomy, Department of Biochemistry, Dalton Cardiovascular Research Center, Institute for Data Science and Informatics, University of Missouri, Columbia, MO65211
| | - George D. Rose
- Jenkins Department of Biophysics, Johns Hopkins University, Baltimore, MD21218
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12
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Sikorska C, Liwo A. Correction to "Origin of Correlations between Local Conformational States of Consecutive Amino-Acid Residues and Their Role in Shaping Protein Structures and in Allostery". J Phys Chem B 2022; 127:425-426. [PMID: 36548477 PMCID: PMC9841556 DOI: 10.1021/acs.jpcb.2c08574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
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13
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Ślusarz R, Lubecka EA, Czaplewski C, Liwo A. Improvements and new functionalities of UNRES server for coarse-grained modeling of protein structure, dynamics, and interactions. Front Mol Biosci 2022; 9:1071428. [PMID: 36589235 PMCID: PMC9794589 DOI: 10.3389/fmolb.2022.1071428] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2022] [Accepted: 11/29/2022] [Indexed: 12/15/2022] Open
Abstract
In this paper we report the improvements and extensions of the UNRES server (https://unres-server.chem.ug.edu.pl) for physics-based simulations with the coarse-grained UNRES model of polypeptide chains. The improvements include the replacement of the old code with the recently optimized one and adding the recent scale-consistent variant of the UNRES force field, which performs better in the modeling of proteins with the β and the α+β structures. The scope of applications of the package was extended to data-assisted simulations with restraints from nuclear magnetic resonance (NMR) and chemical crosslink mass-spectroscopy (XL-MS) measurements. NMR restraints can be input in the NMR Exchange Format (NEF), which has become a standard. Ambiguous NMR restraints are handled without expert intervention owing to a specially designed penalty function. The server can be used to run smaller jobs directly or to prepare input data to run larger production jobs by using standalone installations of UNRES.
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Affiliation(s)
- Rafał Ślusarz
- Faculty of Chemistry, University of Gdańsk, Fahrenheit Union of Universities in Gdańsk, Gdańsk, Poland
| | - Emilia A. Lubecka
- Faculty of Electronics, Telecommunication and Informatics, Gdańsk University of Technology, Fahrenheit Union of Universities in Gdańsk, Gdańsk, Poland
| | - Cezary Czaplewski
- Faculty of Chemistry, University of Gdańsk, Fahrenheit Union of Universities in Gdańsk, Gdańsk, Poland
| | - Adam Liwo
- Faculty of Chemistry, University of Gdańsk, Fahrenheit Union of Universities in Gdańsk, Gdańsk, Poland,*Correspondence: Adam Liwo,
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14
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Sikorska C, Liwo A. Origin of Correlations between Local Conformational States of Consecutive Amino Acid Residues and Their Role in Shaping Protein Structures and in Allostery. J Phys Chem B 2022; 126:9493-9505. [PMID: 36367920 PMCID: PMC9706564 DOI: 10.1021/acs.jpcb.2c04610] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
By analyzing the Kubo-cluster-cumulant expansion of the potential of mean force of polypeptide chains corresponding to backbone-local interactions averaged over the rotation of the peptide groups about the Cα···Cα virtual bonds, we identified two important kinds of "along-chain" correlations that pertain to extended chain segments bordered by turns (usually the β-strands) and to the folded spring-like segments (usually α-helices), respectively, and are expressed as multitorsional potentials. These terms affect the positioning of structural elements with respect to each other and, consequently, contribute to determining their packing. Additionally, for extended chain segments, the correlation terms contribute to propagating the conformational change at one end to the other end, which is characteristic of allosteric interactions. We confirmed both findings by statistical analysis of the virtual-bond geometry of 77 950 proteins. Augmenting coarse-grained and, possibly, all-atom force fields with these correlation terms could improve their capacity to model protein structure and dynamics.
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Affiliation(s)
- Celina Sikorska
- The
MacDiarmid Institute for Advanced Materials and Nanotechnology, Department
of Physics, The University of Auckland,
Private Bag 92019, Auckland1142, New Zealand
| | - Adam Liwo
- Faculty
of Chemistry, University of Gdańsk,
Fahrenheit Union of Universities in Gdańsk, Wita Stwosza 63, 80-308Gdańsk, Poland,. Phone: +48585235124. Fax: +48585235012
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15
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Lubecka EA, Liwo A. A coarse-grained approach to NMR-data-assisted modeling of protein structures. J Comput Chem 2022; 43:2047-2059. [PMID: 36134668 DOI: 10.1002/jcc.27003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 08/03/2022] [Accepted: 09/05/2022] [Indexed: 11/06/2022]
Abstract
The ESCASA algorithm for analytical estimation of proton positions from coarse-grained geometry developed in our recent work has been implemented in modeling protein structures with the highly coarse-grained UNRES model of polypeptide chains (two sites per residue) and nuclear magnetic resonance (NMR) data. A penalty function with the shape of intersecting gorges was applied to treat ambiguous distance restraints, which automatically selects consistent restraints. Hamiltonian replica exchange molecular dynamics was used to carry out the conformational search. The method was tested with both unambiguous and ambiguous restraints producing good-quality models with GDT_TS from 7.4 units higher to 14.4 units lower than those obtained with the CYANA or MELD software for protein-structure determination from NMR data at the all-atom resolution. The method can thus be applied in modeling the structures of flexible proteins, for which extensive conformational search enabled by coarse-graining is more important than high modeling accuracy.
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Affiliation(s)
- Emilia A Lubecka
- Faculty of Electronics, Telecommunications and Informatics, Gdańsk University of Technology, Gdańsk, Poland
| | - Adam Liwo
- Faculty of Chemistry, University of Gdańsk, Gdańsk, Poland
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16
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Bogunia M, Liwo A, Czaplewski C, Makowska J, Giełdoń A, Makowski M. Influence of Temperature and Salt Concentration on the Hydrophobic Interactions of Adamantane and Hexane. J Phys Chem B 2022; 126:634-642. [PMID: 35025490 PMCID: PMC8802301 DOI: 10.1021/acs.jpcb.1c09860] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
![]()
One of the definitions
of hydrophobic interactions is the aggregation
of nonpolar particles in a polar solvent, such as water. While this
phenomenon appears to be very simple, it is crucial for many complex
processes, such as protein folding, to take place. In this work, the
hydrophobic association of adamantane and hexane at various temperatures
and ionic strengths was studied using molecular dynamics simulations
with the AMBER 16.0 program and the GAFF force field. The potentials
of mean force of hydrophobic dimer formation, as well as the excess
free energy, excess energy, excess entropy, and excess heat capacity
corresponding to the formation of the contact minimum, were determined
and analyzed. For both systems, the depth of the contact minimum in
the potential of mean force was found to increase with both temperature
and ionic strength. The excess heat capacity of the association at
the contact minimum and T = 298 K was found to be
negative and to decrease, while the excess entropy and energy were
found to be positive and to increase for both systems, the changes
being more pronounced for the hexane dimer. The excess heat capacity
is also greater in absolute value for the hexane dimer.
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Affiliation(s)
- Małgorzata Bogunia
- Faculty of Chemistry, University of Gdańsk, ul. Wita Stwosza 63, Gdańsk 80-308, Poland
| | - Adam Liwo
- Faculty of Chemistry, University of Gdańsk, ul. Wita Stwosza 63, Gdańsk 80-308, Poland
| | - Cezary Czaplewski
- Faculty of Chemistry, University of Gdańsk, ul. Wita Stwosza 63, Gdańsk 80-308, Poland
| | - Joanna Makowska
- Faculty of Chemistry, University of Gdańsk, ul. Wita Stwosza 63, Gdańsk 80-308, Poland
| | - Artur Giełdoń
- Faculty of Chemistry, University of Gdańsk, ul. Wita Stwosza 63, Gdańsk 80-308, Poland
| | - Mariusz Makowski
- Faculty of Chemistry, University of Gdańsk, ul. Wita Stwosza 63, Gdańsk 80-308, Poland
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17
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Czaplewski C, Gong Z, Lubecka EA, Xue K, Tang C, Liwo A. Recent Developments in Data-Assisted Modeling of Flexible Proteins. Front Mol Biosci 2022; 8:765562. [PMID: 35004845 PMCID: PMC8740120 DOI: 10.3389/fmolb.2021.765562] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Accepted: 12/06/2021] [Indexed: 11/13/2022] Open
Abstract
Many proteins can fold into well-defined conformations. However, intrinsically-disordered proteins (IDPs) do not possess a defined structure. Moreover, folded multi-domain proteins often digress into alternative conformations. Collectively, the conformational dynamics enables these proteins to fulfill specific functions. Thus, most experimental observables are averaged over the conformations that constitute an ensemble. In this article, we review the recent developments in the concept and methods for the determination of the dynamic structures of flexible peptides and proteins. In particular, we describe ways to extract information from nuclear magnetic resonance small-angle X-ray scattering (SAXS), and chemical cross-linking coupled with mass spectroscopy (XL-MS) measurements. All these techniques can be used to obtain ensemble-averaged restraints or to re-weight the simulated conformational ensembles.
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Affiliation(s)
| | - Zhou Gong
- Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, China
| | - Emilia A Lubecka
- Faculty of Electronics, Telecommunications and Informatics, Gdańsk University of Technology, Gdańsk, Poland
| | - Kai Xue
- PKU-Tsinghua Center for Life Sciences, Beijing National Laboratory for Molecular Sciences, College of Chemistry and Molecular Engineering, Peking University, Beijing, China
| | - Chun Tang
- PKU-Tsinghua Center for Life Sciences, Beijing National Laboratory for Molecular Sciences, College of Chemistry and Molecular Engineering, Peking University, Beijing, China
| | - Adam Liwo
- Faculty of Chemistry, University of Gdańsk, Gdańsk, Poland
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18
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Rojas AV, Maisuradze GG, Scheraga HA, Liwo A. Probing Protein Aggregation Using the Coarse-Grained UNRES Force Field. Methods Mol Biol 2022; 2340:79-104. [PMID: 35167071 DOI: 10.1007/978-1-0716-1546-1_5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Protein aggregation is the cause of many, often lethal, diseases, including the Alzheimer's, Parkinson's, and Huntington's diseases, and familial amyloidosis. Theoretical investigation of the mechanism of this process, including the structures of the oligomeric intermediates which are the most toxic, is difficult because of long time scale of aggregation. Coarse-grained models, which enable us to extend the simulation time scale by three or more orders of magnitude, are, therefore, of great advantage in such studies. In this chapter, we describe the application of the physics-based UNited RESidue (UNRES) force field developed in our laboratory to study protein aggregation, in both free simulations and simulations of aggregation propagation from an existing template (seed), and illustrate it with the examples of Aβ-peptide aggregation and Aβ-peptide-assisted aggregation of the peptides derived from the repeat domains of tau (TauRD).
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Affiliation(s)
- Ana V Rojas
- Schrodinger Inc., 120 West 45th Street New York, New York, 10036, NY, USA
| | - Gia G Maisuradze
- Baker Laboratory of Chemistry and Chemical Biology, Cornell University, Ithaca, 14853-1301, NY, USA
| | - Harold A Scheraga
- Baker Laboratory of Chemistry and Chemical Biology, Cornell University, Ithaca, 14853-1301, NY, USA
| | - Adam Liwo
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, Gdańsk, 80-308, Poland.
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19
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Lensink MF, Brysbaert G, Mauri T, Nadzirin N, Velankar S, Chaleil RAG, Clarence T, Bates PA, Kong R, Liu B, Yang G, Liu M, Shi H, Lu X, Chang S, Roy RS, Quadir F, Liu J, Cheng J, Antoniak A, Czaplewski C, Giełdoń A, Kogut M, Lipska AG, Liwo A, Lubecka EA, Maszota-Zieleniak M, Sieradzan AK, Ślusarz R, Wesołowski PA, Zięba K, Del Carpio Muñoz CA, Ichiishi E, Harmalkar A, Gray JJ, Bonvin AMJJ, Ambrosetti F, Vargas Honorato R, Jandova Z, Jiménez-García B, Koukos PI, Van Keulen S, Van Noort CW, Réau M, Roel-Touris J, Kotelnikov S, Padhorny D, Porter KA, Alekseenko A, Ignatov M, Desta I, Ashizawa R, Sun Z, Ghani U, Hashemi N, Vajda S, Kozakov D, Rosell M, Rodríguez-Lumbreras LA, Fernandez-Recio J, Karczynska A, Grudinin S, Yan Y, Li H, Lin P, Huang SY, Christoffer C, Terashi G, Verburgt J, Sarkar D, Aderinwale T, Wang X, Kihara D, Nakamura T, Hanazono Y, Gowthaman R, Guest JD, Yin R, Taherzadeh G, Pierce BG, Barradas-Bautista D, Cao Z, Cavallo L, Oliva R, Sun Y, Zhu S, Shen Y, Park T, Woo H, Yang J, Kwon S, Won J, Seok C, Kiyota Y, Kobayashi S, Harada Y, Takeda-Shitaka M, Kundrotas PJ, Singh A, Vakser IA, Dapkūnas J, Olechnovič K, Venclovas Č, Duan R, Qiu L, Xu X, Zhang S, Zou X, Wodak SJ. Prediction of protein assemblies, the next frontier: The CASP14-CAPRI experiment. Proteins 2021; 89:1800-1823. [PMID: 34453465 PMCID: PMC8616814 DOI: 10.1002/prot.26222] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Revised: 07/24/2021] [Accepted: 08/05/2021] [Indexed: 12/19/2022]
Abstract
We present the results for CAPRI Round 50, the fourth joint CASP-CAPRI protein assembly prediction challenge. The Round comprised a total of twelve targets, including six dimers, three trimers, and three higher-order oligomers. Four of these were easy targets, for which good structural templates were available either for the full assembly, or for the main interfaces (of the higher-order oligomers). Eight were difficult targets for which only distantly related templates were found for the individual subunits. Twenty-five CAPRI groups including eight automatic servers submitted ~1250 models per target. Twenty groups including six servers participated in the CAPRI scoring challenge submitted ~190 models per target. The accuracy of the predicted models was evaluated using the classical CAPRI criteria. The prediction performance was measured by a weighted scoring scheme that takes into account the number of models of acceptable quality or higher submitted by each group as part of their five top-ranking models. Compared to the previous CASP-CAPRI challenge, top performing groups submitted such models for a larger fraction (70-75%) of the targets in this Round, but fewer of these models were of high accuracy. Scorer groups achieved stronger performance with more groups submitting correct models for 70-80% of the targets or achieving high accuracy predictions. Servers performed less well in general, except for the MDOCKPP and LZERD servers, who performed on par with human groups. In addition to these results, major advances in methodology are discussed, providing an informative overview of where the prediction of protein assemblies currently stands.
