1
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Pala D, Clark DE. Caught between a ROCK and a hard place: current challenges in structure-based drug design. Drug Discov Today 2024; 29:104106. [PMID: 39029868 DOI: 10.1016/j.drudis.2024.104106] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2024] [Revised: 06/27/2024] [Accepted: 07/13/2024] [Indexed: 07/21/2024]
Abstract
The discipline of structure-based drug design (SBDD) is several decades old and it is tempting to think that the proliferation of experimental structures for many drug targets might make computer-aided drug design (CADD) straightforward. However, this is far from true. In this review, we illustrate some of the challenges that CADD scientists face every day in their work, even now. We use Rho-associated protein kinase (ROCK), and public domain structures and data, as an example to illustrate some of the challenges we have experienced during our project targeting this protein. We hope that this will help to prevent unrealistic expectations of what CADD can accomplish and to educate non-CADD scientists regarding the challenges still facing their CADD colleagues.
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Affiliation(s)
- Daniele Pala
- Medicinal Chemistry and Drug Design Technologies Department, Chiesi Farmaceutici S.p.A, Research Center, Largo Belloli 11/a, 43122 Parma, Italy
| | - David E Clark
- Charles River, 6-9 Spire Green Centre, Flex Meadow, Harlow CM19 5TR, UK.
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2
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Ghosh D, Biswas A, Radhakrishna M. Advanced computational approaches to understand protein aggregation. BIOPHYSICS REVIEWS 2024; 5:021302. [PMID: 38681860 PMCID: PMC11045254 DOI: 10.1063/5.0180691] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Accepted: 03/18/2024] [Indexed: 05/01/2024]
Abstract
Protein aggregation is a widespread phenomenon implicated in debilitating diseases like Alzheimer's, Parkinson's, and cataracts, presenting complex hurdles for the field of molecular biology. In this review, we explore the evolving realm of computational methods and bioinformatics tools that have revolutionized our comprehension of protein aggregation. Beginning with a discussion of the multifaceted challenges associated with understanding this process and emphasizing the critical need for precise predictive tools, we highlight how computational techniques have become indispensable for understanding protein aggregation. We focus on molecular simulations, notably molecular dynamics (MD) simulations, spanning from atomistic to coarse-grained levels, which have emerged as pivotal tools in unraveling the complex dynamics governing protein aggregation in diseases such as cataracts, Alzheimer's, and Parkinson's. MD simulations provide microscopic insights into protein interactions and the subtleties of aggregation pathways, with advanced techniques like replica exchange molecular dynamics, Metadynamics (MetaD), and umbrella sampling enhancing our understanding by probing intricate energy landscapes and transition states. We delve into specific applications of MD simulations, elucidating the chaperone mechanism underlying cataract formation using Markov state modeling and the intricate pathways and interactions driving the toxic aggregate formation in Alzheimer's and Parkinson's disease. Transitioning we highlight how computational techniques, including bioinformatics, sequence analysis, structural data, machine learning algorithms, and artificial intelligence have become indispensable for predicting protein aggregation propensity and locating aggregation-prone regions within protein sequences. Throughout our exploration, we underscore the symbiotic relationship between computational approaches and empirical data, which has paved the way for potential therapeutic strategies against protein aggregation-related diseases. In conclusion, this review offers a comprehensive overview of advanced computational methodologies and bioinformatics tools that have catalyzed breakthroughs in unraveling the molecular basis of protein aggregation, with significant implications for clinical interventions, standing at the intersection of computational biology and experimental research.
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Affiliation(s)
- Deepshikha Ghosh
- Department of Biological Sciences and Engineering, Indian Institute of Technology (IIT) Gandhinagar, Palaj, Gujarat 382355, India
| | - Anushka Biswas
- Department of Chemical Engineering, Indian Institute of Technology (IIT) Gandhinagar, Palaj, Gujarat 382355, India
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3
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Stroet M, Setz M, Lee T, Malde AK, van den Bergen G, Sykacek P, Oostenbrink C, Mark AE. On the Validation of Protein Force Fields Based on Structural Criteria. J Phys Chem B 2024; 128:4602-4620. [PMID: 38711373 PMCID: PMC11103706 DOI: 10.1021/acs.jpcb.3c08469] [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: 12/29/2023] [Revised: 04/25/2024] [Accepted: 04/29/2024] [Indexed: 05/08/2024]
Abstract
Molecular dynamics simulations depend critically on the quality of the force field used to describe the interatomic interactions and the extent to which it has been validated for use in a specific application. Using a curated test set of 52 high-resolution structures, 39 derived from X-ray diffraction and 13 solved using NMR, we consider the extent to which different parameter sets of the GROMOS protein force field can be distinguished based on comparing a range of structural criteria, including the number of backbone hydrogen bonds, the number of native hydrogen bonds, polar and nonpolar solvent-accessible surface area, radius of gyration, the prevalence of secondary structure elements, J-coupling constants, nuclear Overhauser effect (NOE) intensities, positional root-mean-square deviations (RMSD), and the distribution of backbone ϕ and ψ dihedral angles. It is shown that while statistically significant differences between the average values of individual metrics could be detected, these were in general small. Furthermore, improvements in agreement in one metric were often offset by loss of agreement in another. The work establishes a framework and test set against which protein force fields can be validated. It also highlights the danger of inferring the relative quality of a given force field based on a small range of structural properties or small number of proteins.
