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] [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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Stahl K, Graziadei A, Dau T, Brock O, Rappsilber J. Protein structure prediction with in-cell photo-crosslinking mass spectrometry and deep learning. Nat Biotechnol 2023; 41:1810-1819. [PMID: 36941363 PMCID: PMC10713450 DOI: 10.1038/s41587-023-01704-z] [Citation(s) in RCA: 40] [Impact Index Per Article: 40.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Accepted: 02/06/2023] [Indexed: 03/23/2023]
Abstract
While AlphaFold2 can predict accurate protein structures from the primary sequence, challenges remain for proteins that undergo conformational changes or for which few homologous sequences are known. Here we introduce AlphaLink, a modified version of the AlphaFold2 algorithm that incorporates experimental distance restraint information into its network architecture. By employing sparse experimental contacts as anchor points, AlphaLink improves on the performance of AlphaFold2 in predicting challenging targets. We confirm this experimentally by using the noncanonical amino acid photo-leucine to obtain information on residue-residue contacts inside cells by crosslinking mass spectrometry. The program can predict distinct conformations of proteins on the basis of the distance restraints provided, demonstrating the value of experimental data in driving protein structure prediction. The noise-tolerant framework for integrating data in protein structure prediction presented here opens a path to accurate characterization of protein structures from in-cell data.
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Affiliation(s)
- Kolja Stahl
- Robotics and Biology Laboratory, Technische Universität Berlin, Berlin, Germany
| | - Andrea Graziadei
- Technische Universität Berlin, Chair of Bioanalytics, Berlin, Germany
| | - Therese Dau
- Technische Universität Berlin, Chair of Bioanalytics, Berlin, Germany
- Fritz Lipmann Institute, Leibniz Institute on Aging, Jena, Germany
| | - Oliver Brock
- Robotics and Biology Laboratory, Technische Universität Berlin, Berlin, Germany.
- Science of Intelligence, Research Cluster of Excellence, Berlin, Germany.
| | - Juri Rappsilber
- Technische Universität Berlin, Chair of Bioanalytics, Berlin, Germany.
- Si-M/'Der Simulierte Mensch', a Science Framework of Technische Universität Berlin and Charité - Universitätsmedizin Berlin, Berlin, Germany.
- Wellcome Centre for Cell Biology, University of Edinburgh, Edinburgh, UK.
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3
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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: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [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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4
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Mondal A, Lenz S, MacCallum JL, Perez A. Hybrid computational methods combining experimental information with molecular dynamics. Curr Opin Struct Biol 2023; 81:102609. [PMID: 37224642 DOI: 10.1016/j.sbi.2023.102609] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2023] [Revised: 04/12/2023] [Accepted: 04/23/2023] [Indexed: 05/26/2023]
Abstract
A goal of structural biology is to understand how macromolecules carry out their biological roles by identifying their metastable states, mechanisms of action, pathways leading to conformational changes, and the thermodynamic and kinetic relationships between those states. Integrative modeling brings structural insights into systems where traditional structure determination approaches cannot help. We focus on the synergies and challenges of integrative modeling combining experimental data with molecular dynamics simulations.
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Affiliation(s)
- Arup Mondal
- Quantum Theory Project, Department of Chemistry, University of Florida, Leigh, UK. https://twitter.com/@amondal_chem
| | - Stefan Lenz
- Department of Chemistry, University of Calgary, 2500 University Drive, Canada
| | - Justin L MacCallum
- Department of Chemistry, University of Calgary, 2500 University Drive, Canada. https://twitter.com/@jlmaccal
| | - Alberto Perez
- Quantum Theory Project, Department of Chemistry, University of Florida, Leigh, UK.