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Affiliation(s)
- Marc F Lensink
- CNRS UMR8576 UGSF, Institute for Structural and Functional Glycobiology, University of Lille, Lille, France
| | - Guillaume Brysbaert
- CNRS UMR8576 UGSF, Institute for Structural and Functional Glycobiology, University of Lille, Lille, France
| | - Théo Mauri
- CNRS UMR8576 UGSF, Institute for Structural and Functional Glycobiology, University of Lille, Lille, France
| | - Nurul Nadzirin
- Protein Data Bank in Europe (PDBe), European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, UK
| | - Sameer Velankar
- Protein Data Bank in Europe (PDBe), European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, UK
| | | | - Tereza Clarence
- Biomolecular Modelling Laboratory, The Francis Crick Institute, London, UK
| | - Paul A Bates
- Biomolecular Modelling Laboratory, The Francis Crick Institute, London, UK
| | - Ren Kong
- Institute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou, China
| | - Bin Liu
- Institute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou, China
| | - Guangbo Yang
- Institute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou, China
| | - Ming Liu
- Institute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou, China
| | - Hang Shi
- Institute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou, China
| | - Xufeng Lu
- Institute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou, China
| | - Shan Chang
- Institute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou, China
| | - Raj S Roy
- Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, Missouri, USA
| | - Farhan Quadir
- Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, Missouri, USA
| | - Jian Liu
- Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, Missouri, USA
| | - Jianlin Cheng
- Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, Missouri, USA
- Institute for Data Science and Informatics, University of Missouri, Columbia, Missouri, USA
| | - Anna Antoniak
- Faculty of Chemistry, University of Gdansk, Gdansk, Poland
| | | | - Artur Giełdoń
- Faculty of Chemistry, University of Gdansk, Gdansk, Poland
| | - Mateusz Kogut
- Faculty of Chemistry, University of Gdansk, Gdansk, Poland
| | | | - Adam Liwo
- Faculty of Chemistry, University of Gdansk, Gdansk, Poland
| | - Emilia A Lubecka
- Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, Gdansk, Poland
| | | | | | - Rafał Ślusarz
- Faculty of Chemistry, University of Gdansk, Gdansk, Poland
| | - Patryk A Wesołowski
- Faculty of Chemistry, University of Gdansk, Gdansk, Poland
- Intercollegiate Faculty of Biotechnology, University of Gdansk and Medical University of Gdansk, Gdansk, Poland
| | - Karolina Zięba
- Faculty of Chemistry, University of Gdansk, Gdansk, Poland
| | | | - Eiichiro Ichiishi
- International University of Health and Welfare Hospital (IUHW Hospital), Nasushiobara City, Japan
| | - Ameya Harmalkar
- Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland, USA
| | - Jeffrey J Gray
- Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland, USA
| | - Alexandre M J J Bonvin
- Computational Structural Biology Group, Bijvoet Centre for Biomolecular Research, Department of Chemistry, Faculty of Science, Utrecht University, Utrecht, The Netherlands
| | - Francesco Ambrosetti
- Computational Structural Biology Group, Bijvoet Centre for Biomolecular Research, Department of Chemistry, Faculty of Science, Utrecht University, Utrecht, The Netherlands
| | - Rodrigo Vargas Honorato
- Computational Structural Biology Group, Bijvoet Centre for Biomolecular Research, Department of Chemistry, Faculty of Science, Utrecht University, Utrecht, The Netherlands
| | - Zuzana Jandova
- Computational Structural Biology Group, Bijvoet Centre for Biomolecular Research, Department of Chemistry, Faculty of Science, Utrecht University, Utrecht, The Netherlands
| | - Brian Jiménez-García
- Computational Structural Biology Group, Bijvoet Centre for Biomolecular Research, Department of Chemistry, Faculty of Science, Utrecht University, Utrecht, The Netherlands
| | - Panagiotis I Koukos
- Computational Structural Biology Group, Bijvoet Centre for Biomolecular Research, Department of Chemistry, Faculty of Science, Utrecht University, Utrecht, The Netherlands
| | - Siri Van Keulen
- Computational Structural Biology Group, Bijvoet Centre for Biomolecular Research, Department of Chemistry, Faculty of Science, Utrecht University, Utrecht, The Netherlands
| | - Charlotte W Van Noort
- Computational Structural Biology Group, Bijvoet Centre for Biomolecular Research, Department of Chemistry, Faculty of Science, Utrecht University, Utrecht, The Netherlands
| | - Manon Réau
- Computational Structural Biology Group, Bijvoet Centre for Biomolecular Research, Department of Chemistry, Faculty of Science, Utrecht University, Utrecht, The Netherlands
| | - Jorge Roel-Touris
- Computational Structural Biology Group, Bijvoet Centre for Biomolecular Research, Department of Chemistry, Faculty of Science, Utrecht University, Utrecht, The Netherlands
| | - Sergei Kotelnikov
- Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York, USA
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York, USA
- Innopolis University, Russia
| | - Dzmitry Padhorny
- Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York, USA
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York, USA
| | - Kathryn A Porter
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts, USA
| | - Andrey Alekseenko
- Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York, USA
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York, USA
- Institute of Computer-Aided Design of the Russian Academy of Sciences, Moscow, Russia
| | - Mikhail Ignatov
- Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York, USA
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York, USA
| | - Israel Desta
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts, USA
| | - Ryota Ashizawa
- Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York, USA
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York, USA
| | - Zhuyezi Sun
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts, USA
| | - Usman Ghani
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts, USA
| | - Nasser Hashemi
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts, USA
| | - Sandor Vajda
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts, USA
- Department of Chemistry, Boston University, Boston, Massachusetts, USA
| | - Dima Kozakov
- Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, New York, USA
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York, USA
| | - Mireia Rosell
- Instituto de Ciencias de la Vid y del Vino (ICVV), CSIC - Universidad de la Rioja - Gobierno de La Rioja, Logrono, Spain
- Barcelona Supercomputing Center (BSC), Barcelona, Spain
| | - Luis A Rodríguez-Lumbreras
- Instituto de Ciencias de la Vid y del Vino (ICVV), CSIC - Universidad de la Rioja - Gobierno de La Rioja, Logrono, Spain
- Barcelona Supercomputing Center (BSC), Barcelona, Spain
| | - Juan Fernandez-Recio
- Instituto de Ciencias de la Vid y del Vino (ICVV), CSIC - Universidad de la Rioja - Gobierno de La Rioja, Logrono, Spain
- Barcelona Supercomputing Center (BSC), Barcelona, Spain
| | | | - Sergei Grudinin
- Université Grenoble Alpes, Inria, CNRS, Grenoble INP, LJK, Grenoble, France
| | - Yumeng Yan
- School of Physics, Huazhong University of Science and Technology, Wuhan, China
| | - Hao Li
- School of Physics, Huazhong University of Science and Technology, Wuhan, China
| | - Peicong Lin
- School of Physics, Huazhong University of Science and Technology, Wuhan, China
| | - Sheng-You Huang
- School of Physics, Huazhong University of Science and Technology, Wuhan, China
| | - Charles Christoffer
- Department of Computer Science, Purdue University, West Lafayette, Indiana, USA
| | - Genki Terashi
- Department of Biological Sciences, Purdue University, West Lafayette, Indiana, USA
| | - Jacob Verburgt
- Department of Biological Sciences, Purdue University, West Lafayette, Indiana, USA
| | - Daipayan Sarkar
- Department of Biological Sciences, Purdue University, West Lafayette, Indiana, USA
| | - Tunde Aderinwale
- Department of Computer Science, Purdue University, West Lafayette, Indiana, USA
| | - Xiao Wang
- Department of Computer Science, Purdue University, West Lafayette, Indiana, USA
| | - Daisuke Kihara
- Department of Computer Science, Purdue University, West Lafayette, Indiana, USA
- Department of Biological Sciences, Purdue University, West Lafayette, Indiana, USA
| | - Tsukasa Nakamura
- Graduate School of Information Sciences, Tohoku University, Sendai, Miyagi, Japan
| | - Yuya Hanazono
- Institute for Quantum Life Science, National Institutes for Quantum and Radiological Science and Technology, Tokai, Ibaraki, Japan
| | - Ragul Gowthaman
- University of Maryland Institute for Bioscience and Biotechnology Research, Rockville, Maryland, USA
- Department of Cell Biology and Molecular Genetics, University of Maryland, Maryland, USA
| | - Johnathan D Guest
- University of Maryland Institute for Bioscience and Biotechnology Research, Rockville, Maryland, USA
- Department of Cell Biology and Molecular Genetics, University of Maryland, Maryland, USA
| | - Rui Yin
- University of Maryland Institute for Bioscience and Biotechnology Research, Rockville, Maryland, USA
- Department of Cell Biology and Molecular Genetics, University of Maryland, Maryland, USA
| | - Ghazaleh Taherzadeh
- University of Maryland Institute for Bioscience and Biotechnology Research, Rockville, Maryland, USA
- Department of Cell Biology and Molecular Genetics, University of Maryland, Maryland, USA
| | - Brian G Pierce
- University of Maryland Institute for Bioscience and Biotechnology Research, Rockville, Maryland, USA
- Department of Cell Biology and Molecular Genetics, University of Maryland, Maryland, USA
| | | | - Zhen Cao
- King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
| | - Luigi Cavallo
- King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
| | - Romina Oliva
- University of Naples "Parthenope", Napoli, Italy
| | - Yuanfei Sun
- Department of Electrical and Computer Engineering, Texas A&M University, Texas, USA
| | - Shaowen Zhu
- Department of Electrical and Computer Engineering, Texas A&M University, Texas, USA
| | - Yang Shen
- Department of Electrical and Computer Engineering, Texas A&M University, Texas, USA
| | - Taeyong Park
- Department of Chemistry, Seoul National University, Seoul, Republic of Korea
| | - Hyeonuk Woo
- Department of Chemistry, Seoul National University, Seoul, Republic of Korea
| | - Jinsol Yang
- Department of Chemistry, Seoul National University, Seoul, Republic of Korea
| | - Sohee Kwon
- Department of Chemistry, Seoul National University, Seoul, Republic of Korea
| | - Jonghun Won
- Department of Chemistry, Seoul National University, Seoul, Republic of Korea
| | - Chaok Seok
- Department of Chemistry, Seoul National University, Seoul, Republic of Korea
| | - Yasuomi Kiyota
- School of Pharmacy, Kitasato University, Minato-ku, Tokyo, Japan
| | | | - Yoshiki Harada
- School of Pharmacy, Kitasato University, Minato-ku, Tokyo, Japan
| | | | - Petras J Kundrotas
- Computational Biology Program and Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas, USA
| | - Amar Singh
- Computational Biology Program and Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas, USA
| | - Ilya A Vakser
- Computational Biology Program and Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas, USA
| | - Justas Dapkūnas
- Institute of Biotechnology, Life Sciences Center, Vilnius University, Vilnius, Lithuania
| | - Kliment Olechnovič
- Institute of Biotechnology, Life Sciences Center, Vilnius University, Vilnius, Lithuania
| | - Česlovas Venclovas
- Institute of Biotechnology, Life Sciences Center, Vilnius University, Vilnius, Lithuania
| | - Rui Duan
- Dalton Cardiovascular Research Center, University of Missouri, Columbia, Missouri, USA
| | - Liming Qiu
- Dalton Cardiovascular Research Center, University of Missouri, Columbia, Missouri, USA
| | - Xianjin Xu
- Dalton Cardiovascular Research Center, University of Missouri, Columbia, Missouri, USA
| | - Shuang Zhang
- Dalton Cardiovascular Research Center, University of Missouri, Columbia, Missouri, USA
| | - Xiaoqin Zou
- Institute for Data Science and Informatics, University of Missouri, Columbia, Missouri, USA
- Dalton Cardiovascular Research Center, University of Missouri, Columbia, Missouri, USA
- Department of Physics and Astronomy, University of Missouri, Columbia, Missouri, USA
- Department of Biochemistry, University of Missouri, Columbia, Missouri, USA
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20
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Liwo A, Czaplewski C, Sieradzan AK, Lipska AG, Samsonov SA, Murarka RK. Theory and Practice of Coarse-Grained Molecular Dynamics of Biologically Important Systems. Biomolecules 2021; 11:1347. [PMID: 34572559 PMCID: PMC8465211 DOI: 10.3390/biom11091347] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Revised: 09/03/2021] [Accepted: 09/09/2021] [Indexed: 12/16/2022] Open
Abstract
Molecular dynamics with coarse-grained models is nowadays extensively used to simulate biomolecular systems at large time and size scales, compared to those accessible to all-atom molecular dynamics. In this review article, we describe the physical basis of coarse-grained molecular dynamics, the coarse-grained force fields, the equations of motion and the respective numerical integration algorithms, and selected practical applications of coarse-grained molecular dynamics. We demonstrate that the motion of coarse-grained sites is governed by the potential of mean force and the friction and stochastic forces, resulting from integrating out the secondary degrees of freedom. Consequently, Langevin dynamics is a natural means of describing the motion of a system at the coarse-grained level and the potential of mean force is the physical basis of the coarse-grained force fields. Moreover, the choice of coarse-grained variables and the fact that coarse-grained sites often do not have spherical symmetry implies a non-diagonal inertia tensor. We describe selected coarse-grained models used in molecular dynamics simulations, including the most popular MARTINI model developed by Marrink's group and the UNICORN model of biological macromolecules developed in our laboratory. We conclude by discussing examples of the application of coarse-grained molecular dynamics to study biologically important processes.