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Affiliation(s)
- Martin Stroet
- The
University of Queensland, St. Lucia, Queensland 4072, Australia
| | - Martina Setz
- Institute
for Molecular Modeling and Simulation, Department of Material Science
and Process Engineering, University of Natural
Resources and Life Sciences, Vienna Muthgasse 18, 1190 Vienna, Austria
| | - Thomas Lee
- The
University of Queensland, St. Lucia, Queensland 4072, Australia
| | - Alpeshkumar K. Malde
- Institute
for Glycomics and School of Environment and Science, Griffith University, Gold Coast, Queensland 4222, Australia
| | | | - Peter Sykacek
- Institute
of Computational Biology, Department of Biotechnology, University of Natural Resources and Life Sciences,
Vienna, Muthgasse 18, 1190 Vienna, Austria
| | - Chris Oostenbrink
- Institute
for Molecular Modeling and Simulation, Department of Material Science
and Process Engineering, University of Natural
Resources and Life Sciences, Vienna Muthgasse 18, 1190 Vienna, Austria
- Christian
Doppler Laboratory for Molecular Informatics in the Biosciences, University of Natural Resources and Life Sciences,
Vienna, Muthgasse 18, 1190 Vienna, Austria
| | - Alan E. Mark
- The
University of Queensland, St. Lucia, Queensland 4072, Australia
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4
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Champion C, Lehner M, Smith AA, Ferrage F, Bolik-Coulon N, Riniker S. Unraveling motion in proteins by combining NMR relaxometry and molecular dynamics simulations: A case study on ubiquitin. J Chem Phys 2024; 160:104105. [PMID: 38465679 DOI: 10.1063/5.0188416] [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: 11/21/2023] [Accepted: 02/20/2024] [Indexed: 03/12/2024] Open
Abstract
Nuclear magnetic resonance (NMR) relaxation experiments shine light onto the dynamics of molecular systems in the picosecond to millisecond timescales. As these methods cannot provide an atomically resolved view of the motion of atoms, functional groups, or domains giving rise to such signals, relaxation techniques have been combined with molecular dynamics (MD) simulations to obtain mechanistic descriptions and gain insights into the functional role of side chain or domain motion. In this work, we present a comparison of five computational methods that permit the joint analysis of MD simulations and NMR relaxation experiments. We discuss their relative strengths and areas of applicability and demonstrate how they may be utilized to interpret the dynamics in MD simulations with the small protein ubiquitin as a test system. We focus on the aliphatic side chains given the rigidity of the backbone of this protein. We find encouraging agreement between experiment, Markov state models built in the χ1/χ2 rotamer space of isoleucine residues, explicit rotamer jump models, and a decomposition of the motion using ROMANCE. These methods allow us to ascribe the dynamics to specific rotamer jumps. Simulations with eight different combinations of force field and water model highlight how the different metrics may be employed to pinpoint force field deficiencies. Furthermore, the presented comparison offers a perspective on the utility of NMR relaxation to serve as validation data for the prediction of kinetics by state-of-the-art biomolecular force fields.
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Affiliation(s)
- Candide Champion
- Department of Chemistry and Applied Biosciences, ETH Zürich, Vladimir-Prelog-Weg 2, 8093 Zürich, Switzerland
| | - Marc Lehner
- Department of Chemistry and Applied Biosciences, ETH Zürich, Vladimir-Prelog-Weg 2, 8093 Zürich, Switzerland
| | - Albert A Smith
- Institute for Medical Physics and Biophysics, Leipzig University, Härtelstrasse 16-18, 04107 Leipzig, Germany
| | - Fabien Ferrage
- Laboratoire des Biomolécules, LBM, Département de Chimie, École normale supérieure, PSL University, Sorbonne Université, CNRS, 75005 Paris, France
| | - Nicolas Bolik-Coulon
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5S 1A8, Canada
- Department of Chemistry, University of Toronto, Toronto, Ontario M5S 3H6, Canada
- Department of Biochemistry, University of Toronto, Toronto, Ontario M5S 3H6, Canada
| | - Sereina Riniker
- Department of Chemistry and Applied Biosciences, ETH Zürich, Vladimir-Prelog-Weg 2, 8093 Zürich, Switzerland
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5
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Coppa C, Bazzoli A, Barkhordari M, Contini A. Accelerated Molecular Dynamics for Peptide Folding: Benchmarking Different Combinations of Force Fields and Explicit Solvent Models. J Chem Inf Model 2023; 63:3030-3042. [PMID: 37163419 DOI: 10.1021/acs.jcim.3c00138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/12/2023]
Abstract
Accelerated molecular dynamics (aMD) protocols were assessed on predicting the secondary structure of eight peptides, of which two are helical, three are β-hairpins, and three are disordered. Protocols consisted of combinations of three force fields (ff99SB, ff14SB, ff19SB) and two explicit solvation models (TIP3P and OPC), and were evaluated in two independent aMD simulations, one starting from an extended conformation, the other starting from a misfolded conformation. The results of these analyses indicate that all three combinations performed well on helical peptides. As for β-hairpins, ff19SB performed well with both solvation methods, with a slight preference for the TIP3P solvation model, even though performance was dependent on both peptide sequence and initial conformation. The ff19SB/OPC combination had the best performance on intrinsically disordered peptides. In general, ff14SB/TIP3P suffered the strongest helical bias.