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5
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Oppenheim T, Radzinski M, Braitbard M, Brielle ES, Yogev O, Goldberger E, Yesharim Y, Ravid T, Schneidman-Duhovny D, Reichmann D. The Cdc48 N-terminal domain has a molecular switch that mediates the Npl4-Ufd1-Cdc48 complex formation. Structure 2023; 31:764-779.e8. [PMID: 37311459 DOI: 10.1016/j.str.2023.05.014] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2022] [Revised: 02/28/2023] [Accepted: 05/18/2023] [Indexed: 06/15/2023]
Abstract
Cdc48 (VCP/p97) is a major AAA-ATPase involved in protein quality control, along with its canonical cofactors Ufd1 and Npl4 (UN). Here, we present novel structural insights into the interactions within the Cdc48-Npl4-Ufd1 ternary complex. Using integrative modeling, we combine subunit structures with crosslinking mass spectrometry (XL-MS) to map the interaction between Npl4 and Ufd1, alone and in complex with Cdc48. We describe the stabilization of the UN assembly upon binding with the N-terminal-domain (NTD) of Cdc48 and identify a highly conserved cysteine, C115, at the Cdc48-Npl4-binding interface which is central to the stability of the Cdc48-Npl4-Ufd1 complex. Mutation of Cys115 to serine disrupts the interaction between Cdc48-NTD and Npl4-Ufd1 and leads to a moderate decrease in cellular growth and protein quality control in yeast. Our results provide structural insight into the architecture of the Cdc48-Npl4-Ufd1 complex as well as its in vivo implications.
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Affiliation(s)
- Tal Oppenheim
- Department of Biological Chemistry, The Alexander Silberman Institute of Life Sciences, Safra Campus Givat Ram, the Hebrew University of Jerusalem, Jerusalem 91904, Israel
| | - Meytal Radzinski
- Department of Biological Chemistry, The Alexander Silberman Institute of Life Sciences, Safra Campus Givat Ram, the Hebrew University of Jerusalem, Jerusalem 91904, Israel
| | - Merav Braitbard
- Department of Biological Chemistry, The Alexander Silberman Institute of Life Sciences, Safra Campus Givat Ram, the Hebrew University of Jerusalem, Jerusalem 91904, Israel
| | - Esther S Brielle
- Department of Biological Chemistry, The Alexander Silberman Institute of Life Sciences, Safra Campus Givat Ram, the Hebrew University of Jerusalem, Jerusalem 91904, Israel
| | - Ohad Yogev
- Department of Biological Chemistry, The Alexander Silberman Institute of Life Sciences, Safra Campus Givat Ram, the Hebrew University of Jerusalem, Jerusalem 91904, Israel
| | - Eliya Goldberger
- Department of Biological Chemistry, The Alexander Silberman Institute of Life Sciences, Safra Campus Givat Ram, the Hebrew University of Jerusalem, Jerusalem 91904, Israel
| | - Yarden Yesharim
- Department of Biological Chemistry, The Alexander Silberman Institute of Life Sciences, Safra Campus Givat Ram, the Hebrew University of Jerusalem, Jerusalem 91904, Israel
| | - Tommer Ravid
- Department of Biological Chemistry, The Alexander Silberman Institute of Life Sciences, Safra Campus Givat Ram, the Hebrew University of Jerusalem, Jerusalem 91904, Israel
| | - Dina Schneidman-Duhovny
- School of Computer Science and Engineering, the Hebrew University of Jerusalem, Jerusalem 9190401, Israel.
| | - Dana Reichmann
- Department of Biological Chemistry, The Alexander Silberman Institute of Life Sciences, Safra Campus Givat Ram, the Hebrew University of Jerusalem, Jerusalem 91904, Israel.
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6
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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] [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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7
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Modeling the Structure, Dynamics, and Transformations of Proteins with the UNRES Force Field. METHODS IN MOLECULAR BIOLOGY (CLIFTON, N.J.) 2022; 2376:399-416. [PMID: 34845623 DOI: 10.1007/978-1-0716-1716-8_23] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
The physics-based united-residue (UNRES) model of proteins ( www.unres.pl ) has been designed to carry out large-scale simulations of protein folding. The force field has been derived and parameterized based on the principles of statistical-mechanics, which makes it independent of structural databases and applicable to treat nonstandard situations such as, proteins that contain D-amino-acid residues. Powered by Langevin dynamics and its replica-exchange extensions, UNRES has found a variety of applications, including ab initio and database-assisted protein-structure prediction, simulating protein-folding pathways, exploring protein free-energy landscapes, and solving biological problems. This chapter provides a summary of UNRES and a guide for potential users regarding the application of the UNRES package in a variety of research tasks.