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Affiliation(s)
- Adam Liwo
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland; (C.C.); (A.K.S.); (A.G.L.); (S.A.S.)
| | - Cezary Czaplewski
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland; (C.C.); (A.K.S.); (A.G.L.); (S.A.S.)
| | - Adam K. Sieradzan
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland; (C.C.); (A.K.S.); (A.G.L.); (S.A.S.)
| | - Agnieszka G. Lipska
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland; (C.C.); (A.K.S.); (A.G.L.); (S.A.S.)
| | - Sergey A. Samsonov
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland; (C.C.); (A.K.S.); (A.G.L.); (S.A.S.)
| | - Rajesh K. Murarka
- Department of Chemistry, Indian Institute of Science Education and Research Bhopal, Bhopal Bypass Road, Bhopal 462066, MP, India;
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21
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Gondelaud F, Bouakil M, Le Fèvre A, Miele AE, Chirot F, Duclos B, Liwo A, Ricard-Blum S. Extended disorder at the cell surface: The conformational landscape of the ectodomains of syndecans. Matrix Biol Plus 2021; 12:100081. [PMID: 34505054 PMCID: PMC8416954 DOI: 10.1016/j.mbplus.2021.100081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2021] [Revised: 07/11/2021] [Accepted: 07/12/2021] [Indexed: 10/26/2022] Open
Abstract
Syndecans are membrane proteoglycans regulating extracellular matrix assembly, cell adhesion and signaling. Their ectodomains can be shed from the cell surface, and act as paracrine and autocrine effectors or as competitors of full-length syndecans. We report the first biophysical characterization of the recombinant ectodomains of the four human syndecans using biophysical techniques, and show that they behave like flexible random-coil intrinsically disordered proteins, and adopt several conformation ensembles in solution. We have characterized their conformational landscapes using native mass spectrometry (MS) and ion-mobility MS, and demonstrated that the syndecan ectodomains explore the majority of their conformational landscape, from minor compact, globular-like, conformations to extended ones. We also report that the ectodomain of syndecan-4, corresponding to a natural isoform, is able to dimerize via a disulfide bond. We have generated a three-dimensional model of the C-terminus of this dimer, which supports the dimerization via a disulfide bond. Furthermore, we have mapped the NXIP adhesion motif of syndecans and their sequences involved in the formation of ternary complexes with integrins and growth factor receptors on the major conformations of their ectodomains, and shown that these sequences are not accessible in all the conformations, suggesting that only some of them are biologically active. Lastly, although the syndecan ectodomains have a far lower number of amino acid residues than their membrane partners, their intrinsic disorder and flexibility allow them to adopt extended conformations, which have roughly the same size as the cell surface receptors (e.g., integrins and growth factor receptors) they bind to.
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Key Words
- CCS, collision cross section
- CD, circular dichroism
- CSD, charge state distribution
- Cell-matrix interactions
- Conformations
- DLS, dynamic light scattering
- DTT, dithiothreitol
- ED, ectodomain
- ESI-IM-MS, electrospray ionization - ion mobility - mass spectrometry
- ESI-MS, electrospray ionization - mass spectrometry
- GAG, glycosaminoglycan
- IDP, intrinsically disordered protein
- Intrinsically disordered proteins
- MoRF, molecular recognition feature
- PAGE, polyacrylamide gel electrophoresis
- PMG, pre-molten globule
- RC, random-coil
- SASA, solvent accessible surface area
- SAXS, small angle X-ray scattering
- SDC, syndecan
- SDS, sodium dodecyl sulfate
- SEC, size exclusion chromatography
- Syndecans
- TFE, trifluoroethanol
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Affiliation(s)
- Frank Gondelaud
- Univ Lyon, University Claude Bernard Lyon 1, CNRS, INSA Lyon, CPE, Institute of Molecular and Supramolecular Chemistry and Biochemistry (ICBMS), UMR 5246, F-69622 Villeurbanne cedex, France
| | - Mathilde Bouakil
- Univ Lyon, University Claude Bernard Lyon 1, CNRS, Institut Lumière Matière, UMR 5306, Cité Lyonnaise de l'Environnement et de l'Analyse, 5 rue de la Doua, 69100 Villeurbanne, France
| | - Aurélien Le Fèvre
- Univ Lyon, University Claude Bernard Lyon 1, CNRS, Institut des Sciences Analytiques, UMR 5280, 5 Rue de la Doua, 69100 Villeurbanne, France
| | - Adriana Erica Miele
- Univ Lyon, University Claude Bernard Lyon 1, CNRS, INSA Lyon, CPE, Institute of Molecular and Supramolecular Chemistry and Biochemistry (ICBMS), UMR 5246, F-69622 Villeurbanne cedex, France
| | - Fabien Chirot
- Univ Lyon, University Claude Bernard Lyon 1, CNRS, Institut des Sciences Analytiques, UMR 5280, 5 Rue de la Doua, 69100 Villeurbanne, France
| | - Bertrand Duclos
- Univ Lyon, University Claude Bernard Lyon 1, CNRS, INSA Lyon, CPE, Institute of Molecular and Supramolecular Chemistry and Biochemistry (ICBMS), UMR 5246, F-69622 Villeurbanne cedex, France
| | - Adam Liwo
- Laboratory of Molecular Modeling, Faculty of Chemistry, University of Gdansk, Wita Stwosza 63, 80-308 Gdansk, Poland
| | - Sylvie Ricard-Blum
- Univ Lyon, University Claude Bernard Lyon 1, CNRS, INSA Lyon, CPE, Institute of Molecular and Supramolecular Chemistry and Biochemistry (ICBMS), UMR 5246, F-69622 Villeurbanne cedex, France
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Antoniak A, Biskupek I, Bojarski KK, Czaplewski C, Giełdoń A, Kogut M, Kogut MM, Krupa P, Lipska AG, Liwo A, Lubecka EA, Marcisz M, Maszota-Zieleniak M, Samsonov SA, Sieradzan AK, Ślusarz MJ, Ślusarz R, Wesołowski PA, Ziȩba K. Modeling protein structures with the coarse-grained UNRES force field in the CASP14 experiment. J Mol Graph Model 2021; 108:108008. [PMID: 34419932 DOI: 10.1016/j.jmgm.2021.108008] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2021] [Revised: 08/12/2021] [Accepted: 08/13/2021] [Indexed: 12/31/2022]
Abstract
The UNited RESidue (UNRES) force field was tested in the 14th Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP14), in which larger oligomeric and multimeric targets were present compared to previous editions. Three prediction modes were tested (i) ab initio (the UNRES group), (ii) contact-assisted (the UNRES-contact group), and (iii) template-assisted (the UNRES-template group). For most of the targets, the contact restraints were derived from the server models top-ranked by the DeepQA method, while the DNCON2 method was used for 11 targets. Our consensus-fragment procedure was used to run template-assisted predictions. Each group also processed the Nuclear Magnetic Resonance (NMR)- and Small Angle X-Ray Scattering (SAXS)-data assisted targets. The average Global Distance Test Total Score (GDT_TS) of the 'Model 1' predictions were 29.17, 39.32, and 56.37 for the UNRES, UNRES-contact, and UNRES-template predictions, respectively, increasing by 0.53, 2.24, and 3.76, respectively, compared to CASP13. It was also found that the GDT_TS of the UNRES models obtained in ab initio mode and in the contact-assisted mode decreases with the square root of chain length, while the exponent in this relationship is 0.20 for the UNRES-template group models and 0.11 for the best performing AlphaFold2 models, which suggests that incorporation of database information, which stems from protein evolution, brings in long-range correlations, thus enabling the correction of force-field inaccuracies.
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Affiliation(s)
- Anna Antoniak
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308, Gdańsk, Poland
| | - Iga Biskupek
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308, Gdańsk, Poland
| | - Krzysztof K Bojarski
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308, Gdańsk, Poland
| | - Cezary Czaplewski
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308, Gdańsk, Poland
| | - Artur Giełdoń
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308, Gdańsk, Poland
| | - Mateusz Kogut
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308, Gdańsk, Poland
| | - Małgorzata M Kogut
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308, Gdańsk, Poland
| | - Paweł Krupa
- Institute of Physics, Polish Academy of Sciences, Aleja Lotników 32/46, Warsaw, PL-02668, Poland
| | - Agnieszka G Lipska
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308, Gdańsk, Poland
| | - Adam Liwo
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308, Gdańsk, Poland; School of Computational Sciences, Korea Institute for Advanced Study, 87 Hoegiro, Dongdaemun-gu, 130-722, Seoul, Republic of Korea.
| | - Emilia A Lubecka
- Faculty of Electronics, Telecommunications and Informatics, Gdańsk University of Technology, G. Narutowicza 11/12, 80-233, Gdańsk, Poland
| | - Mateusz Marcisz
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308, Gdańsk, Poland; Intercollegiate Faculty of Biotechnology, University of Gdańsk and Medical University of Gdańsk, ul. Abrahama 58, 80-307, Gdańsk, Poland
| | | | - Sergey A Samsonov
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308, Gdańsk, Poland
| | - Adam K Sieradzan
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308, Gdańsk, Poland
| | - Magdalena J Ślusarz
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308, Gdańsk, Poland
| | - Rafał Ślusarz
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308, Gdańsk, Poland
| | - Patryk A Wesołowski
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308, Gdańsk, Poland; Intercollegiate Faculty of Biotechnology, University of Gdańsk and Medical University of Gdańsk, ul. Abrahama 58, 80-307, Gdańsk, Poland
| | - Karolina Ziȩba
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308, Gdańsk, Poland
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23
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Kogut M, Gong Z, Tang C, Liwo A. Pseudopotentials for coarse-grained cross-link-assisted modeling of protein structures. J Comput Chem 2021; 42:2054-2067. [PMID: 34402552 DOI: 10.1002/jcc.26736] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Revised: 07/09/2021] [Accepted: 08/03/2021] [Indexed: 11/08/2022]
Abstract
Pseudopotentials for the chemical cross-links comprising the glutamic- and aspartic-acid side chains bridged with adipic- (ADH) or pimelic-acid hydrazide (PDH), and the lysine side chains bridged with glutaric (BS2 G) or suberic acid (BS3 ) for coarse-grained cross-link-assisted simulations were determined by canonical molecular dynamics with the Amber14sb force field. The potentials depend on the distance between side-chain ends and on side-chain orientation, this preventing from making cross-link contacts across the globule in simulations. The potentials were implemented in the UNRES coarse-grained force field and their effect on the quality of models was assessed with 11 monomeric and 1 dimeric proteins, using synthetic or experimental cross-link data. Simulations with the new potentials resulted in improvement of the generated models compared to unrestrained simulations in more instances compared to those with the statistical potentials.
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Affiliation(s)
- Mateusz Kogut
- Faculty of Chemistry, University of Gdańsk, Gdańsk, Poland
| | - Zhou Gong
- Innovation Academy of Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, China
| | - Chun Tang
- College of Chemistry and Molecular Engineering, PKU-Tsinghua Center for Life Sciences, Beijing National Laboratory for Molecular Sciences, Peking University, Beijing, China
| | - Adam Liwo
- Faculty of Chemistry, University of Gdańsk, Gdańsk, Poland
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24
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Lubecka EA, Liwo A. ESCASA: Analytical estimation of atomic coordinates from coarse-grained geometry for nuclear-magnetic-resonance-assisted protein structure modeling. I. Backbone and H β protons. J Comput Chem 2021; 42:1579-1589. [PMID: 34048074 DOI: 10.1002/jcc.26695] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Revised: 05/06/2021] [Accepted: 05/11/2021] [Indexed: 12/13/2022]
Abstract
A method for the estimation of coordinates of atoms in proteins from coarse-grained geometry by simple analytical formulas (ESCASA), for use in nuclear-magnetic-resonance (NMR) data-assisted coarse-grained simulations of proteins is proposed. In this paper, the formulas for the backbone Hα and amide (HN ) protons, and the side-chain Hβ protons, given the Cα -trace, have been derived and parameterized, by using the interproton distances calculated from a set of 140 high-resolution non-homologous protein structures. The mean standard deviation over all types of proton pairs in the set was 0.44 Å after fitting. Validation against a set of 41 proteins with NMR-determined structures, which were not considered in parameterization, resulted in average standard deviation from average proton-proton distances of the NMR-determined structures of 0.25 Å, compared to 0.21 Å obtained with the PULCHRA all-atom-chain reconstruction algorithm and to the 0.12 Å standard deviation of the average-structure proton-proton distance of NMR-determined ensembles. The formulas provide analytical forces and can, therefore, be used in coarse-grained molecular dynamics.
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Affiliation(s)
- Emilia A Lubecka
- Faculty of Electronics, Telecommunications and Informatics, Gdańsk University of Technology, Gdańsk, Poland
| | - Adam Liwo
- Faculty of Chemistry, University of Gdańsk, Gdańsk, Poland
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25
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Krupa P, Karczyńska AS, Mozolewska MA, Liwo A, Czaplewski C. UNRES-Dock-protein-protein and peptide-protein docking by coarse-grained replica-exchange MD simulations. Bioinformatics 2021; 37:1613-1615. [PMID: 33079977 DOI: 10.1093/bioinformatics/btaa897] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2020] [Revised: 09/04/2020] [Accepted: 10/06/2020] [Indexed: 11/13/2022] Open
Abstract
MOTIVATION The majority of the proteins in living organisms occur as homo- or hetero-multimeric structures. Although there are many tools to predict the structures of single-chain proteins or protein complexes with small ligands, peptide-protein and protein-protein docking is more challenging. In this work, we utilized multiplexed replica-exchange molecular dynamics (MREMD) simulations with the physics-based heavily coarse-grained UNRES model, which provides more than a 1000-fold simulation speed-up compared with all-atom approaches to predict structures of protein complexes. RESULTS We present a new protein-protein and peptide-protein docking functionality of the UNRES package, which includes a variable degree of conformational flexibility. UNRES-Dock protocol was tested on a set of 55 complexes with size from 43 to 587 amino-acid residues, showing that structures of the complexes can be predicted with good quality, if the sampling of the conformational space is sufficient, especially for flexible peptide-protein systems. The developed automatized protocol has been implemented in the standalone UNRES package and in the UNRES server. AVAILABILITY AND IMPLEMENTATION UNRES server: http://unres-server.chem.ug.edu.pl; UNRES package and data used in testing of UNRES-Dock: http://unres.pl. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Paweł Krupa
- Faculty of Chemistry, University of Gdańsk, Gdańsk 80-308, Poland.,Institute of Physics, Polish Academy of Sciences, Warsaw 02-668, Poland
| | - Agnieszka S Karczyńska
- Faculty of Chemistry, University of Gdańsk, Gdańsk 80-308, Poland.,University of Grenoble Alpes, Inria, CNRS, Grenoble INP, LJK, Grenoble 38000, France
| | | | - Adam Liwo
- Faculty of Chemistry, University of Gdańsk, Gdańsk 80-308, Poland
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26
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Zieba K, Czaplewski C, Liwo A, Graziano G. Hydrophobic hydration and pairwise hydrophobic interaction of Lennard-Jones and Mie particles in different water models. Phys Chem Chem Phys 2020; 22:4758-4771. [PMID: 32064469 DOI: 10.1039/c9cp06627f] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
The study provides a deep computational analysis of the thermodynamic and structural features associated with the hydration of xenon, Xe, and its pairwise hydrophobic interaction (i.e., the potential of mean force, PMF), over a large temperature range. Xe is described both as a Lennard-Jones particle, LJ-Xe, and as a Mie particle, Mie-Xe (pseudo hard sphere). Three different water models are used: TIP3P-Ew, SPCE and TIP4P-2005. Mie-Xe is more hydrophobic than LJ-Xe due to the lack of the attractive energetic interactions with water molecules; its hydration, around room temperature, is opposed by a large and negative entropy change and a positive enthalpy change. The PMF of Mie-Xe is characterized by a deep minimum at contact distance whose depth increases with temperature, and whose magnitude is significantly larger than that obtained for LJ-Xe. The contact minimum configuration of Mie-Xe is favoured by a large positive entropy change and contrasted by a positive enthalpy change. These results are qualitatively the same regardless of the water model used. There is no clear connection between the values determined for the thermodynamic functions and the structural features of the hydration shells surrounding the single Mie-Xe and the couple of Mie-Xe particles in the contact minimum configuration. This confirms that the structural reorganization of water associated with such processes is characterized by an almost complete enthalpy-entropy compensation.