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Affiliation(s)
- Crescenzo Coppa
- Dipartimento di Scienze Farmaceutiche - Sezione di Chimica Generale e Organica "Alessandro Marchesini", Università degli Studi di Milano, Via Venezian, 21, 20133 Milano, Italy
| | - Andrea Bazzoli
- Dipartimento di Scienze Farmaceutiche - Sezione di Chimica Generale e Organica "Alessandro Marchesini", Università degli Studi di Milano, Via Venezian, 21, 20133 Milano, Italy
| | - Maral Barkhordari
- Dipartimento di Scienze Farmaceutiche - Sezione di Chimica Generale e Organica "Alessandro Marchesini", Università degli Studi di Milano, Via Venezian, 21, 20133 Milano, Italy
| | - Alessandro Contini
- Dipartimento di Scienze Farmaceutiche - Sezione di Chimica Generale e Organica "Alessandro Marchesini", Università degli Studi di Milano, Via Venezian, 21, 20133 Milano, Italy
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6
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Kříž K, Schmidt L, Andersson AT, Walz MM, van der Spoel D. An Imbalance in the Force: The Need for Standardized Benchmarks for Molecular Simulation. J Chem Inf Model 2023; 63:412-431. [PMID: 36630710 PMCID: PMC9875315 DOI: 10.1021/acs.jcim.2c01127] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Indexed: 01/12/2023]
Abstract
Force fields (FFs) for molecular simulation have been under development for more than half a century. As with any predictive model, rigorous testing and comparisons of models critically depends on the availability of standardized data sets and benchmarks. While such benchmarks are rather common in the fields of quantum chemistry, this is not the case for empirical FFs. That is, few benchmarks are reused to evaluate FFs, and development teams rather use their own training and test sets. Here we present an overview of currently available tests and benchmarks for computational chemistry, focusing on organic compounds, including halogens and common ions, as FFs for these are the most common ones. We argue that many of the benchmark data sets from quantum chemistry can in fact be reused for evaluating FFs, but new gas phase data is still needed for compounds containing phosphorus and sulfur in different valence states. In addition, more nonequilibrium interaction energies and forces, as well as molecular properties such as electrostatic potentials around compounds, would be beneficial. For the condensed phases there is a large body of experimental data available, and tools to utilize these data in an automated fashion are under development. If FF developers, as well as researchers in artificial intelligence, would adopt a number of these data sets, it would become easier to compare the relative strengths and weaknesses of different models and to, eventually, restore the balance in the force.
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Affiliation(s)
- Kristian Kříž
- Department
of Cell and Molecular Biology, Uppsala University, Box 596, SE-75124Uppsala, Sweden
| | - Lisa Schmidt
- Faculty
of Biosciences, University of Heidelberg, Heidelberg69117, Germany
| | - Alfred T. Andersson
- Department
of Cell and Molecular Biology, Uppsala University, Box 596, SE-75124Uppsala, Sweden
| | - Marie-Madeleine Walz
- Department
of Cell and Molecular Biology, Uppsala University, Box 596, SE-75124Uppsala, Sweden
| | - David van der Spoel
- Department
of Cell and Molecular Biology, Uppsala University, Box 596, SE-75124Uppsala, Sweden
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7
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D’Amore L, Hahn DF, Dotson DL, Horton JT, Anwar J, Craig I, Fox T, Gobbi A, Lakkaraju SK, Lucas X, Meier K, Mobley DL, Narayanan A, Schindler CE, Swope WC, in ’t Veld PJ, Wagner J, Xue B, Tresadern G. Collaborative Assessment of Molecular Geometries and Energies from the Open Force Field. J Chem Inf Model 2022; 62:6094-6104. [PMID: 36433835 PMCID: PMC9873353 DOI: 10.1021/acs.jcim.2c01185] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
Force fields form the basis for classical molecular simulations, and their accuracy is crucial for the quality of, for instance, protein-ligand binding simulations in drug discovery. The huge diversity of small-molecule chemistry makes it a challenge to build and parameterize a suitable force field. The Open Force Field Initiative is a combined industry and academic consortium developing a state-of-the-art small-molecule force field. In this report, industry members of the consortium worked together to objectively evaluate the performance of the force fields (referred to here as OpenFF) produced by the initiative on a combined public and proprietary dataset of 19,653 relevant molecules selected from their internal research and compound collections. This evaluation was important because it was completely blind; at most partners, none of the molecules or data were used in force field development or testing prior to this work. We compare the Open Force Field "Sage" version 2.0.0 and "Parsley" version 1.3.0 with GAFF-2.11-AM1BCC, OPLS4, and SMIRNOFF99Frosst. We analyzed force-field-optimized geometries and conformer energies compared to reference quantum mechanical data. We show that OPLS4 performs best, and the latest Open Force Field release shows a clear improvement compared to its predecessors. The performance of established force fields such as GAFF-2.11 was generally worse. While OpenFF researchers were involved in building the benchmarking infrastructure used in this work, benchmarking was done entirely in-house within industrial organizations and the resulting assessment is reported here. This work assesses the force field performance using separate benchmarking steps, external datasets, and involving external research groups. This effort may also be unique in terms of the number of different industrial partners involved, with 10 different companies participating in the benchmark efforts.