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8
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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] [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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9
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Kryshtafovych A, Schwede T, Topf M, Fidelis K, Moult J. Critical assessment of methods of protein structure prediction (CASP)-Round XIV. Proteins 2021; 89:1607-1617. [PMID: 34533838 PMCID: PMC8726744 DOI: 10.1002/prot.26237] [Citation(s) in RCA: 225] [Impact Index Per Article: 75.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Accepted: 07/28/2021] [Indexed: 01/14/2023]
Abstract
Critical assessment of structure prediction (CASP) is a community experiment to advance methods of computing three-dimensional protein structure from amino acid sequence. Core components are rigorous blind testing of methods and evaluation of the results by independent assessors. In the most recent experiment (CASP14), deep-learning methods from one research group consistently delivered computed structures rivaling the corresponding experimental ones in accuracy. In this sense, the results represent a solution to the classical protein-folding problem, at least for single proteins. The models have already been shown to be capable of providing solutions for problematic crystal structures, and there are broad implications for the rest of structural biology. Other research groups also substantially improved performance. Here, we describe these results and outline some of the many implications. Other related areas of CASP, including modeling of protein complexes, structure refinement, estimation of model accuracy, and prediction of inter-residue contacts and distances, are also described.
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Affiliation(s)
- Andriy Kryshtafovych
- Genome Center, University of California, Davis, 451 Health Sciences Drive, Davis, CA 95616, USA
| | - Torsten Schwede
- University of Basel, Biozentrum & SIB Swiss Institute of Bioinformatics, Basel, Switzerland
| | - Maya Topf
- Centre for Structural Systems Biology, Leibniz-Institut für Experimentelle Virologie and Universit tsklinikum Hamburg-Eppendorf (UKE), Hamburg, Germany
| | - Krzysztof Fidelis
- Genome Center, University of California, Davis, 451 Health Sciences Drive, Davis, CA 95616, USA
| | - John Moult
- Institute for Bioscience and Biotechnology Research, 9600 Gudelsky Drive, Rockville, MD 20850, USA, Department of Cell Biology and Molecular Genetics, University of Maryland
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10
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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] [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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11
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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] [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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12
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Structural interactions define assembly adapter function of a type II secretion system pseudopilin. Structure 2021; 29:1116-1127.e8. [PMID: 34139172 DOI: 10.1016/j.str.2021.05.015] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Revised: 03/15/2021] [Accepted: 05/28/2021] [Indexed: 01/13/2023]
Abstract
The type IV filament superfamily comprises widespread membrane-associated polymers in prokaryotes. The type II secretion system (T2SS), a virulence pathway in many pathogens, belongs to this superfamily. A knowledge gap in understanding of the T2SS is the molecular role of a small "pseudopilin" protein. Using multiple biophysical techniques, we have deciphered how this missing component of the Xcp T2SS architecture is structurally integrated, and thereby unlocked its function. We demonstrate that low-abundance XcpH is the adapter that bridges a trimeric initiating tip complex, XcpIJK, with a periplasmic filament of XcpG subunits. Each pseudopilin protein caps an XcpG protofilament in an overall pseudopilus compatible with dimensions of the periplasm and the outer membrane-spanning secretin through which substrates pass. Unexpectedly, to fulfill its adapter function, the XcpH N-terminal helix must be unwound, a property shared with XcpG subunits. We provide an experimentally validated three-dimensional structural model of a complete type IV filament.