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Affiliation(s)
- Karolina Zieba
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland.
| | - Cezary Czaplewski
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland.
| | - Adam Liwo
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland.
| | - Giuseppe Graziano
- Department of Science and Technology, University of Sannio, Via Francesco de Sanctis snc, 82100 Benevento, Italy.
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27
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Liwo A, Czaplewski C, Sieradzan AK, Lubecka EA, Lipska AG, Golon Ł, Karczyńska A, Krupa P, Mozolewska MA, Makowski M, Ganzynkowicz R, Giełdoń A, Maciejczyk M. Scale-consistent approach to the derivation of coarse-grained force fields for simulating structure, dynamics, and thermodynamics of biopolymers. Prog Mol Biol Transl Sci 2020; 170:73-122. [PMID: 32145953 DOI: 10.1016/bs.pmbts.2019.12.004] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
In this chapter the scale-consistent approach to the derivation of coarse-grained force fields developed in our laboratory is presented, in which the effective energy function originates from the potential of mean force of the system under consideration and embeds atomistically detailed interactions in the resulting energy terms through use of Kubo's cluster-cumulant expansion, appropriate selection of the major degrees of freedom to be averaged out in the derivation of analytical approximations to the energy terms, and appropriate expression of the interaction energies at the all-atom level in these degrees of freedom. Our approach enables the developers to find correct functional forms of the effective coarse-grained energy terms, without having to import them from all-atom force fields or deriving them on a heuristic basis. In particular, the energy terms derived in such a way exhibit correct dependence on coarse-grained geometry, in particular on site orientation. Moreover, analytical formulas for the multibody (correlation) terms, which appear to be crucial for coarse-grained modeling of many of the regular structures such as, e.g., protein α-helices and β-sheets, can be derived in a systematic way. Implementation of the developed theory to the UNIfied COarse-gRaiNed (UNICORN) model of biological macromolecules, which consists of the UNRES (for proteins), NARES-2P (for nucleic acids), and SUGRES-1P (for polysaccharides) components, and is being developed in our laboratory is described. Successful applications of UNICORN to the prediction of protein structure, simulating the folding and stability of proteins and nucleic acids, and solving biological problems are discussed.
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Affiliation(s)
- Adam Liwo
- Faculty of Chemistry, University of Gdańsk, Gdańsk, Poland; School of Computational Sciences, Korea Institute for Advanced Study, Seoul, Republic of Korea.
| | | | - Adam K Sieradzan
- Faculty of Chemistry, University of Gdańsk, Gdańsk, Poland; School of Computational Sciences, Korea Institute for Advanced Study, Seoul, Republic of Korea
| | - Emilia A Lubecka
- Institute of Informatics, Faculty of Mathematics, Physics, and Informatics, University of Gdańsk, Gdańsk, Poland
| | | | - Łukasz Golon
- Faculty of Chemistry, University of Gdańsk, Gdańsk, Poland
| | | | - Paweł Krupa
- Institute of Physics, Polish Academy of Sciences, Warsaw, Poland
| | | | | | | | - Artur Giełdoń
- Faculty of Chemistry, University of Gdańsk, Gdańsk, Poland
| | - Maciej Maciejczyk
- Department of Physics and Biophysics, Faculty of Food Science, University of Warmia and Mazury in Olsztyn, Olsztyn, Poland
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Karczyńska AS, Ziȩba K, Uciechowska U, Mozolewska MA, Krupa P, Lubecka EA, Lipska AG, Sikorska C, Samsonov SA, Sieradzan AK, Giełdoń A, Liwo A, Ślusarz R, Ślusarz M, Lee J, Joo K, Czaplewski C. Improved Consensus-Fragment Selection in Template-Assisted Prediction of Protein Structures with the UNRES Force Field in CASP13. J Chem Inf Model 2020; 60:1844-1864. [PMID: 31999919 PMCID: PMC7588044 DOI: 10.1021/acs.jcim.9b00864] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
![]()
The method for protein-structure
prediction, which combines the
physics-based coarse-grained UNRES force field with knowledge-based
modeling, has been developed further and tested in the 13th Community
Wide Experiment on the Critical Assessment of Techniques for Protein
Structure Prediction (CASP13). The method implements restraints from
the consensus fragments common to server models. In this work, the
server models to derive fragments have been chosen on the basis of
quality assessment; a fully automatic fragment-selection procedure
has been introduced, and Dynamic Fragment Assembly pseudopotentials
have been fully implemented. The Global Distance Test Score (GDT_TS),
averaged over our “Model 1” predictions, increased by
over 10 units with respect to CASP12 for the free-modeling category
to reach 40.82. Our “Model 1” predictions ranked 20
and 14 for all and free-modeling targets, respectively (upper 20.2%
and 14.3% of all models submitted to CASP13 in these categories, respectively),
compared to 27 (upper 21.1%) and 24 (upper 18.9%) in CASP12, respectively.
For oligomeric targets, the Interface Patch Similarity (IPS) and Interface
Contact Similarity (ICS) averaged over our best oligomer models increased
from 0.28 to 0.36 and from 12.4 to 17.8, respectively, from CASP12
to CASP13, and top-ranking models of 2 targets (H0968 and T0997o)
were obtained (none in CASP12). The improvement of our method in CASP13
over CASP12 was ascribed to the combined effect of the overall enhancement
of server-model quality, our success in selecting server models and
fragments to derive restraints, and improvements of the restraint
and potential-energy functions.
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Affiliation(s)
| | - Karolina Ziȩba
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, Gdańsk 80-308, Poland
| | - Urszula Uciechowska
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, Gdańsk 80-308, Poland
| | - Magdalena A Mozolewska
- Institute of Computer Science, Polish Academy of Sciences, ul. Jana Kazimierza 5, Warsaw PL-02668, Poland
| | - Paweł Krupa
- Institute of Physics, Polish Academy of Sciences, Aleja Lotników 32/46, Warsaw PL-02668, Poland
| | - Emilia A Lubecka
- Institute of Informatics, Faculty of Mathematics, Physics, and Informatics, University of Gdańsk, Wita Stwosza 57, Gdańsk 80-308, Poland
| | - Agnieszka G Lipska
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, Gdańsk 80-308, Poland
| | - Celina Sikorska
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, Gdańsk 80-308, Poland
| | - Sergey A Samsonov
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, Gdańsk 80-308, Poland
| | - Adam K Sieradzan
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, Gdańsk 80-308, Poland.,School of Computational Sciences, Korea Institute for Advanced Study, 85 Hoegiro, Dongdaemun-gu, Seoul 130-722, Republic of Korea
| | - Artur Giełdoń
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, Gdańsk 80-308, Poland
| | - Adam Liwo
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, Gdańsk 80-308, Poland.,School of Computational Sciences, Korea Institute for Advanced Study, 85 Hoegiro, Dongdaemun-gu, Seoul 130-722, Republic of Korea
| | - Rafał Ślusarz
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, Gdańsk 80-308, Poland
| | - Magdalena Ślusarz
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, Gdańsk 80-308, Poland
| | - Jooyoung Lee
- School of Computational Sciences, Korea Institute for Advanced Study, 85 Hoegiro, Dongdaemun-gu, Seoul 130-722, Republic of Korea
| | - Keehyoung Joo
- Center for Advanced Computation, Korea Institute for Advanced Study, 85 Hoegiro, Dongdaemun-gu, Seoul 130-722, Republic of Korea
| | - Cezary Czaplewski
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, Gdańsk 80-308, Poland
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29
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Liwo A, Czaplewski C. Extension of the force-matching method to coarse-grained models with axially symmetric sites to produce transferable force fields: Application to the UNRES model of proteins. J Chem Phys 2020; 152:054902. [DOI: 10.1063/1.5138991] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Affiliation(s)
- Adam Liwo
- Faculty of Chemistry, University of Gdańsk, ul. Wita-Stwosza 63, 80-308 Gdańsk, Poland
- School of Computational Sciences, Korea Institute for Advanced Study, 87 Hoegiro, Dongdaemun-gu, 130-722 Seoul, South Korea
| | - Cezary Czaplewski
- Faculty of Chemistry, University of Gdańsk, ul. Wita-Stwosza 63, 80-308 Gdańsk, Poland
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30
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Fajardo JE, Shrestha R, Gil N, Belsom A, Crivelli SN, Czaplewski C, Fidelis K, Grudinin S, Karasikov M, Karczyńska AS, Kryshtafovych A, Leitner A, Liwo A, Lubecka EA, Monastyrskyy B, Pagès G, Rappsilber J, Sieradzan AK, Sikorska C, Trabjerg E, Fiser A. Assessment of chemical‐crosslink‐assisted protein structure modeling in CASP13. Proteins 2020; 88:540. [DOI: 10.1002/prot.25867] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- J. Eduardo Fajardo
- Department of Systems and Computational BiologyAlbert Einstein College of Medicine New York
- Department of BiochemistryAlbert Einstein College of Medicine New York
| | - Rojan Shrestha
- Department of Systems and Computational BiologyAlbert Einstein College of Medicine New York
- Department of BiochemistryAlbert Einstein College of Medicine New York
| | - Nelson Gil
- Department of Systems and Computational BiologyAlbert Einstein College of Medicine New York
- Department of BiochemistryAlbert Einstein College of Medicine New York
| | - Adam Belsom
- Bioanalytics, Institute of BiotechnologyTechnische Universität Berlin Berlin Germany
| | | | | | | | | | - Mikhail Karasikov
- Center for Energy SystemsSkolkovo Institute of Science and Technology Moscow Russia
- Moscow Institute of Physics and Technology Moscow Russia
- Department of Computer ScienceETH Zurich Zurich Switzerland
| | | | | | - Alexander Leitner
- Department of BiologyInstitute of Molecular Systems Biology Zurich Switzerland
| | - Adam Liwo
- Faculty of ChemistryUniversity of Gdansk Poland
- School of Computational SciencesKorea Institute for Advanced Study Seoul Republic of Korea
| | - Emilia A. Lubecka
- Institute of Informatics, Faculty of Mathematics, Physics, and InformaticsUniversity of Gdańsk Gdańsk Poland
| | | | | | - Juri Rappsilber
- Bioanalytics, Institute of BiotechnologyTechnische Universität Berlin Berlin Germany
- Wellcome Centre for Cell BiologyUniversity of Edinburgh Edinburgh UK
| | | | | | - Esben Trabjerg
- Department of BiologyInstitute of Molecular Systems Biology Zurich Switzerland
| | - Andras Fiser
- Department of Systems and Computational BiologyAlbert Einstein College of Medicine New York
- Department of BiochemistryAlbert Einstein College of Medicine New York
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31
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Lensink MF, Brysbaert G, Nadzirin N, Velankar S, Chaleil RAG, Gerguri T, Bates PA, Laine E, Carbone A, Grudinin S, Kong R, Liu RR, Xu XM, Shi H, Chang S, Eisenstein M, Karczynska A, Czaplewski C, Lubecka E, Lipska A, Krupa P, Mozolewska M, Golon Ł, Samsonov S, Liwo A, Crivelli S, Pagès G, Karasikov M, Kadukova M, Yan Y, Huang SY, Rosell M, Rodríguez-Lumbreras LA, Romero-Durana M, Díaz-Bueno L, Fernandez-Recio J, Christoffer C, Terashi G, Shin WH, Aderinwale T, Subraman SRMV, Kihara D, Kozakov D, Vajda S, Porter K, Padhorny D, Desta I, Beglov D, Ignatov M, Kotelnikov S, Moal IH, Ritchie DW, de Beauchêne IC, Maigret B, Devignes MD, Echartea MER, Barradas-Bautista D, Cao Z, Cavallo L, Oliva R, Cao Y, Shen Y, Baek M, Park T, Woo H, Seok C, Braitbard M, Bitton L, Scheidman-Duhovny D, Dapkūnas J, Olechnovič K, Venclovas Č, Kundrotas PJ, Belkin S, Chakravarty D, Badal VD, Vakser IA, Vreven T, Vangaveti S, Borrman T, Weng Z, Guest JD, Gowthaman R, Pierce BG, Xu X, Duan R, Qiu L, Hou J, Merideth BR, Ma Z, Cheng J, Zou X, Koukos PI, Roel-Touris J, Ambrosetti F, Geng C, Schaarschmidt J, Trellet ME, Melquiond ASJ, Xue L, Jiménez-García B, van Noort CW, Honorato RV, Bonvin AMJJ, Wodak SJ. Blind prediction of homo- and hetero-protein complexes: The CASP13-CAPRI experiment. Proteins 2019; 87:1200-1221. [PMID: 31612567 PMCID: PMC7274794 DOI: 10.1002/prot.25838] [Citation(s) in RCA: 79] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2019] [Revised: 09/26/2019] [Accepted: 09/27/2019] [Indexed: 12/28/2022]
Abstract
We present the results for CAPRI Round 46, the third joint CASP-CAPRI protein assembly prediction challenge. The Round comprised a total of 20 targets including 14 homo-oligomers and 6 heterocomplexes. Eight of the homo-oligomer targets and one heterodimer comprised proteins that could be readily modeled using templates from the Protein Data Bank, often available for the full assembly. The remaining 11 targets comprised 5 homodimers, 3 heterodimers, and two higher-order assemblies. These were more difficult to model, as their prediction mainly involved "ab-initio" docking of subunit models derived from distantly related templates. A total of ~30 CAPRI groups, including 9 automatic servers, submitted on average ~2000 models per target. About 17 groups participated in the CAPRI scoring rounds, offered for most targets, submitting ~170 models per target. The prediction performance, measured by the fraction of models of acceptable quality or higher submitted across all predictors groups, was very good to excellent for the nine easy targets. Poorer performance was achieved by predictors for the 11 difficult targets, with medium and high quality models submitted for only 3 of these targets. A similar performance "gap" was displayed by scorer groups, highlighting yet again the unmet challenge of modeling the conformational changes of the protein components that occur upon binding or that must be accounted for in template-based modeling. Our analysis also indicates that residues in binding interfaces were less well predicted in this set of targets than in previous Rounds, providing useful insights for directions of future improvements.