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Affiliation(s)
- Lorenzo D’Amore
- Computational Chemistry, Janssen R&D, C/ Jarama 75A, 45007 Toledo, Spain
| | - David F. Hahn
- Computational Chemistry, Janssen R&D, Turnhoutseweg 30, Beerse B-2340, Belgium
| | - David L. Dotson
- The Open Force Field Initiative, Open Molecular Software Foundation, Davis, California 95616, USA
| | - Joshua T. Horton
- School of Natural and Environmental Sciences, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
| | - Jamshed Anwar
- Department of Chemistry, Lancaster University, Lancaster LA1 4YW, UK
| | - Ian Craig
- Molecular Modeling & Drug Discovery, BASF SE, 67056 Ludwigshafen, Germany
| | - Thomas Fox
- Medicinal Chemistry, Boehringer Ingelheim Pharma GmbH & Co KG, 88397 Biberach/Riss, Germany
| | - Alberto Gobbi
- Genentech, Inc., 1 DNA Way, South San Francisco, California, 94080, USA
| | | | - Xavier Lucas
- Roche Pharma Research and Early Development, Therapeutic Modalities, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd, Grenzacherstrasse 124, 4070 Basel, Switzerland
| | - Katharina Meier
- Computational Life Science Technology Functions, Crop Science, R&D, Bayer AG, 40789 Monheim, Germany
| | - David L. Mobley
- Departments of Pharmaceutical Sciences and Chemistry, University of California 92617, Irvine, USA
| | - Arjun Narayanan
- Data and Computational Sciences, Vertex Pharmaceuticals, 50 Northern Ave, Boston, MA 02210, USA
| | | | - William C. Swope
- Genentech, Inc., 1 DNA Way, South San Francisco, California, 94080, USA
| | | | - Jeffrey Wagner
- The Open Force Field Initiative, Open Molecular Software Foundation, Davis, California, 95616, USA,Chemistry Department, The University of California at Irvine, Irvine, California, 92617, USA
| | - Bai Xue
- XtalPi Inc. Floor 3, International Biomedical Innovation Park II, No. 2 Hongliu Road, Fubao Community, Fubao Street, Futian District, Shenzhen, Guangdong, 518040 China
| | - Gary Tresadern
- Computational Chemistry, Janssen R&D, Turnhoutseweg 30, Beerse B-2340, Belgium
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8
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Berselli A, Benfenati F, Maragliano L, Alberini G. Multiscale modelling of claudin-based assemblies: a magnifying glass for novel structures of biological interfaces. Comput Struct Biotechnol J 2022; 20:5984-6010. [DOI: 10.1016/j.csbj.2022.10.038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 10/24/2022] [Accepted: 10/24/2022] [Indexed: 11/03/2022] Open
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9
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Polêto MD, Lemkul JA. Integration of Experimental Data and Use of Automated Fitting Methods in Developing Protein Force Fields. Commun Chem 2022; 5:10.1038/s42004-022-00653-z. [PMID: 35382231 PMCID: PMC8979544 DOI: 10.1038/s42004-022-00653-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Accepted: 02/21/2022] [Indexed: 01/27/2023] Open
Abstract
The development of accurate protein force fields has been the cornerstone of molecular simulations for the past 50 years. During this period, many lessons have been learned regarding the use of experimental target data and parameter fitting procedures. Here, we review recent advances in protein force field development. We discuss the recent emergence of polarizable force fields and the role of electronic polarization and areas in which additive force fields fall short. The use of automated fitting methods and the inclusion of additional experimental solution data during parametrization is discussed as a means to highlight possible routes to improve the accuracy of force fields even further.