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13
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Zhang F, Zhang N, Xu Q, Zhang L, Zhang C, Liu H, Yu Z, Zhou S, Feng G, Huang F. Decellularized nerve extracellular matrix/chitosan crosslinked by genipin to prepare a moldable nerve repair material. Cell Tissue Bank 2021; 22:419-430. [PMID: 34115245 PMCID: PMC8192270 DOI: 10.1007/s10561-020-09889-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2020] [Accepted: 12/04/2020] [Indexed: 01/23/2023]
Abstract
Decellularized nerve extracellular matrix (NECM) composited with chitosan are moldable materials suitable for spinal cord repair. But the rapid biodegradation of the materials may interrupt neural tissue reconstruction in vivo. To improve the stability of the materials, the materials produced by NECM and chitosan hydrogels were crosslinked by genipine, glutaraldehyde or ultraviolet ray. Physicochemical property, degradation and biocompatibility of materials crosslinked by genipin, glutaraldehyde or ultraviolet ray were evaluated. The scaffold crosslinked by genipin possessed a porous structure, and the porosity ratio was 89.07 + 4.90%, the average diameter of pore was 85.32 + 5.34 μm. The crosslinked degree of the scaffold crosslinked by genipin and glutaraldehyde was 75.13 ± 4.87%, 71.25 ± 5.06% respectively; Uncrosslinked scaffold disintegrated when immerged in distilled water while the scaffold crosslinked by genipin and glutaraldehyde group retained their integrity. The scaffold crosslinked by genipin has better water absorption, water retention and anti-enzymatic hydrolysis ability than the other three groups. Cell cytotoxicity showed that the cytotoxicity of scaffold crosslinked by genipin was lower than that crosslinked by glutaraldehyde. The histocompatibility of scaffold crosslinked by genipin was also better than glutaraldehyde group. More cells grew well in the scaffold crosslinked by genipin when co-cultured with L929 cells. The decellularized nerve extracellular matrix/chitosan scaffold crosslinked by the genipin has good mechanical properties, micro structure and biocompatibility, which is an ideal scaffold for the spinal cord tissue engineering.
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Affiliation(s)
- Fangsong Zhang
- Department of Human Anatomy, College of Basic Medical Sciences, Binzhou Medical University, Yantai, 264003, People's Republic of China
- Department of Medical Imagine, Shanghai Mental Health Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200030, People's Republic of China
| | - Naili Zhang
- Department of Human Anatomy, College of Basic Medical Sciences, Binzhou Medical University, Yantai, 264003, People's Republic of China
- Institute of Human Anatomy and Histology and Embryology, Binzhou Medical University, Yantai, 264003, People's Republic of China
| | - Qing Xu
- Yantai Affiliated Hosptial of Binzhou Medical University, Yantai, 264100, People's Republic of China
| | - Luping Zhang
- Department of Human Anatomy, College of Basic Medical Sciences, Binzhou Medical University, Yantai, 264003, People's Republic of China
- Institute of Human Anatomy and Histology and Embryology, Binzhou Medical University, Yantai, 264003, People's Republic of China
| | - Chunlei Zhang
- Department of Human Anatomy, College of Basic Medical Sciences, Binzhou Medical University, Yantai, 264003, People's Republic of China
- Institute of Human Anatomy and Histology and Embryology, Binzhou Medical University, Yantai, 264003, People's Republic of China
| | - Hongfu Liu
- Department of Human Anatomy, College of Basic Medical Sciences, Binzhou Medical University, Yantai, 264003, People's Republic of China
- Institute of Human Anatomy and Histology and Embryology, Binzhou Medical University, Yantai, 264003, People's Republic of China
| | - Zhenhai Yu
- Department of Human Anatomy, College of Basic Medical Sciences, Binzhou Medical University, Yantai, 264003, People's Republic of China
- Institute of Human Anatomy and Histology and Embryology, Binzhou Medical University, Yantai, 264003, People's Republic of China
| | - Shuai Zhou
- Department of Human Anatomy, College of Basic Medical Sciences, Binzhou Medical University, Yantai, 264003, People's Republic of China
- Institute of Human Anatomy and Histology and Embryology, Binzhou Medical University, Yantai, 264003, People's Republic of China
| | - Guoying Feng
- Department of Human Anatomy, College of Basic Medical Sciences, Binzhou Medical University, Yantai, 264003, People's Republic of China
- Institute of Human Anatomy and Histology and Embryology, Binzhou Medical University, Yantai, 264003, People's Republic of China
| | - Fei Huang
- Department of Human Anatomy, College of Basic Medical Sciences, Binzhou Medical University, Yantai, 264003, People's Republic of China.
- Institute of Human Anatomy and Histology and Embryology, Binzhou Medical University, Yantai, 264003, People's Republic of China.
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14
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Ziegler SJ, Mallinson SJ, St. John PC, Bomble YJ. Advances in integrative structural biology: Towards understanding protein complexes in their cellular context. Comput Struct Biotechnol J 2020; 19:214-225. [PMID: 33425253 PMCID: PMC7772369 DOI: 10.1016/j.csbj.2020.11.052] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2020] [Revised: 11/25/2020] [Accepted: 11/28/2020] [Indexed: 01/26/2023] Open
Abstract
Microorganisms rely on protein interactions to transmit signals, react to stimuli, and grow. One of the best ways to understand these protein interactions is through structural characterization. However, in the past, structural knowledge was limited to stable, high-affinity complexes that could be crystallized. Recent developments in structural biology have revolutionized how protein interactions are characterized. The combination of multiple techniques, known as integrative structural biology, has provided insight into how large protein complexes interact in their native environment. In this mini-review, we describe the past, present, and potential future of integrative structural biology as a tool for characterizing protein interactions in their cellular context.