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Affiliation(s)
- Marc F. Lensink
- University of Lille, CNRS UMR8576 UGSF, Unité de Glycobiologie Structurale et Fonctionnelle, Lille, France
| | - Guillaume Brysbaert
- University of Lille, CNRS UMR8576 UGSF, Unité de Glycobiologie Structurale et Fonctionnelle, Lille, France
| | - Nurul Nadzirin
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, UK
| | - Sameer Velankar
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, UK
| | | | - Tereza Gerguri
- Biomolecular Modelling Laboratory, The Francis Crick Institute, London, UK
| | - Paul A. Bates
- Biomolecular Modelling Laboratory, The Francis Crick Institute, London, UK
| | - Elodie Laine
- CNRS, IBPS, Laboratoire de Biologie Computationnelle et Quantitative (LCQB), Sorbonne Université, Paris, France
| | - Alessandra Carbone
- CNRS, IBPS, Laboratoire de Biologie Computationnelle et Quantitative (LCQB), Sorbonne Université, Paris, France
- Institut Universitaire de France (IUF), Paris, France
| | - Sergei Grudinin
- Université Grenoble Alpes, CNRS, Inria, Grenoble INP, LJK, Grenoble, France
| | - Ren Kong
- Institute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou, China
| | - Ran-Ran Liu
- Institute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou, China
| | - Xi-Ming Xu
- Institute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou, China
| | - Hang Shi
- Institute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou, China
| | - Shan Chang
- Institute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou, China
| | - Miriam Eisenstein
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel
| | | | | | - Emilia Lubecka
- Institute of Informatics, Faculty of Mathematics, Physics, and Informatics, University of Gdańsk, Gdańsk, Poland
| | | | - Paweł Krupa
- Polish Academy of Sciences, Institute of Physics, Warsaw, Poland
| | | | - Łukasz Golon
- Faculty of Chemistry, University of Gdańsk, Gdańsk, Poland
| | | | - Adam Liwo
- Faculty of Chemistry, University of Gdańsk, Gdańsk, Poland
- School of Computational Sciences, Korea Institute for Advanced Study, Seoul, South Korea
| | | | - Guillaume Pagès
- Université Grenoble Alpes, CNRS, Inria, Grenoble INP, LJK, Grenoble, France
| | | | - Maria Kadukova
- Université Grenoble Alpes, CNRS, Inria, Grenoble INP, LJK, Grenoble, France
- Moscow Institute of Physics and Technology, Dolgoprudniy, Russia
| | - Yumeng Yan
- School of Physics, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Sheng-You Huang
- School of Physics, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Mireia Rosell
- Barcelona Supercomputing Center (BSC), Barcelona, Spain
- Instituto de Ciencias de la Vid y del Vino (ICVV-CSIC), Logroño, Spain
| | - Luis A. Rodríguez-Lumbreras
- Barcelona Supercomputing Center (BSC), Barcelona, Spain
- Instituto de Ciencias de la Vid y del Vino (ICVV-CSIC), Logroño, Spain
| | | | | | - Juan Fernandez-Recio
- Barcelona Supercomputing Center (BSC), Barcelona, Spain
- Instituto de Ciencias de la Vid y del Vino (ICVV-CSIC), Logroño, Spain
- Instituto de Biología Molecular de Barcelona (IBMB-CSIC), Barcelona, Spain
| | | | - Genki Terashi
- Department of Biological Sciences, Purdue University, West Lafayette, Indiana
| | - Woong-Hee Shin
- Department of Biological Sciences, Purdue University, West Lafayette, Indiana
| | - Tunde Aderinwale
- Department of Computer Science, Purdue University, West Lafayette, Indiana
| | | | - Daisuke Kihara
- Department of Computer Science, Purdue University, West Lafayette, Indiana
| | - Dima Kozakov
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York
| | - Sandor Vajda
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts
- Department of Chemistry, Boston University, Boston, Massachusetts
| | - Kathryn Porter
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts
| | - Dzmitry Padhorny
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York
| | - Israel Desta
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts
| | - Dmitri Beglov
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts
| | - Mikhail Ignatov
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York
| | - Sergey Kotelnikov
- Moscow Institute of Physics and Technology, Dolgoprudniy, Russia
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, New York
| | - Iain H. Moal
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, UK
| | | | | | | | | | | | - Didier Barradas-Bautista
- Physical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
| | - Zhen Cao
- Physical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
| | - Luigi Cavallo
- Physical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
| | - Romina Oliva
- Department of Sciences and Technologies, University of Naples “Parthenope”, Napoli, Italy
| | - Yue Cao
- Department of Electrical and Computer Engineering, Texas A&M University, College Station, Texas
| | - Yang Shen
- Department of Electrical and Computer Engineering, Texas A&M University, College Station, Texas
| | - Minkyung Baek
- Department of Chemistry, Seoul National University, Seoul, Republic of Korea
| | - Taeyong Park
- Department of Chemistry, Seoul National University, Seoul, Republic of Korea
| | - Hyeonuk Woo
- Department of Chemistry, Seoul National University, Seoul, Republic of Korea
| | - Chaok Seok
- Department of Chemistry, Seoul National University, Seoul, Republic of Korea
| | - Merav Braitbard
- Department of Biological Chemistry, Institute of Live Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Lirane Bitton
- School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Dina Scheidman-Duhovny
- Department of Biological Chemistry, Institute of Live Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
- School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Justas Dapkūnas
- Institute of Biotechnology, Life Sciences Center, Vilnius University, Vilnius, Lithuania
| | - Kliment Olechnovič
- Institute of Biotechnology, Life Sciences Center, Vilnius University, Vilnius, Lithuania
| | - Česlovas Venclovas
- Institute of Biotechnology, Life Sciences Center, Vilnius University, Vilnius, Lithuania
| | - Petras J. Kundrotas
- Computational Biology Program and Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas
| | - Saveliy Belkin
- Computational Biology Program and Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas
| | - Devlina Chakravarty
- Computational Biology Program and Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas
| | - Varsha D. Badal
- Computational Biology Program and Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas
| | - Ilya A. Vakser
- Computational Biology Program and Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas
| | - Thom Vreven
- Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, Massachusetts
| | - Sweta Vangaveti
- Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, Massachusetts
| | - Tyler Borrman
- Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, Massachusetts
| | - Zhiping Weng
- Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, Massachusetts
| | - Johnathan D. Guest
- University of Maryland Institute for Bioscience and Biotechnology Research, Rockville, Maryland
- Department of Cell Biology and Molecular Genetics, University of Maryland, College Park, Maryland
| | - Ragul Gowthaman
- University of Maryland Institute for Bioscience and Biotechnology Research, Rockville, Maryland
- Department of Cell Biology and Molecular Genetics, University of Maryland, College Park, Maryland
| | - Brian G. Pierce
- University of Maryland Institute for Bioscience and Biotechnology Research, Rockville, Maryland
- Department of Cell Biology and Molecular Genetics, University of Maryland, College Park, Maryland
| | - Xianjin Xu
- Dalton Cardiovascular Research Center, University of Missouri, Columbia, Missouri
| | - Rui Duan
- Dalton Cardiovascular Research Center, University of Missouri, Columbia, Missouri
| | - Liming Qiu
- Dalton Cardiovascular Research Center, University of Missouri, Columbia, Missouri
| | - Jie Hou
- Department of Computer Science, University of Missouri, Columbia, Missouri
| | - Benjamin Ryan Merideth
- Dalton Cardiovascular Research Center, University of Missouri, Columbia, Missouri
- Informatics Institute, University of Missouri, Columbia, Missouri
| | - Zhiwei Ma
- Dalton Cardiovascular Research Center, University of Missouri, Columbia, Missouri
- Department of Physics and Astronomy, University of Missouri, Columbia, Missouri
| | - Jianlin Cheng
- Department of Computer Science, University of Missouri, Columbia, Missouri
- Informatics Institute, University of Missouri, Columbia, Missouri
| | - Xiaoqin Zou
- Dalton Cardiovascular Research Center, University of Missouri, Columbia, Missouri
- Informatics Institute, University of Missouri, Columbia, Missouri
- Department of Physics and Astronomy, University of Missouri, Columbia, Missouri
- Department of Biochemistry, University of Missouri, Columbia, Missouri
| | - Panagiotis I. Koukos
- Computational Structural Biology Group, Department of Chemistry, Faculty of Science, Utrecht University, Utrecht, The Netherlands
| | - Jorge Roel-Touris
- Computational Structural Biology Group, Department of Chemistry, Faculty of Science, Utrecht University, Utrecht, The Netherlands
| | - Francesco Ambrosetti
- Computational Structural Biology Group, Department of Chemistry, Faculty of Science, Utrecht University, Utrecht, The Netherlands
| | - Cunliang Geng
- Computational Structural Biology Group, Department of Chemistry, Faculty of Science, Utrecht University, Utrecht, The Netherlands
| | - Jörg Schaarschmidt
- Computational Structural Biology Group, Department of Chemistry, Faculty of Science, Utrecht University, Utrecht, The Netherlands
| | - Mikael E. Trellet
- Computational Structural Biology Group, Department of Chemistry, Faculty of Science, Utrecht University, Utrecht, The Netherlands
| | - Adrien S. J. Melquiond
- Computational Structural Biology Group, Department of Chemistry, Faculty of Science, Utrecht University, Utrecht, The Netherlands
| | - Li Xue
- Computational Structural Biology Group, Department of Chemistry, Faculty of Science, Utrecht University, Utrecht, The Netherlands
| | - Brian Jiménez-García
- Computational Structural Biology Group, Department of Chemistry, Faculty of Science, Utrecht University, Utrecht, The Netherlands
| | - Charlotte W. van Noort
- Computational Structural Biology Group, Department of Chemistry, Faculty of Science, Utrecht University, Utrecht, The Netherlands
| | - Rodrigo V. Honorato
- Computational Structural Biology Group, Department of Chemistry, Faculty of Science, Utrecht University, Utrecht, The Netherlands
| | - Alexandre M. J. J. Bonvin
- Computational Structural Biology Group, Department of Chemistry, Faculty of Science, Utrecht University, Utrecht, The Netherlands
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Fajardo JE, Shrestha R, Gil N, Belsom A, Crivelli SN, Czaplewski C, Fidelis K, Grudinin S, Karasikov M, Karczyńska AS, Kryshtafovych A, Leitner A, Liwo A, Lubecka EA, Monastyrskyy B, Pagès G, Rappsilber J, Sieradzan AK, Sikorska C, Trabjerg E, Fiser A. Assessment of chemical-crosslink-assisted protein structure modeling in CASP13. Proteins 2019; 87:1283-1297. [PMID: 31569265 PMCID: PMC6851497 DOI: 10.1002/prot.25816] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2019] [Revised: 08/08/2019] [Accepted: 09/13/2019] [Indexed: 12/22/2022]
Abstract
With the advance of experimental procedures obtaining chemical crosslinking information is becoming a fast and routine practice. Information on crosslinks can greatly enhance the accuracy of protein structure modeling. Here, we review the current state of the art in modeling protein structures with the assistance of experimentally determined chemical crosslinks within the framework of the 13th meeting of Critical Assessment of Structure Prediction approaches. This largest-to-date blind assessment reveals benefits of using data assistance in difficult to model protein structure prediction cases. However, in a broader context, it also suggests that with the unprecedented advance in accuracy to predict contacts in recent years, experimental crosslinks will be useful only if their specificity and accuracy further improved and they are better integrated into computational workflows.
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Affiliation(s)
- J. Eduardo Fajardo
- Department of Systems and Computational Biology, and Department of Biochemistry, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Bronx, NY 10461, USA
| | - Rojan Shrestha
- Department of Systems and Computational Biology, and Department of Biochemistry, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Bronx, NY 10461, USA
| | - Nelson Gil
- Department of Systems and Computational Biology, and Department of Biochemistry, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Bronx, NY 10461, USA
| | - Adam Belsom
- Bioanalytics, Institute of Biotechnology, Technische Universität Berlin, 13355 Berlin, Germany
| | - Silvia N. Crivelli
- Department of Computer Science, UC Davis, One Shields Ave., Davis, CA 95616
| | - Cezary Czaplewski
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland
| | - Krzysztof Fidelis
- Genome Center, University of California, Davis, 451 Health Sciences Dr., Davis CA 95616-8816, USA
| | - Sergei Grudinin
- Univ. Grenoble Alpes, CNRS, Inria, Grenoble INP LJK, 38000 Grenoble, France
| | - Mikhail Karasikov
- Center for Energy Systems, Skolkovo Institute of Science and Technology, Moscow, 143026, Russia
- Moscow Institute of Physics and Technology, Moscow, 141701, Russia
- Department of Computer Science, ETH Zurich, Zurich, 8092, Switzerland
| | | | - Andriy Kryshtafovych
- Genome Center, University of California, Davis, 451 Health Sciences Dr., Davis CA 95616-8816, USA
| | - Alexander Leitner
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Otto-Stern-Weg 3, 8093 Zurich, Switzerland
| | - Adam Liwo
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland
- School of Computational Sciences, Korea Institute for Advanced Study, 85 Hoegiro, Dongdaemun-gu, Seoul 130-722, Republic of Korea
| | - Emilia A. Lubecka
- Institute of Informatics, Faculty of Mathematics, Physics, and Informatics, University of Gdańsk, Wita Stwosza 57, 80-308 Gdańsk, Poland
| | - Bohdan Monastyrskyy
- Genome Center, University of California, Davis, 451 Health Sciences Dr., Davis CA 95616-8816, USA
| | - Guillaume Pagès
- Univ. Grenoble Alpes, CNRS, Inria, Grenoble INP LJK, 38000 Grenoble, France
| | - Juri Rappsilber
- Bioanalytics, Institute of Biotechnology, Technische Universität Berlin, 13355 Berlin, Germany
- Wellcome Centre for Cell Biology, University of Edinburgh, Edinburgh EH9 3BF, United Kingdom
| | - Adam K. Sieradzan
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland
| | - Celina Sikorska
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland
| | - Esben Trabjerg
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Otto-Stern-Weg 3, 8093 Zurich, Switzerland
| | - Andras Fiser
- Department of Systems and Computational Biology, and Department of Biochemistry, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Bronx, NY 10461, USA
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Ziȩba K, Ślusarz M, Ślusarz R, Liwo A, Czaplewski C, Sieradzan AK. Extension of the UNRES Coarse-Grained Force Field to Membrane Proteins in the Lipid Bilayer. J Phys Chem B 2019; 123:7829-7839. [PMID: 31454484 DOI: 10.1021/acs.jpcb.9b06700] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
The physics-based UNRES coarse-grained force field for the simulations of protein structure and dynamics has been extended to treat membrane proteins. The lipid bilayer has been modeled by introducing a continuous nonpolar phase with the water-interface region of appropriate thickness. The potentials for average electrostatic and correlation interactions of the peptide groups have been rescaled to account for the reduction of the dielectric permittivity compared to the water phase and new potentials for protein side-chain-side-chain interactions inside and across the lipid phase have been introduced. The model was implemented in the UNRES package for coarse-grained simulations of proteins, and the package with the new functionality was tested for total energy conservation and thermostat behavior in microcanonical and canonical molecular dynamics simulations runs, respectively. The method was validated by running unrestricted ab initio blind-prediction tests of 10 short α-helical membrane proteins, all runs started from the extended structures. The modified UNRES force field was able to predict correctly the overall folds of the membrane proteins studied.