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Affiliation(s)
- Marcelo D. Polêto
- Department of Biochemistry, Virginia Tech, Blacksburg, VA 24061 United States
| | - Justin A. Lemkul
- Department of Biochemistry, Virginia Tech, Blacksburg, VA 24061 United States
- Center for Drug Discovery, Virginia Tech, Blacksburg, VA 24061 United States
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10
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Conde D, Garrido PF, Calvelo M, Piñeiro Á, Garcia-Fandino R. Molecular Dynamics Simulations of Transmembrane Cyclic Peptide Nanotubes Using Classical Force Fields, Hydrogen Mass Repartitioning, and Hydrogen Isotope Exchange Methods: A Critical Comparison. Int J Mol Sci 2022; 23:ijms23063158. [PMID: 35328578 PMCID: PMC8951607 DOI: 10.3390/ijms23063158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Revised: 03/06/2022] [Accepted: 03/07/2022] [Indexed: 12/04/2022] Open
Abstract
Self-assembled cyclic peptide nanotubes with alternating D- and L-amino acid residues in the sequence of each subunit have attracted a great deal of attention due to their potential for new nanotechnology and biomedical applications, mainly in the field of antimicrobial peptides. Molecular dynamics simulations can be used to characterize these systems with atomic resolution at different time scales, providing information that is difficult to obtain via wet lab experiments. However, the performance of classical force fields typically employed in the simulation of biomolecules has not yet been extensively tested with this kind of highly constrained peptide. Four different classical force fields (AMBER, CHARMM, OPLS, and GROMOS), using a nanotube formed by eight D,L-α-cyclic peptides inserted into a lipid bilayer as a model system, were employed here to fill this gap. Significant differences in the pseudo-cylindrical cavities formed by the nanotubes were observed, the most important being the diameter of the nanopores, the number and location of confined water molecules, and the density distribution of the solvent molecules. Furthermore, several modifications were performed on GROMOS54a7, aiming to explore acceleration strategies of the MD simulations. The hydrogen mass repartitioning (HMR) and hydrogen isotope exchange (HIE) methods were tested to slow down the fastest degrees of freedom. These approaches allowed a significant increase in the time step employed in the equation of the motion integration algorithm, from 2 fs up to 5–7 fs, with no serious changes in the structural and dynamical properties of the nanopores. Subtle differences with respect to the simulations with the unmodified force fields were observed in the concerted movements of the cyclic peptides, as well as in the lifetime of several H-bonds. All together, these results are expected to contribute to better understanding of the behavior of self-assembled cyclic peptide nanotubes, as well as to support the methods tested to speed up general MD simulations; additionally, they do provide a number of quantitative descriptors that are expected to be used as a reference to design new experiments intended to validate and complement computational studies of antimicrobial cyclic peptides.
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Affiliation(s)
- Daniel Conde
- Center for Research in Biological Chemistry and Molecular Materials, Departamento de Química Orgánica, Universidade de Santiago de Compostela, Campus Vida s/n, 15782 Santiago de Compostela, Spain; (D.C.); (M.C.)
- Departamento de Física Aplicada, Facultade de Física, Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain;
| | - Pablo F. Garrido
- Departamento de Física Aplicada, Facultade de Física, Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain;
| | - Martín Calvelo
- Center for Research in Biological Chemistry and Molecular Materials, Departamento de Química Orgánica, Universidade de Santiago de Compostela, Campus Vida s/n, 15782 Santiago de Compostela, Spain; (D.C.); (M.C.)
- Departament de Química Inorgánica i Orgànica and Institut de Química Teòrica i Computacional (IQTCUB), Universitat de Barcelona, 08028 Barcelona, Spain
| | - Ángel Piñeiro
- Departamento de Física Aplicada, Facultade de Física, Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain;
- Correspondence: (Á.P.); (R.G.-F.)
| | - Rebeca Garcia-Fandino
- Center for Research in Biological Chemistry and Molecular Materials, Departamento de Química Orgánica, Universidade de Santiago de Compostela, Campus Vida s/n, 15782 Santiago de Compostela, Spain; (D.C.); (M.C.)
- CIQUP, Centro de Investigação em Química, Departamento de Química e Bioquímica, Faculdade de Ciências, Universidade do Porto, 4196-007 Porto, Portugal
- Correspondence: (Á.P.); (R.G.-F.)
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11
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Wang L, O'Mara ML. Effect of the Force Field on Molecular Dynamics Simulations of the Multidrug Efflux Protein P-Glycoprotein. J Chem Theory Comput 2021; 17:6491-6508. [PMID: 34506133 DOI: 10.1021/acs.jctc.1c00414] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Molecular dynamics (MD) simulations have been used extensively to study P-glycoprotein (P-gp), a flexible multidrug transporter that is a key player in the development of multidrug resistance to chemotherapeutics. A substantial body of literature has grown from simulation studies that have employed various simulation conditions and parameters, including AMBER, CHARMM, OPLS, GROMOS, and coarse-grained force fields, drawing conclusions from simulations spanning hundreds of nanoseconds. Each force field is typically parametrized and validated on different data and observables, usually of small molecules and peptides; there have been few comparisons of force field performance on large protein-membrane systems. Here we compare the conformational ensembles of P-gp embedded in a POPC/cholesterol bilayer generated over 500 ns of replicate simulation with five force fields from popular biomolecular families: AMBER 99SB-ILDN, CHARMM 36, OPLS-AA/L, GROMOS 54A7, and MARTINI. We find considerable differences among the ensembles with little conformational overlap, although they correspond to similar extents to structural data obtained from electron paramagnetic resonance and cross-linking studies. Moreover, each trajectory was still sampling new conformations at a high rate after 500 ns of simulation, suggesting the need for more sampling. This work highlights the need to consider known limitations of the force field used (e.g., biases toward certain secondary structures) and the simulation itself (e.g., whether sufficient sampling has been achieved) when interpreting accumulated results of simulation studies of P-gp and other transport proteins.