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Key Words
- CLEM, correlated light and electron microscopy
- Crosslinking mass spectrometry
- Cryo-electron microscopy
- Cryo-electron tomography
- EPR, electron paramagnetic resonance
- FRET, Forster resonance energy transfer
- ISB, Integrative structural biology
- Integrative structural biology
- ML, machine learning
- MR, molecular replacement
- MSAs, multiple sequence alignments
- MX, macromolecular crystallography
- NMR, nuclear magnetic resonance
- PDB, Protein Data Bank
- Protein docking
- Protein structure prediction
- Quinary interactions
- SAD, single-wavelength anomalous dispersion
- SANS, small angle neutron scattering
- SAXS, small angle X-ray scattering
- X-ray crystallography
- XL-MS, cross-linking mass spectrometry
- cryo-EM SPA, cryo-EM single particle analysis
- cryo-EM, cryo-electron microscopy
- cryo-ET, cryo-electron tomography
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Affiliation(s)
- Samantha J. Ziegler
- Biosciences Center, National Renewable Energy Laboratory, 15013 Denver West Parkway, Golden, CO 80401, USA
| | - Sam J.B. Mallinson
- Biosciences Center, National Renewable Energy Laboratory, 15013 Denver West Parkway, Golden, CO 80401, USA
| | - Peter C. St. John
- Biosciences Center, National Renewable Energy Laboratory, 15013 Denver West Parkway, Golden, CO 80401, USA
| | - Yannick J. Bomble
- Biosciences Center, National Renewable Energy Laboratory, 15013 Denver West Parkway, Golden, CO 80401, USA
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15
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Sinnott M, Malhotra S, Madhusudhan MS, Thalassinos K, Topf M. Combining Information from Crosslinks and Monolinks in the Modeling of Protein Structures. Structure 2020; 28:1061-1070.e3. [DOI: 10.1016/j.str.2020.05.012] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2020] [Revised: 05/08/2020] [Accepted: 05/22/2020] [Indexed: 11/30/2022]
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16
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Gong Z, Ye SX, Tang C. Tightening the Crosslinking Distance Restraints for Better Resolution of Protein Structure and Dynamics. Structure 2020; 28:1160-1167.e3. [PMID: 32763142 DOI: 10.1016/j.str.2020.07.010] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Revised: 07/04/2020] [Accepted: 07/21/2020] [Indexed: 12/11/2022]
Abstract
Chemical crosslinking coupled with mass spectrometry (CXMS) has been increasingly used in structural biology. CXMS distance restraints are usually applied to Cα or Cβ atoms of the crosslinked residues, with upper bounds typically over 20 Å. The incorporation of loose CXMS restraints only marginally improves the resolution of the calculated structures. Here, we present a revised format of CXMS distance restraints, which works by first modifying the crosslinked residue with a rigid extension derived from the crosslinker. With the flexible side chain explicitly represented, the reformatted restraint can be applied to the modification group instead, with an upper bound of 6 Å or less. The short distance restraint can be represented and back-calculated simply with a straight line. The use of tighter restraints not only afford better-resolved structures but also uncover protein dynamics. Together, our approach enables more information extracted from the CXMS data.
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Affiliation(s)
- Zhou Gong
- CAS Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic Molecular Physics, National Center for Magnetic Resonance at Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, Hubei Province 430071, China
| | - Shang-Xiang Ye
- CAS Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic Molecular Physics, National Center for Magnetic Resonance at Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, Hubei Province 430071, China; Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, Hubei Province 430074, China
| | - Chun Tang
- CAS Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic Molecular Physics, National Center for Magnetic Resonance at Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, Hubei Province 430071, China; Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, Hubei Province 430074, China; Beijing National Laboratory for Molecular Sciences, College of Chemistry and Molecular Engineering, and Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China.