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Affiliation(s)
- Karolina Ziȩba
- Faculty of Chemistry , University of Gdańsk , Wita Stwosza 63 , 80-308 Gdańsk , Poland
| | - Magdalena Ślusarz
- Faculty of Chemistry , University of Gdańsk , Wita Stwosza 63 , 80-308 Gdańsk , Poland
| | - Rafał Ślusarz
- Faculty of Chemistry , University of Gdańsk , Wita Stwosza 63 , 80-308 Gdańsk , Poland
| | - Adam Liwo
- Faculty of Chemistry , University of Gdańsk , Wita Stwosza 63 , 80-308 Gdańsk , Poland
| | - Cezary Czaplewski
- Faculty of Chemistry , University of Gdańsk , Wita Stwosza 63 , 80-308 Gdańsk , Poland
| | - Adam K Sieradzan
- Faculty of Chemistry , University of Gdańsk , Wita Stwosza 63 , 80-308 Gdańsk , Poland
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Lubecka EA, Karczyńska AS, Lipska AG, Sieradzan AK, Ziȩba K, Sikorska C, Uciechowska U, Samsonov SA, Krupa P, Mozolewska MA, Golon Ł, Giełdoń A, Czaplewski C, Ślusarz R, Ślusarz M, Crivelli SN, Liwo A. Evaluation of the scale-consistent UNRES force field in template-free prediction of protein structures in the CASP13 experiment. J Mol Graph Model 2019; 92:154-166. [PMID: 31376733 DOI: 10.1016/j.jmgm.2019.07.013] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2019] [Revised: 07/20/2019] [Accepted: 07/23/2019] [Indexed: 01/17/2023]
Abstract
The recent NEWCT-9P version of the coarse-grained UNRES force field for proteins, with scale-consistent formulas for the local and correlation terms, has been tested in the CASP13 experiment of the blind-prediction of protein structure, in the ab initio, contact-assisted, and data-assisted modes. Significant improvement of the performance has been observed with respect to the CASP11 and CASP12 experiments (by over 10 GDT_TS units for the ab initio mode predictions and by over 15 GDT_TS units for the contact-assisted prediction, respectively), which is a result of introducing scale-consistent terms and improved handling of contact-distance restraints. As in previous CASP exercises, UNRES ranked higher in the free modeling category than in the general category that included template based modeling targets. Use of distance restraints from the predicted contacts, albeit many of them were wrong, resulted in the increase of GDT_TS by over 8 units on average and introducing sparse restraints from small-angle X-ray/neutron scattering and chemical cross-link-mass-spectrometry experiments, and ambiguous restraints from nuclear magnetic resonance experiments has also improved the predictions by 8.6, 9.7, and 10.7 GDT_TS units on average, respectively.
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Affiliation(s)
- Emilia A Lubecka
- Institute of Informatics, Faculty of Mathematics, Physics, and Informatics, University of Gdańsk, Wita Stwosza 57, 80-308, Gdańsk, Poland; Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308, Gdańsk, Poland
| | | | - Agnieszka G Lipska
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308, Gdańsk, Poland
| | - Adam K Sieradzan
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308, Gdańsk, Poland
| | - Karolina Ziȩba
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308, Gdańsk, Poland
| | - Celina Sikorska
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308, Gdańsk, Poland
| | - Urszula Uciechowska
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308, Gdańsk, Poland
| | - Sergey A Samsonov
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308, Gdańsk, Poland
| | - Paweł Krupa
- Institute of Physics, Polish Academy of Sciences, Aleja Lotników 32/46, Warsaw, PL, 02668, Poland
| | - Magdalena A Mozolewska
- Institute of Computer Science, Polish Academy of Sciences, ul. Jana Kazimierza 5, Warsaw, 01-248, Poland
| | - Łukasz Golon
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308, Gdańsk, Poland
| | - Artur Giełdoń
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308, Gdańsk, Poland
| | - Cezary Czaplewski
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308, Gdańsk, Poland
| | - Rafał Ślusarz
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308, Gdańsk, Poland
| | - Magdalena Ślusarz
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308, Gdańsk, Poland
| | - Silvia N Crivelli
- Department of Computer Science, UC Davis, One Shields Ave., Davis, CA, 95616, USA
| | - Adam Liwo
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308, Gdańsk, Poland; School of Computational Sciences, Korea Institute for Advanced Study, 85 Hoegiro, Dongdaemun-gu, 130-722, Seoul, Republic of Korea.
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35
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Sieradzan AK, Bogunia M, Mech P, Ganzynkowicz R, Giełdoń A, Liwo A, Makowski M. Introduction of Phosphorylated Residues into the UNRES Coarse-Grained Model: Toward Modeling of Signaling Processes. J Phys Chem B 2019; 123:5721-5729. [PMID: 31194908 DOI: 10.1021/acs.jpcb.9b03799] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Phosphorylated proteins take part in many signaling pathways and play a key role in homeostasis regulation. The all-atom force fields enable us to study the systems containing phosphorylated proteins, but they are limited to short time scales. In this paper, we report the extension of the physics-based coarse-grained UNRES force field to treat systems with phosphorylated amino-acid residues. To derive the respective potentials, appropriate physics-based analytical expressions were fitted to the potentials of mean force of systems modeling phosphorylated amino-acid residues computed in our previous work and implemented in UNRES. The extended UNRES performed well in ab initio simulations of two miniproteins containing phosphorylated residues, strongly suggesting that realistic large-scale simulations of processes involving phosphorylated proteins, especially signaling processes, are now possible.
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Affiliation(s)
- Adam K Sieradzan
- Faculty of Chemistry , University of Gdańsk , ul. Wita Stwosza 63 , 80-308 Gdańsk , Poland
| | - Małgorzata Bogunia
- Faculty of Chemistry , University of Gdańsk , ul. Wita Stwosza 63 , 80-308 Gdańsk , Poland
| | - Paulina Mech
- Faculty of Chemistry , University of Gdańsk , ul. Wita Stwosza 63 , 80-308 Gdańsk , Poland
| | - Robert Ganzynkowicz
- Faculty of Chemistry , University of Gdańsk , ul. Wita Stwosza 63 , 80-308 Gdańsk , Poland
| | - Artur Giełdoń
- Faculty of Chemistry , University of Gdańsk , ul. Wita Stwosza 63 , 80-308 Gdańsk , Poland
| | - Adam Liwo
- Faculty of Chemistry , University of Gdańsk , ul. Wita Stwosza 63 , 80-308 Gdańsk , Poland
| | - Mariusz Makowski
- Faculty of Chemistry , University of Gdańsk , ul. Wita Stwosza 63 , 80-308 Gdańsk , Poland
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36
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Lubecka EA, Liwo A. Introduction of a bounded penalty function in contact-assisted simulations of protein structures to omit false restraints. J Comput Chem 2019; 40:2164-2178. [PMID: 31037754 DOI: 10.1002/jcc.25847] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2019] [Revised: 03/29/2019] [Accepted: 04/14/2019] [Indexed: 12/26/2022]
Abstract
Contact-assisted simulations, the contacts being predicted or determined experimentally, have become very important in the determination of the structures of proteins and other biological macromolecules. In this work, the effect of contact-distance restraints on the simulated structures was investigated with the use of multiplexed replica exchange simulations with the coarse-grained UNRES force field. A modified bounded flat-bottom restraint function that does not generate a gradient when a restraint cannot be satisfied was implemented. Calculations were run with (i) a set of four small proteins, with contact restraints derived from experimental structures, and (ii) selected CASP11 and CASP12 targets, with restraints as used at prediction time. The bounded penalty function largely omitted false contacts, which were usually inconsistent. It was found that at least 20% of correct contacts must be present in the restraint set to improve model quality with respect to unrestrained simulations. © 2019 Wiley Periodicals, Inc.
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Affiliation(s)
- Emilia A Lubecka
- Institute of Informatics, Faculty of Mathematics, Physics and Informatics, University of Gdańsk, Wita Stwosza 57, 80-308 Gdańsk, Poland.,Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland
| | - Adam Liwo
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland
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37
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Liwo A, Sieradzan AK, Lipska AG, Czaplewski C, Joung I, Żmudzińska W, Hałabis A, Ołdziej S. A general method for the derivation of the functional forms of the effective energy terms in coarse-grained energy functions of polymers. III. Determination of scale-consistent backbone-local and correlation potentials in the UNRES force field and force-field calibration and validation. J Chem Phys 2019; 150:155104. [PMID: 31005069 DOI: 10.1063/1.5093015] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
The general theory of the construction of scale-consistent energy terms in the coarse-grained force fields presented in Paper I of this series has been applied to the revision of the UNRES force field for physics-based simulations of proteins. The potentials of mean force corresponding to backbone-local and backbone-correlation energy terms were calculated from the ab initio energy surfaces of terminally blocked glycine, alanine, and proline, and the respective analytical expressions, derived by using the scale-consistent formalism, were fitted to them. The parameters of all these potentials depend on single-residue types, thus reducing their number and preventing over-fitting. The UNRES force field with the revised backbone-local and backbone-correlation terms was calibrated with a set of four small proteins with basic folds: tryptophan cage variant (TRP1; α), Full Sequence Design (FSD; α + β), villin headpiece (villin; α), and a truncated FBP-28 WW-domain variant (2MWD; β) (the NEWCT-4P force field) and, subsequently, with an enhanced set of 9 proteins composed of TRP1, FSD, villin, 1BDC (α), 2I18 (α), 1QHK (α + β), 2N9L (α + β), 1E0L (β), and 2LX7 (β) (the NEWCT-9P force field). The NEWCT-9P force field performed better than NEWCT-4P in a blind-prediction-like test with a set of 26 proteins not used in calibration and outperformed, in a test with 76 proteins, the most advanced OPT-WTFSA-2 version of UNRES with former backbone-local and backbone-correlation terms that contained more energy terms and more optimizable parameters. The NEWCT-9P force field reproduced the bimodal distribution of backbone-virtual-bond angles in the simulated structures, as observed in experimental protein structures.
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Affiliation(s)
- Adam Liwo
- Faculty of Chemistry, University of Gdańsk, ul. Wita-Stwosza 63, 80-308 Gdańsk, Poland
| | - Adam K Sieradzan
- Faculty of Chemistry, University of Gdańsk, ul. Wita-Stwosza 63, 80-308 Gdańsk, Poland
| | - Agnieszka G Lipska
- Faculty of Chemistry, University of Gdańsk, ul. Wita-Stwosza 63, 80-308 Gdańsk, Poland
| | - Cezary Czaplewski
- Faculty of Chemistry, University of Gdańsk, ul. Wita-Stwosza 63, 80-308 Gdańsk, Poland
| | - InSuk Joung
- School of Computational Sciences, Korea Institute for Advanced Study, 87 Hoegiro, Dongdaemun-gu, 130-722 Seoul, South Korea
| | - Wioletta Żmudzińska
- Intercollegiate Faculty of Biotechnology, University of Gdańsk and Medical University of Gdańsk, ul. Abrahama 58, 80-307 Gdańsk, Poland
| | - Anna Hałabis
- Intercollegiate Faculty of Biotechnology, University of Gdańsk and Medical University of Gdańsk, ul. Abrahama 58, 80-307 Gdańsk, Poland
| | - Stanisław Ołdziej
- Intercollegiate Faculty of Biotechnology, University of Gdańsk and Medical University of Gdańsk, ul. Abrahama 58, 80-307 Gdańsk, Poland
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38
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Samsonov SA, Lubecka EA, Bojarski KK, Ganzynkowicz R, Liwo A. Local and long range potentials for heparin‐protein systems for coarse‐grained simulations. Biopolymers 2019; 110:e23269. [DOI: 10.1002/bip.23269] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2018] [Revised: 02/21/2019] [Accepted: 02/22/2019] [Indexed: 12/31/2022]
Affiliation(s)
| | - Emilia A. Lubecka
- Faculty of ChemistryUniversity of Gdańsk Gdańsk Poland
- Faculty of Mathematics, Physics and Informatics, Institute of InformaticsUniversity of Gdańsk Gdańsk Poland
| | | | | | - Adam Liwo
- Faculty of ChemistryUniversity of Gdańsk Gdańsk Poland
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39
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Kohut G, Sieradzan A, Zsila F, Juhász T, Bősze S, Liwo A, Samsonov SA, Beke-Somfai T. The molecular mechanism of structural changes in the antimicrobial peptide CM15 upon complex formation with drug molecule suramin: a computational analysis. Phys Chem Chem Phys 2019; 21:10644-10659. [DOI: 10.1039/c9cp00471h] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Stabilization of helical conformations of CM15 upon interactions with suramin.
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Affiliation(s)
- Gergely Kohut
- Institute of Materials and Environmental Chemistry
- Research Centre for Natural Sciences
- Hungarian Academy of Sciences
- H-1117 Budapest
- Hungary
| | - Adam Sieradzan
- Faculty of Chemistry
- University of Gdańsk
- 80-308 Gdańsk
- Poland
| | - Ferenc Zsila
- Institute of Materials and Environmental Chemistry
- Research Centre for Natural Sciences
- Hungarian Academy of Sciences
- H-1117 Budapest
- Hungary
| | - Tünde Juhász
- Institute of Materials and Environmental Chemistry
- Research Centre for Natural Sciences
- Hungarian Academy of Sciences
- H-1117 Budapest
- Hungary
| | - Szilvia Bősze
- MTA-ELTE Research Group of Peptide Chemistry
- Hungarian Academy of Sciences
- Eötvös Loránd University
- H-1518 Budapest
- Hungary
| | - Adam Liwo
- Faculty of Chemistry
- University of Gdańsk
- 80-308 Gdańsk
- Poland
| | | | - Tamás Beke-Somfai
- Institute of Materials and Environmental Chemistry
- Research Centre for Natural Sciences
- Hungarian Academy of Sciences
- H-1117 Budapest
- Hungary
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40
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Faraggi E, Krupa P, Mozolewska MA, Liwo A, Kloczkowski A. Reoptimized UNRES Potential for Protein Model Quality Assessment. Genes (Basel) 2018; 9:genes9120601. [PMID: 30513992 PMCID: PMC6315818 DOI: 10.3390/genes9120601] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2018] [Revised: 11/25/2018] [Accepted: 11/27/2018] [Indexed: 11/16/2022] Open
Abstract
Ranking protein structure models is an elusive problem in bioinformatics. These models are evaluated on both the degree of similarity to the native structure and the folding pathway. Here, we simulated the use of the coarse-grained UNited RESidue (UNRES) force field as a tool to choose the best protein structure models for a given protein sequence among a pool of candidate models, using server data from the CASP11 experiment. Because the original UNRES was optimized for Molecular Dynamics simulations, we reoptimized UNRES using a deep feed-forward neural network, and we show that introducing additional descriptive features can produce better results. Overall, we found that the reoptimized UNRES performs better in selecting the best structures and tracking protein unwinding from its native state. We also found a relatively poor correlation between UNRES values and the model’s Template Modeling Score (TMS). This is remedied by reoptimization. We discuss some cases where our reoptimization procedure is useful.