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Affiliation(s)
- Lily Wang
- Research School of Chemistry, College of Science, Australian National University, Canberra, ACT 2601, Australia
| | - Megan L O'Mara
- Research School of Chemistry, College of Science, Australian National University, Canberra, ACT 2601, Australia
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12
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Fas BA, Maiani E, Sora V, Kumar M, Mashkoor M, Lambrughi M, Tiberti M, Papaleo E. The conformational and mutational landscape of the ubiquitin-like marker for autophagosome formation in cancer. Autophagy 2021; 17:2818-2841. [PMID: 33302793 PMCID: PMC8525936 DOI: 10.1080/15548627.2020.1847443] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2019] [Revised: 10/28/2020] [Accepted: 11/03/2020] [Indexed: 02/06/2023] Open
Abstract
Macroautophagy/autophagy is a cellular process to recycle damaged cellular components, and its modulation can be exploited for disease treatments. A key autophagy player is the ubiquitin-like protein MAP1LC3B/LC3B. Mutations and changes in MAP1LC3B expression occur in cancer samples. However, the investigation of the effects of these mutations on MAP1LC3B protein structure is still missing. Despite many LC3B structures that have been solved, a comprehensive study, including dynamics, has not yet been undertaken. To address this knowledge gap, we assessed nine physical models for biomolecular simulations for their capabilities to describe the structural ensemble of MAP1LC3B. With the resulting MAP1LC3B structural ensembles, we characterized the impact of 26 missense mutations from pan-cancer studies with different approaches, and we experimentally validated our prediction for six variants using cellular assays. Our findings shed light on damaging or neutral mutations in MAP1LC3B, providing an atlas of its modifications in cancer. In particular, P32Q mutation was found detrimental for protein stability with a propensity to aggregation. In a broader context, our framework can be applied to assess the pathogenicity of protein mutations or to prioritize variants for experimental studies, allowing to comprehensively account for different aspects that mutational events alter in terms of protein structure and function.Abbreviations: ATG: autophagy-related; Cα: alpha carbon; CG: coarse-grained; CHARMM: Chemistry at Harvard macromolecular mechanics; CONAN: contact analysis; FUNDC1: FUN14 domain containing 1; FYCO1: FYVE and coiled-coil domain containing 1; GABARAP: GABA type A receptor-associated protein; GROMACS: Groningen machine for chemical simulations; HP: hydrophobic pocket; LIR: LC3 interacting region; MAP1LC3B/LC3B microtubule associated protein 1 light chain 3 B; MD: molecular dynamics; OPTN: optineurin; OSF: open software foundation; PE: phosphatidylethanolamine, PLEKHM1: pleckstrin homology domain-containing family M 1; PSN: protein structure network; PTM: post-translational modification; SA: structural alphabet; SLiM: short linear motif; SQSTM1/p62: sequestosome 1; WT: wild-type.
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Affiliation(s)
- Burcu Aykac Fas
- Computational Biology Laboratory, Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Emiliano Maiani
- Computational Biology Laboratory, Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Valentina Sora
- Computational Biology Laboratory, Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Mukesh Kumar
- Computational Biology Laboratory, Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Maliha Mashkoor
- Computational Biology Laboratory, Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Matteo Lambrughi
- Computational Biology Laboratory, Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Matteo Tiberti
- Computational Biology Laboratory, Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Elena Papaleo
- Computational Biology Laboratory, Danish Cancer Society Research Center, Copenhagen, Denmark
- Translational Disease Systems Biology, Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Protein Research University of Copenhagen, Copenhagen, Denmark
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13
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Pearce R, Zhang Y. Toward the solution of the protein structure prediction problem. J Biol Chem 2021; 297:100870. [PMID: 34119522 PMCID: PMC8254035 DOI: 10.1016/j.jbc.2021.100870] [Citation(s) in RCA: 60] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Revised: 06/07/2021] [Accepted: 06/09/2021] [Indexed: 11/20/2022] Open
Abstract
Since Anfinsen demonstrated that the information encoded in a protein's amino acid sequence determines its structure in 1973, solving the protein structure prediction problem has been the Holy Grail of structural biology. The goal of protein structure prediction approaches is to utilize computational modeling to determine the spatial location of every atom in a protein molecule starting from only its amino acid sequence. Depending on whether homologous structures can be found in the Protein Data Bank (PDB), structure prediction methods have been historically categorized as template-based modeling (TBM) or template-free modeling (FM) approaches. Until recently, TBM has been the most reliable approach to predicting protein structures, and in the absence of reliable templates, the modeling accuracy sharply declines. Nevertheless, the results of the most recent community-wide assessment of protein structure prediction experiment (CASP14) have demonstrated that the protein structure prediction problem can be largely solved through the use of end-to-end deep machine learning techniques, where correct folds could be built for nearly all single-domain proteins without using the PDB templates. Critically, the model quality exhibited little correlation with the quality of available template structures, as well as the number of sequence homologs detected for a given target protein. Thus, the implementation of deep-learning techniques has essentially broken through the 50-year-old modeling border between TBM and FM approaches and has made the success of high-resolution structure prediction significantly less dependent on template availability in the PDB library.