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17
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Gong Z, Ye SX, Nie ZF, Tang C. The Conformational Preference of Chemical Cross-linkers Determines the Cross-linking Probability of Reactive Protein Residues. J Phys Chem B 2020; 124:4446-4453. [PMID: 32369371 DOI: 10.1021/acs.jpcb.0c02522] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Chemical cross-linking mass spectrometry (XLMS) is an emerging technique in structural biology. Providing the cross-linked peptides are identified by mass spectrometry with high confidence, a distance restraint can be applied between the two reactive protein residues, with the upper bound corresponding to the maximal span of the cross-linker. However, as the upper bound is typically over 20 Å, cross-link distance restraints are unrestrictive and provide a marginal improvement in protein structural refinement. Here we analyze the experimental cross-links for lysine or acidic residues and show that the distribution of Cβ-Cβ' distances can be described with two overlapping Gaussian species. In addition to the pairwise occurrence probability of the reactive protein residues, we show that the distribution profile of the cross-link distances is determined by the intrinsic conformational propensity of the cross-linker. The cross-linker prefers either a compact or extended conformation and, once attached to a reactive protein residue, predominantly an extended conformation. Consequently, the long-distance Gaussian species occurs at a much higher probability than the short-distance species in the observed cross-links. Together, the probabilistic distribution of the cross-link distance allows the construction of a more restrictive restraint for structural modeling and better use of the XLMS data.
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Affiliation(s)
- Zhou Gong
- CAS Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic Molecular Physics, National Center for Magnetic Resonance at Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, Hubei Province 430071, China
| | - Shang-Xiang Ye
- CAS Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic Molecular Physics, National Center for Magnetic Resonance at Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, Hubei Province 430071, China
| | - Ze-Feng Nie
- CAS Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic Molecular Physics, National Center for Magnetic Resonance at Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, Hubei Province 430071, China
| | - Chun Tang
- CAS Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic Molecular Physics, National Center for Magnetic Resonance at Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, Hubei Province 430071, China
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18
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Chance MR, Farquhar ER, Yang S, Lodowski DT, Kiselar J. Protein Footprinting: Auxiliary Engine to Power the Structural Biology Revolution. J Mol Biol 2020; 432:2973-2984. [PMID: 32088185 PMCID: PMC7245549 DOI: 10.1016/j.jmb.2020.02.011] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Revised: 02/07/2020] [Accepted: 02/10/2020] [Indexed: 12/25/2022]
Abstract
Structural biology is entering an exciting time where many new high-resolution structures of large complexes and membrane proteins are determined regularly. These advances have been driven by over fifteen years of technology advancements, first in macromolecular crystallography, and recently in Cryo-electron microscopy. These structures are allowing detailed questions about functional mechanisms of the structures, and the biology enabled by these structures, to be addressed for the first time. At the same time, mass spectrometry technologies for protein structure analysis, "footprinting" studies, have improved their sensitivity and resolution dramatically and can provide detailed sub-peptide and residue level information for validating structures and interactions or understanding the dynamics of structures in the context of ligand binding or assembly. In this perspective, we review the use of protein footprinting to extend our understanding of macromolecular systems, particularly for systems challenging for analysis by other techniques, such as intrinsically disordered proteins, amyloidogenic proteins, and other proteins/complexes so far recalcitrant to existing methods. We also illustrate how the availability of high-resolution structural information can be a foundation for a suite of hybrid approaches to divine structure-function relationships beyond what individual techniques can deliver.
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Affiliation(s)
- Mark R Chance
- Case Center for Proteomics and Bioinformatics, USA; Case Center for Synchrotron Biosciences, USA; Department of Nutrition, Case Western Reserve University, School of Medicine, 10900 Euclid Ave., Cleveland, OH, 44106, USA.