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Affiliation(s)
- Eshel Faraggi
- Research and Information Systems, LLC, Indianapolis, IN 46240, USA.
- Department of Physics, Indiana University Purdue University Indianapolis, Indianapolis, IN 46202, USA.
- Battelle Center for Mathematical Medicine, Nationwide Children's Hospital, Columbus, OH 43215, USA.
| | - Pawel Krupa
- Battelle Center for Mathematical Medicine, Nationwide Children's Hospital, Columbus, OH 43215, USA.
- Institute of Physics, Polish Academy of Sciences, Al. Lotnikow 32/46, PL-02-668 Warsaw, Poland.
| | - Magdalena A Mozolewska
- Battelle Center for Mathematical Medicine, Nationwide Children's Hospital, Columbus, OH 43215, USA.
- Institute of Computer Science, Polish Academy of Sciences, ul. Jana Kazimierza 5, 01-248 Warszawa, Poland.
| | - Adam Liwo
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland.
- Center for In Silico Protein Structure and School of Computational Sciences, Korea Institute for Advanced Study, 85 Hoegiro, Dongdaemun-gu, Seoul 130-722, Korea.
| | - Andrzej Kloczkowski
- Battelle Center for Mathematical Medicine, Nationwide Children's Hospital, Columbus, OH 43215, USA.
- Department of Pediatrics, The Ohio State University, Columbus, OH 43215, USA.
- Kavli Institute for Theoretical Physics China, Chinese Academy of Sciences, Beijing 100190, China.
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41
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Sieradzan AK, Giełdoń A, Yin Y, He Y, Scheraga HA, Liwo A. A new protein nucleic-acid coarse-grained force field based on the UNRES and NARES-2P force fields. J Comput Chem 2018; 39:2360-2370. [PMID: 30306573 DOI: 10.1002/jcc.25571] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2018] [Revised: 06/29/2018] [Accepted: 08/08/2018] [Indexed: 12/22/2022]
Abstract
Based on the coarse-grained UNRES and NARES-2P models of proteins and nucleic acids, respectively, developed in our laboratory, in this work we have developed a coarse-grained model of systems containing proteins and nucleic acids. The UNRES and NARES-2P effective energy functions have been applied to the protein and nucleic-acid components of a system, respectively, while protein-nucleic-acid interactions have been described by the respective coarse-grained potentials developed in our recent work (Yin et al., J. Chem Theory Comput. 2015, 11, 1792). The Debye-Hückel screening has been applied to the electrostatic-interaction energy between the phosphate groups and charged amino-acid side chains. The model has been integrated into the UNRES package for coarse-grained molecular dynamics simulations of proteins and the implementation has been tested for energy conservation in microcanonical molecular dynamics runs and for temperature conservation in canonical molecular dynamics runs. Two case studies were performed: (i) the dynamics of the Ku protein heterodimer bound to DNA, for which it was found that the Ku70/Ku80 protein complex plays an active role in DNA repairing and (ii) conformational changes of the multiple antibiotic resistance (MarA) protein occurring during DNA binding, for which the functionally important motions occurring during this process were identified. © 2018 Wiley Periodicals, Inc.
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Affiliation(s)
- Adam K Sieradzan
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308, Gdańsk, Poland
| | - Artur Giełdoń
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308, Gdańsk, Poland
| | - Yanping Yin
- Baker Laboratory of Chemistry and Chemical Biology, Cornell University, Ithaca, New York, 14853-1301
| | - Yi He
- Baker Laboratory of Chemistry and Chemical Biology, Cornell University, Ithaca, New York, 14853-1301.,School of Engineering, University of California Merced, 5200 N. Lake Road, Merced, California, 95343
| | - Harold A Scheraga
- Baker Laboratory of Chemistry and Chemical Biology, Cornell University, Ithaca, New York, 14853-1301
| | - Adam Liwo
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308, Gdańsk, Poland
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42
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Kohut G, Liwo A, Bősze S, Beke-Somfai T, Samsonov SA. Protein-Ligand Interaction Energy-Based Entropy Calculations: Fundamental Challenges For Flexible Systems. J Phys Chem B 2018; 122:7821-7827. [PMID: 30049211 DOI: 10.1021/acs.jpcb.8b03658] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
Entropy calculations represent one of the most challenging steps in obtaining the binding free energy in biomolecular systems. A novel computationally effective approach (IE) was recently proposed to calculate the entropy based on the computation of protein-ligand interaction energy directly from molecular dynamics (MD) simulations. We present a study focused on the application of this method to flexible molecular systems and compare its performance with well-established normal mode (NM) and quasiharmonic (QH) entropy calculation approaches. Our results demonstrated that the IE method is intended for calculating entropy change for binding partners in fixed conformations, as by the original definition of IE, and is not applicable to the molecular complexes in which the interacting partners undergo significant conformational changes during the binding process.
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Affiliation(s)
- Gergely Kohut
- Institute of Materials and Environmental Chemistry, Research Centre for Natural Sciences, Hungarian Academy of Sciences , Magyar tudósok körútja 2 , H-1117 Budapest , Hungary
| | - Adam Liwo
- Faculty of Chemistry , University of Gdańsk , ul. Wita Stwosza 63 , 80-308 Gdańsk , Poland
| | - Szilvia Bősze
- MTA-ELTE Research Group of Peptide Chemistry , Hungarian Academy of Sciences, Eotvos Lorand University , Budapest 112 , P.O. Box 32, H-1518 Budapest , Hungary
| | - Tamás Beke-Somfai
- Institute of Materials and Environmental Chemistry, Research Centre for Natural Sciences, Hungarian Academy of Sciences , Magyar tudósok körútja 2 , H-1117 Budapest , Hungary.,Department of Chemical and Biological Engineering, Physical Chemistry , Chalmers University of Technology , SE-412 96 Göteborg , Sweden
| | - Sergey A Samsonov
- Faculty of Chemistry , University of Gdańsk , ul. Wita Stwosza 63 , 80-308 Gdańsk , Poland
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43
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Vallet SD, Miele AE, Uciechowska-Kaczmarzyk U, Liwo A, Duclos B, Samsonov SA, Ricard-Blum S. Insights into the structure and dynamics of lysyl oxidase propeptide, a flexible protein with numerous partners. Sci Rep 2018; 8:11768. [PMID: 30082873 PMCID: PMC6078952 DOI: 10.1038/s41598-018-30190-6] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2018] [Accepted: 07/20/2018] [Indexed: 01/29/2023] Open
Abstract
Lysyl oxidase (LOX) catalyzes the oxidative deamination of lysine and hydroxylysine residues in collagens and elastin, which is the first step of the cross-linking of these extracellular matrix proteins. It is secreted as a proenzyme activated by bone morphogenetic protein-1, which releases the LOX catalytic domain and its bioactive N-terminal propeptide. We characterized the recombinant human propeptide by circular dichroism, dynamic light scattering, and small-angle X-ray scattering (SAXS), and showed that it is elongated, monomeric, disordered and flexible (Dmax: 11.7 nm, Rg: 3.7 nm). We generated 3D models of the propeptide by coarse-grained molecular dynamics simulations restrained by SAXS data, which were used for docking experiments. Furthermore, we have identified 17 new binding partners of the propeptide by label-free assays. They include four glycosaminoglycans (hyaluronan, chondroitin, dermatan and heparan sulfate), collagen I, cross-linking and proteolytic enzymes (lysyl oxidase-like 2, transglutaminase-2, matrix metalloproteinase-2), a proteoglycan (fibromodulin), one growth factor (Epidermal Growth Factor, EGF), and one membrane protein (tumor endothelial marker-8). This suggests new roles for the propeptide in EGF signaling pathway.
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Affiliation(s)
- Sylvain D Vallet
- Univ Lyon, University Claude Bernard Lyon 1, CNRS, INSA Lyon, CPE, Institute of Molecular and Supramolecular Chemistry and Biochemistry, UMR 5246, F-69622, Villeurbanne cedex, France
| | - Adriana E Miele
- Univ Lyon, University Claude Bernard Lyon 1, CNRS, INSA Lyon, CPE, Institute of Molecular and Supramolecular Chemistry and Biochemistry, UMR 5246, F-69622, Villeurbanne cedex, France
| | - Urszula Uciechowska-Kaczmarzyk
- Laboratory of Molecular Modeling, Department of Theoretical Chemistry, Faculty of Chemistry, University of Gdansk, Wita Stwosza 63, 80-308, Gdańsk, Poland
| | - Adam Liwo
- Laboratory of Molecular Modeling, Department of Theoretical Chemistry, Faculty of Chemistry, University of Gdansk, Wita Stwosza 63, 80-308, Gdańsk, Poland
| | - Bertrand Duclos
- Univ Lyon, University Claude Bernard Lyon 1, CNRS, INSA Lyon, CPE, Institute of Molecular and Supramolecular Chemistry and Biochemistry, UMR 5246, F-69622, Villeurbanne cedex, France
| | - Sergey A Samsonov
- Laboratory of Molecular Modeling, Department of Theoretical Chemistry, Faculty of Chemistry, University of Gdansk, Wita Stwosza 63, 80-308, Gdańsk, Poland
| | - Sylvie Ricard-Blum
- Univ Lyon, University Claude Bernard Lyon 1, CNRS, INSA Lyon, CPE, Institute of Molecular and Supramolecular Chemistry and Biochemistry, UMR 5246, F-69622, Villeurbanne cedex, France.
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44
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Sieradzan AK, Golon Ł, Liwo A. Prediction of DNA and RNA structure with the NARES-2P force field and conformational space annealing. Phys Chem Chem Phys 2018; 20:19656-19663. [PMID: 30014063 DOI: 10.1039/c8cp03018a] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
A physics-based method for the prediction of the structures of nucleic acids, which is based on the physics-based 2-bead NARES-2P model of polynucleotides and global-optimization Conformational Space Annealing (CSA) algorithm has been proposed. The target structure is sought as the global-energy-minimum structure, which ignores the entropy component of the free energy but spares expensive multicanonical simulations necessary to find the conformational ensemble with the lowest free energy. The CSA algorithm has been modified to optimize its performance when treating both single and multi-chain nucleic acids. It was shown that the method finds the native fold for simple RNA molecules and DNA duplexes and with limited distance restraints, which can easily be obtained from the secondary-structure-prediction servers, complex RNA folds can be treated with using moderate computer resources.
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Affiliation(s)
- Adam K Sieradzan
- Faculty of Chemistry, University of Gdańsk, 80-308 Gdańsk, Poland.
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45
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Czaplewski C, Karczyńska A, Sieradzan AK, Liwo A. UNRES server for physics-based coarse-grained simulations and prediction of protein structure, dynamics and thermodynamics. Nucleic Acids Res 2018; 46:W304-W309. [PMID: 29718313 PMCID: PMC6031057 DOI: 10.1093/nar/gky328] [Citation(s) in RCA: 46] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2018] [Revised: 04/12/2018] [Accepted: 04/18/2018] [Indexed: 12/24/2022] Open
Abstract
A server implementation of the UNRES package (http://www.unres.pl) for coarse-grained simulations of protein structures with the physics-based UNRES model, coined a name UNRES server, is presented. In contrast to most of the protein coarse-grained models, owing to its physics-based origin, the UNRES force field can be used in simulations, including those aimed at protein-structure prediction, without ancillary information from structural databases; however, the implementation includes the possibility of using restraints. Local energy minimization, canonical molecular dynamics simulations, replica exchange and multiplexed replica exchange molecular dynamics simulations can be run with the current UNRES server; the latter are suitable for protein-structure prediction. The user-supplied input includes protein sequence and, optionally, restraints from secondary-structure prediction or small x-ray scattering data, and simulation type and parameters which are selected or typed in. Oligomeric proteins, as well as those containing D-amino-acid residues and disulfide links can be treated. The output is displayed graphically (minimized structures, trajectories, final models, analysis of trajectory/ensembles); however, all output files can be downloaded by the user. The UNRES server can be freely accessed at http://unres-server.chem.ug.edu.pl.
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Affiliation(s)
- Cezary Czaplewski
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland
| | - Agnieszka Karczyńska
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland
| | - Adam K Sieradzan
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland
| | - Adam Liwo
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland
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46
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Keasar C, McGuffin LJ, Wallner B, Chopra G, Adhikari B, Bhattacharya D, Blake L, Bortot LO, Cao R, Dhanasekaran BK, Dimas I, Faccioli RA, Faraggi E, Ganzynkowicz R, Ghosh S, Ghosh S, Giełdoń A, Golon L, He Y, Heo L, Hou J, Khan M, Khatib F, Khoury GA, Kieslich C, Kim DE, Krupa P, Lee GR, Li H, Li J, Lipska A, Liwo A, Maghrabi AHA, Mirdita M, Mirzaei S, Mozolewska MA, Onel M, Ovchinnikov S, Shah A, Shah U, Sidi T, Sieradzan AK, Ślusarz M, Ślusarz R, Smadbeck J, Tamamis P, Trieber N, Wirecki T, Yin Y, Zhang Y, Bacardit J, Baranowski M, Chapman N, Cooper S, Defelicibus A, Flatten J, Koepnick B, Popović Z, Zaborowski B, Baker D, Cheng J, Czaplewski C, Delbem ACB, Floudas C, Kloczkowski A, Ołdziej S, Levitt M, Scheraga H, Seok C, Söding J, Vishveshwara S, Xu D, Crivelli SN. An analysis and evaluation of the WeFold collaborative for protein structure prediction and its pipelines in CASP11 and CASP12. Sci Rep 2018; 8:9939. [PMID: 29967418 PMCID: PMC6028396 DOI: 10.1038/s41598-018-26812-8] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2017] [Accepted: 05/17/2018] [Indexed: 01/14/2023] Open
Abstract
Every two years groups worldwide participate in the Critical Assessment of Protein Structure Prediction (CASP) experiment to blindly test the strengths and weaknesses of their computational methods. CASP has significantly advanced the field but many hurdles still remain, which may require new ideas and collaborations. In 2012 a web-based effort called WeFold, was initiated to promote collaboration within the CASP community and attract researchers from other fields to contribute new ideas to CASP. Members of the WeFold coopetition (cooperation and competition) participated in CASP as individual teams, but also shared components of their methods to create hybrid pipelines and actively contributed to this effort. We assert that the scale and diversity of integrative prediction pipelines could not have been achieved by any individual lab or even by any collaboration among a few partners. The models contributed by the participating groups and generated by the pipelines are publicly available at the WeFold website providing a wealth of data that remains to be tapped. Here, we analyze the results of the 2014 and 2016 pipelines showing improvements according to the CASP assessment as well as areas that require further adjustments and research.