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Affiliation(s)
- Robin Pearce
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA
| | - Yang Zhang
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA; Department of Biological Chemistry, University of Michigan, Ann Arbor, Michigan, USA.
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14
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Xu Y, Huang J. Validating the CHARMM36m protein force field with LJ-PME reveals altered hydrogen bonding dynamics under elevated pressures. Commun Chem 2021; 4:99. [PMID: 36697521 PMCID: PMC9814493 DOI: 10.1038/s42004-021-00537-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Accepted: 06/08/2021] [Indexed: 01/28/2023] Open
Abstract
The pressure-temperature phase diagram is important to our understanding of the physics of biomolecules. Compared to studies on temperature effects, studies of the pressure dependence of protein dynamic are rather limited. Molecular dynamics (MD) simulations with fine-tuned force fields (FFs) offer a powerful tool to explore the influence of thermodynamic conditions on proteins. Here we evaluate the transferability of the CHARMM36m (C36m) protein force field at varied pressures compared with NMR data using ubiquitin as a model protein. The pressure dependences of J couplings for hydrogen bonds and order parameters for internal motion are in good agreement with experiment. We demonstrate that the C36m FF combined with the Lennard-Jones particle-mesh Ewald (LJ-PME) method is suitable for simulations in a wide range of temperature and pressure. As the ubiquitin remains stable up to 2500 bar, we identify the mobility and stability of different hydrogen bonds in response to pressure. Based on those results, C36m is expected to be applied to more proteins in the future to further investigate protein dynamics under elevated pressures.
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Affiliation(s)
- You Xu
- grid.494629.40000 0004 8008 9315Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang China ,Westlake AI Therapeutics Lab, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang China ,grid.494629.40000 0004 8008 9315Institute of Biology, Westlake Institute for Advanced Study, Hangzhou, Zhejiang China
| | - Jing Huang
- grid.494629.40000 0004 8008 9315Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, Zhejiang China ,Westlake AI Therapeutics Lab, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang China ,grid.494629.40000 0004 8008 9315Institute of Biology, Westlake Institute for Advanced Study, Hangzhou, Zhejiang China
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15
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Sinelnikova A, Spoel DVD. NMR refinement and peptide folding using the GROMACS software. JOURNAL OF BIOMOLECULAR NMR 2021; 75:143-149. [PMID: 33778935 PMCID: PMC8131288 DOI: 10.1007/s10858-021-00363-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Accepted: 03/18/2021] [Indexed: 05/11/2023]
Abstract
Nuclear magnetic resonance spectroscopy is used routinely for studying the three-dimensional structures and dynamics of proteins and nucleic acids. Structure determination is usually done by adding restraints based upon NMR data to a classical energy function and performing restrained molecular simulations. Here we report on the implementation of a script to extract NMR restraints from a NMR-STAR file and export it to the GROMACS software. With this package it is possible to model distance restraints, dihedral restraints and orientation restraints. The output from the script is validated by performing simulations with and without restraints, including the ab initio refinement of one peptide.
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Affiliation(s)
- Anna Sinelnikova
- Department of Physics and Astronomy, Uppsala University, Uppsala, Sweden
| | - David van der Spoel
- Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden
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16
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Kozak F, Kurzbach D. How to assess the structural dynamics of transcription factors by integrating sparse NMR and EPR constraints with molecular dynamics simulations. Comput Struct Biotechnol J 2021; 19:2097-2105. [PMID: 33995905 PMCID: PMC8085671 DOI: 10.1016/j.csbj.2021.04.020] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Revised: 04/07/2021] [Accepted: 04/07/2021] [Indexed: 12/12/2022] Open
Abstract
We review recent advances in modeling structural ensembles of transcription factors from nuclear magnetic resonance (NMR) and electron paramagnetic resonance (EPR) spectroscopic data, integrated with molecular dynamics (MD) simulations. We focus on approaches that confirm computed conformational ensembles by sparse constraints obtained from magnetic resonance. This combination enables the deduction of functional and structural protein models even if nuclear Overhauser effects (NOEs) are too scarce for conventional structure determination. We highlight recent insights into the folding-upon-DNA binding transitions of intrinsically disordered transcription factors that could be assessed using such integrative approaches.