| | | | - Sichun Yang
- Case Center for Proteomics and Bioinformatics, USA; Department of Nutrition, Case Western Reserve University, School of Medicine, 10900 Euclid Ave., Cleveland, OH, 44106, USA
| | - David T Lodowski
- Case Center for Proteomics and Bioinformatics, USA; Department of Nutrition, Case Western Reserve University, School of Medicine, 10900 Euclid Ave., Cleveland, OH, 44106, USA
| | - Janna Kiselar
- Case Center for Proteomics and Bioinformatics, USA; Department of Nutrition, Case Western Reserve University, School of Medicine, 10900 Euclid Ave., Cleveland, OH, 44106, USA
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19
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Srivastava A, Tiwari SP, Miyashita O, Tama F. Integrative/Hybrid Modeling Approaches for Studying Biomolecules. J Mol Biol 2020; 432:2846-2860. [DOI: 10.1016/j.jmb.2020.01.039] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2019] [Revised: 01/20/2020] [Accepted: 01/24/2020] [Indexed: 12/12/2022]
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20
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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] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
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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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21
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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] [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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22
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Kryshtafovych A, Schwede T, Topf M, Fidelis K, Moult J. Critical assessment of methods of protein structure prediction (CASP)-Round XIII. Proteins 2019; 87:1011-1020. [PMID: 31589781 DOI: 10.1002/prot.25823] [Citation(s) in RCA: 290] [Impact Index Per Article: 58.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2019] [Revised: 09/25/2019] [Accepted: 09/27/2019] [Indexed: 12/24/2022]
Abstract
CASP (critical assessment of structure prediction) assesses the state of the art in modeling protein structure from amino acid sequence. The most recent experiment (CASP13 held in 2018) saw dramatic progress in structure modeling without use of structural templates (historically "ab initio" modeling). Progress was driven by the successful application of deep learning techniques to predict inter-residue distances. In turn, these results drove dramatic improvements in three-dimensional structure accuracy: With the proviso that there are an adequate number of sequences known for the protein family, the new methods essentially solve the long-standing problem of predicting the fold topology of monomeric proteins. Further, the number of sequences required in the alignment has fallen substantially. There is also substantial improvement in the accuracy of template-based models. Other areas-model refinement, accuracy estimation, and the structure of protein assemblies-have again yielded interesting results. CASP13 placed increased emphasis on the use of sparse data together with modeling and chemical crosslinking, SAXS, and NMR all yielded more mature results. This paper summarizes the key outcomes of CASP13. The special issue of PROTEINS contains papers describing the CASP13 assessments in each modeling category and contributions from the participants.
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Affiliation(s)
| | - Torsten Schwede
- Biozentrum & SIB Swiss Institute of Bioinformatics, University of Basel, Basel, Switzerland
| | - Maya Topf
- Institute of Structural and Molecular Biology, Birkbeck College, University of London, London, UK
| | | | - John Moult
- Institute for Bioscience and Biotechnology Research, Rockville, Maryland.,Department of Cell Biology and Molecular Genetics, University of Maryland, College Park, Maryland
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23
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Guzenko D, Lafita A, Monastyrskyy B, Kryshtafovych A, Duarte JM. Assessment of protein assembly prediction in CASP13. Proteins 2019; 87:1190-1199. [PMID: 31374138 DOI: 10.1002/prot.25795] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2019] [Revised: 07/11/2019] [Accepted: 07/27/2019] [Indexed: 01/08/2023]
Abstract
We present the assembly category assessment in the 13th edition of the CASP community-wide experiment. For the second time, protein assemblies constitute an independent assessment category. Compared to the last edition we see a clear uptake in participation, more oligomeric targets released, and consistent, albeit modest, improvement of the predictions quality. Looking at the tertiary structure predictions, we observe that ignoring the oligomeric state of the targets hinders modeling success. We also note that some contact prediction groups successfully predicted homomeric interfacial contacts, though it appears that these predictions were not used for assembly modeling. Homology modeling with sizeable human intervention appears to form the basis of the assembly prediction techniques in this round of CASP. Future developments should see more integrated approaches where subunits are modeled in the context of the assemblies they form.
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Affiliation(s)
- Dmytro Guzenko
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, San Diego Supercomputer Center, University of California, La Jolla, California
| | - Aleix Lafita
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, UK
| | - Bohdan Monastyrskyy
- Protein Structure Prediction Center, Genome and Biomedical Sciences Facilities, University of California, Davis, California, USA
| | - Andriy Kryshtafovych
- Protein Structure Prediction Center, Genome and Biomedical Sciences Facilities, University of California, Davis, California, USA
| | - Jose M Duarte
- Research Collaboratory for Structural Bioinformatics Protein Data Bank, San Diego Supercomputer Center, University of California, La Jolla, California
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