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Affiliation(s)
- Chen Keasar
- Department of Computer Science, Ben Gurion University of the Negev, Be'er sheva, Israel
| | - Liam J McGuffin
- Biomedical Sciences Division, School of Biological Sciences, University of Reading, Reading, RG6 6AS, UK
| | - Björn Wallner
- Division of Bioinformatics, Department of Physics, Chemistry, and Biology, Linköping University, Linköping, Sweden
| | - Gaurav Chopra
- Department of Chemistry, College of Science, Purdue University, West Lafayette, IN, USA
- Purdue Institute for Drug Discovery, Purdue University, West Lafayette, IN, USA
- Purdue Center for Cancer Research, Purdue University, West Lafayette, IN, USA
- Purdue Institute for Inflammation, Immunology and Infectious Disease, Purdue University, West Lafayette, IN, USA
- Purdue Institute for Integrative Neuroscience, Purdue University, West Lafayette, IN, USA
| | - Badri Adhikari
- Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, USA
| | - Debswapna Bhattacharya
- Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, USA
- Department of Computer Science and Software Engineering, Auburn University, Auburn, AL, USA
| | - Lauren Blake
- Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Leandro Oliveira Bortot
- Laboratory of Biological Physics, Faculty of Pharmaceutical Sciences at Ribeirão Preto, University of São Paulo, São Paulo, Brazil
| | - Renzhi Cao
- Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, USA
| | - B K Dhanasekaran
- Molecular Biophysics Unit and IISC Mathematics Initiative, Indian Institute of Science, Bangalore, India
| | - Itzhel Dimas
- Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | | | - Eshel Faraggi
- Research and Information Systems, LLC, Carmel, IN, USA
- Department of Biochemistry and Molecular Biology, IU School of Medicine, Indianapolis, IN, USA
- Batelle Center for Mathematical Medicine, The Research Institute at Nationwide Children's Hospital, Columbus, OH, USA
| | | | - Sambit Ghosh
- Molecular Biophysics Unit and IISC Mathematics Initiative, Indian Institute of Science, Bangalore, India
| | - Soma Ghosh
- Molecular Biophysics Unit and IISC Mathematics Initiative, Indian Institute of Science, Bangalore, India
| | - Artur Giełdoń
- Faculty of Chemistry, University of Gdansk, Gdańsk, Poland
| | - Lukasz Golon
- Faculty of Chemistry, University of Gdansk, Gdańsk, Poland
| | - Yi He
- School of Engineering, University of California, Merced, CA, USA
| | - Lim Heo
- Department of Chemistry, Seoul National University, Seoul, Republic of Korea
| | - Jie Hou
- Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, USA
| | - Main Khan
- Department of Computer and Information Science, University of Massachusetts Dartmouth, MA, USA
| | - Firas Khatib
- Department of Computer and Information Science, University of Massachusetts Dartmouth, MA, USA
| | - George A Khoury
- Department of Chemical and Biological Engineering, Princeton University, Princeton, NJ, USA
| | - Chris Kieslich
- Texas A&M Energy Institute, Texas A&M University, College Station, TX, USA
| | - David E Kim
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
| | - Pawel Krupa
- Faculty of Chemistry, University of Gdansk, Gdańsk, Poland
| | - Gyu Rie Lee
- Department of Chemistry, Seoul National University, Seoul, Republic of Korea
| | - Hongbo Li
- Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, USA
- School of Computer Science and Information Technology, NorthEast Normal University, Changchun, China
- Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO, USA
| | - Jilong Li
- Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, USA
| | | | - Adam Liwo
- Faculty of Chemistry, University of Gdansk, Gdańsk, Poland
| | - Ali Hassan A Maghrabi
- Biomedical Sciences Division, School of Biological Sciences, University of Reading, Reading, RG6 6AS, UK
| | - Milot Mirdita
- Max Planck Institute for Biophysical Chemistry, Göttingen, Germany
| | - Shokoufeh Mirzaei
- Lawrence Berkeley National Laboratory, Berkeley, CA, USA
- California State Polytechnic University, Pomona, CA, USA
| | | | - Melis Onel
- Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, TX, USA
| | - Sergey Ovchinnikov
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Anand Shah
- Department of Computer and Information Science, University of Massachusetts Dartmouth, MA, USA
| | - Utkarsh Shah
- Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, TX, USA
| | - Tomer Sidi
- Department of Computer Science, Ben Gurion University of the Negev, Be'er sheva, Israel
| | | | | | - Rafal Ślusarz
- Faculty of Chemistry, University of Gdansk, Gdańsk, Poland
| | - James Smadbeck
- Department of Chemical and Biological Engineering, Princeton University, Princeton, NJ, USA
| | - Phanourios Tamamis
- Texas A&M Energy Institute, Texas A&M University, College Station, TX, USA
- Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, TX, USA
| | - Nicholas Trieber
- Department of Computer and Information Science, University of Massachusetts Dartmouth, MA, USA
| | - Tomasz Wirecki
- Faculty of Chemistry, University of Gdansk, Gdańsk, Poland
| | - Yanping Yin
- Baker Laboratory of Chemistry and Chemical Biology, Cornell University, Ithaca, NY, USA
| | - Yang Zhang
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Jaume Bacardit
- Interdisciplinary Computing and Complex BioSystems (ICOS) research group, School of Computing, Newcastle University, Newcastle-upon-Tyne, UK
| | - Maciej Baranowski
- Intercollegiate Faculty of Biotechnology, University of Gdańsk and Medical University of Gdańsk, Gdańsk, Poland
| | - Nicholas Chapman
- Center for Game Science, Department of Computer Science & Engineering, University of Washington, Seattle, WA, USA
| | - Seth Cooper
- College of Computer and Information Science, Northeastern University, Boston, MA, USA
| | - Alexandre Defelicibus
- Institute of Mathematical and Computer Sciences, University of São Paulo, São Paulo, Brazil
| | - Jeff Flatten
- Center for Game Science, Department of Computer Science & Engineering, University of Washington, Seattle, WA, USA
| | - Brian Koepnick
- Department of Biochemistry, University of Washington, Seattle, WA, USA
| | - Zoran Popović
- Center for Game Science, Department of Computer Science & Engineering, University of Washington, Seattle, WA, USA
| | | | - David Baker
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
- Center for Game Science, Department of Computer Science & Engineering, University of Washington, Seattle, WA, USA
| | - Jianlin Cheng
- Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, USA
| | | | | | | | | | - Stanislaw Ołdziej
- Intercollegiate Faculty of Biotechnology, University of Gdańsk and Medical University of Gdańsk, Gdańsk, Poland
| | - Michael Levitt
- Department of Structural Biology, School of Medicine, Stanford University, Stanford, CA, USA
| | - Harold Scheraga
- Baker Laboratory of Chemistry and Chemical Biology, Cornell University, Ithaca, NY, USA
| | - Chaok Seok
- Department of Chemistry, Seoul National University, Seoul, Republic of Korea
| | - Johannes Söding
- Max Planck Institute for Biophysical Chemistry, Göttingen, Germany
| | - Saraswathi Vishveshwara
- Molecular Biophysics Unit and IISC Mathematics Initiative, Indian Institute of Science, Bangalore, India
| | - Dong Xu
- Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, USA
- Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO, USA
| | - Silvia N Crivelli
- Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
- Department of Computer Science, University of California, Davis, CA, USA.
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47
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Sieradzan AK, Makowski M, Augustynowicz A, Liwo A. A general method for the derivation of the functional forms of the effective energy terms in coarse-grained energy functions of polymers. I. Backbone potentials of coarse-grained polypeptide chains. J Chem Phys 2018; 146:124106. [PMID: 28388107 DOI: 10.1063/1.4978680] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023] Open
Abstract
A general and systematic method for the derivation of the functional expressions for the effective energy terms in coarse-grained force fields of polymer chains is proposed. The method is based on the expansion of the potential of mean force of the system studied in the cluster-cumulant series and expanding the all-atom energy in the Taylor series in the squares of interatomic distances about the squares of the distances between coarse-grained centers, to obtain approximate analytical expressions for the cluster cumulants. The primary degrees of freedom to average about are the angles for collective rotation of the atoms contained in the coarse-grained interaction sites about the respective virtual-bond axes. The approach has been applied to the revision of the virtual-bond-angle, virtual-bond-torsional, and backbone-local-and-electrostatic correlation potentials for the UNited RESidue (UNRES) model of polypeptide chains, demonstrating the strong dependence of the torsional and correlation potentials on virtual-bond angles, not considered in the current UNRES. The theoretical considerations are illustrated with the potentials calculated from the ab initiopotential-energysurface of terminally blocked alanine by numerical integration and with the statistical potentials derived from known protein structures. The revised torsional potentials correctly indicate that virtual-bond angles close to 90° result in the preference for the turn and helical structures, while large virtual-bond angles result in the preference for polyproline II and extended backbone geometry. The revised correlation potentials correctly reproduce the preference for the formation of β-sheet structures for large values of virtual-bond angles and for the formation of α-helical structures for virtual-bond angles close to 90°.
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Affiliation(s)
- Adam K Sieradzan
- Faculty of Chemistry, University of Gdańsk, ul. Wita-Stwosza 63, 80-308 Gdańsk, Poland
| | - Mariusz Makowski
- Faculty of Chemistry, University of Gdańsk, ul. Wita-Stwosza 63, 80-308 Gdańsk, Poland
| | - Antoni Augustynowicz
- Faculty of Mathematics, Physics, and Informatics, University of Gdańsk, ul. Wita Stwosza 57, 80-308 Gdańsk, Poland
| | - Adam Liwo
- Faculty of Chemistry, University of Gdańsk, ul. Wita-Stwosza 63, 80-308 Gdańsk, Poland
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Krupa P, Hałabis A, Żmudzińska W, Ołdziej S, Scheraga HA, Liwo A. Correction to Maximum Likelihood Calibration of the UNRES Force Field for Simulation of Protein Structure and Dynamics. J Chem Inf Model 2018; 58:206. [PMID: 29283263 DOI: 10.1021/acs.jcim.7b00716] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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49
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Karczyńska AS, Mozolewska MA, Krupa P, Giełdoń A, Liwo A, Czaplewski C. Prediction of protein structure with the coarse-grained UNRES force field assisted by small X-ray scattering data and knowledge-based information. Proteins 2017; 86 Suppl 1:228-239. [PMID: 29134679 DOI: 10.1002/prot.25421] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2017] [Revised: 11/09/2017] [Accepted: 11/10/2017] [Indexed: 11/09/2022]
Abstract
A new approach to assisted protein-structure prediction has been proposed, which is based on running multiplexed replica exchange molecular dynamics simulations with the coarse-grained UNRES force field with restraints derived from knowledge-based models and distance distribution from small angle X-ray scattering (SAXS) measurements. The latter restraints are incorporated into the target function as a maximum-likelihood term that guides the shape of the simulated structures towards that defined by SAXS. The approach was first verified with the 1KOY protein, for which the distance distribution was calculated from the experimental structure, and subsequently used to predict the structures of 11 data-assisted targets in the CASP12 experiment. Major improvement of the GDT_TS was obtained for 2 targets, minor improvement for other 2 while, for 6 target GDT_TS deteriorated compared with that calculated for predictions without the SAXS data, partly because of assuming a wrong multimeric state (for Ts866) or because the crystal conformation was more compact than the solution conformation (for Ts942). Particularly good results were obtained for Ts909, in which use of SAXS data resulted in the selection of a correctly packed trimer and, subsequently, increased the GDT_TS of monomer prediction. It was found that running simulations with correct oligomeric state is essential for the success in SAXS-data-assisted prediction.
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Affiliation(s)
| | - Magdalena A Mozolewska
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, Gdańsk, 80-308, Poland.,Institute of Computer Science, Polish Academy of Sciences, ul. Jana Kazimierza 5, Warsaw, 01-248, Poland
| | - Paweł Krupa
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, Gdańsk, 80-308, Poland.,Institute of Physics, Polish Academy of Sciences, Aleja Lotników 32/46, Warsaw, PL-02668, Poland
| | - Artur Giełdoń
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, Gdańsk, 80-308, Poland
| | - Adam Liwo
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, Gdańsk, 80-308, Poland.,School of Computational Sciences, Korea Institute for Advanced Study, 85 Hoegiro, Dongdaemun-gu, Seoul, 130-722, Republic of Korea
| | - Cezary Czaplewski
- Faculty of Chemistry, University of Gdańsk, Wita Stwosza 63, Gdańsk, 80-308, Poland
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50
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Krupa P, Sieradzan AK, Mozolewska MA, Li H, Liwo A, Scheraga HA. Dynamics of Disulfide-Bond Disruption and Formation in the Thermal Unfolding of Ribonuclease A. J Chem Theory Comput 2017; 13:5721-5730. [DOI: 10.1021/acs.jctc.7b00724] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Paweł Krupa
- Baker
Laboratory of Chemistry and Chemical Biology, Cornell University, Ithaca, New York 14853-1301, United States
| | - Adam K. Sieradzan
- Faculty
of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland
| | - Magdalena A. Mozolewska
- Baker
Laboratory of Chemistry and Chemical Biology, Cornell University, Ithaca, New York 14853-1301, United States
| | - Huiyu Li
- Baker
Laboratory of Chemistry and Chemical Biology, Cornell University, Ithaca, New York 14853-1301, United States
| | - Adam Liwo
- Faculty
of Chemistry, University of Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland
| | - Harold A. Scheraga
- Baker
Laboratory of Chemistry and Chemical Biology, Cornell University, Ithaca, New York 14853-1301, United States
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