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Affiliation(s)
- Fanny Kozak
- University Vienna, Faculty of Chemistry, Institute of Biological Chemistry, Waehringer Str. 38, 1090 Vienna, Austria
| | - Dennis Kurzbach
- University Vienna, Faculty of Chemistry, Institute of Biological Chemistry, Waehringer Str. 38, 1090 Vienna, Austria
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17
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Reinknecht C, Riga A, Rivera J, Snyder DA. Patterns in Protein Flexibility: A Comparison of NMR "Ensembles", MD Trajectories, and Crystallographic B-Factors. Molecules 2021; 26:molecules26051484. [PMID: 33803249 PMCID: PMC7967184 DOI: 10.3390/molecules26051484] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Revised: 02/18/2021] [Accepted: 02/28/2021] [Indexed: 11/16/2022] Open
Abstract
Proteins are molecular machines requiring flexibility to function. Crystallographic B-factors and Molecular Dynamics (MD) simulations both provide insights into protein flexibility on an atomic scale. Nuclear Magnetic Resonance (NMR) lacks a universally accepted analog of the B-factor. However, a lack of convergence in atomic coordinates in an NMR-based structure calculation also suggests atomic mobility. This paper describes a pattern in the coordinate uncertainties of backbone heavy atoms in NMR-derived structural “ensembles” first noted in the development of FindCore2 (previously called Expanded FindCore: DA Snyder, J Grullon, YJ Huang, R Tejero, GT Montelione, Proteins: Structure, Function, and Bioinformatics 82 (S2), 219–230) and demonstrates that this pattern exists in coordinate variances across MD trajectories but not in crystallographic B-factors. This either suggests that MD trajectories and NMR “ensembles” capture motional behavior of peptide bond units not captured by B-factors or indicates a deficiency common to force fields used in both NMR and MD calculations.
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18
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Wang W. Recent advances in atomic molecular dynamics simulation of intrinsically disordered proteins. Phys Chem Chem Phys 2021; 23:777-784. [PMID: 33355572 DOI: 10.1039/d0cp05818a] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Intrinsically disordered proteins (IDPs) play important roles in cellular functions. The inherent structural heterogeneity of IDPs makes the high-resolution experimental characterization of IDPs extremely difficult. Molecular dynamics (MD) simulation could provide the atomic-level description of the structural and dynamic properties of IDPs. This perspective reviews the recent progress in atomic MD simulation studies of IDPs, including the development of force fields and sampling methods, as well as applications in IDP-involved protein-protein interactions. The employment of large-scale simulations and advanced sampling techniques allows more accurate estimation of the thermodynamics and kinetics of IDP-mediated protein interactions, and the holistic landscape of the binding process of IDPs is emerging.
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Affiliation(s)
- Wenning Wang
- Department of Chemistry, Multiscale Research Institute of Complex Systems and Institute of Biomedical Sciences, Fudan University, Shanghai 200438, China.
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19
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Gopal SM, Wingbermühle S, Schnatwinkel J, Juber S, Herrmann C, Schäfer LV. Conformational Preferences of an Intrinsically Disordered Protein Domain: A Case Study for Modern Force Fields. J Phys Chem B 2021; 125:24-35. [PMID: 33382616 DOI: 10.1021/acs.jpcb.0c08702] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Molecular simulations of intrinsically disordered proteins (IDPs) are challenging because they require sampling a very large number of relevant conformations, corresponding to a multitude of shallow minima in a flat free energy landscape. However, in the presence of a binding partner, the free energy landscape of an IDP can be dominated by few deep minima. This characteristic imposes high demands on the accuracy of the force field used to describe the molecular interactions. Here, as a model system for an IDP that is unstructured in solution but folds upon binding to a structured interaction partner, the transactivation domain of c-Myb was studied both in the unbound (free) form and when bound to the KIX domain. Six modern biomolecular force fields were systematically tested and compared in terms of their ability to describe the structural ensemble of the IDP. The protein force field/water model combinations included in this study are AMBER ff99SB-disp with its corresponding water model that was derived from TIP4P-D, CHARMM36m with TIP3P, ff15ipq with SPC/Eb, ff99SB*-ILDNP with TIP3P and TIP4P-D, and FB15 with TIP3P-FB water. Comparing the results from REST2-enhanced sampling simulations with experimental CD spectra and secondary chemical shifts reveals that the ff99SB-disp force field can realistically capture the broad and mildly helical structural ensemble of free c-Myb. The structural ensembles yielded by CHARMM36m, ff99SB*-ILDNP together with TIP4P-D water, and FB15 are also mildly helical; however, each of these force fields can be assigned a specific subset of c-Myb residues for which the simulations could not reproduce the experimental secondary chemical shifts. In addition, microsecond-timescale MD simulations of the KIX/c-Myb complex show that most force fields used preserve a stable helix fold of c-Myb in the complex. Still, all force fields predict a KIX/c-Myb complex interface that differs slightly from the structures provided by NMR because several NOE-derived distances between KIX and c-Myb were exceeded in the simulations. Taken together, the ff99SB-disp force field in the first place but also CHARMM36m, ff99SB*-ILDNP together with TIP4P-D water, and FB15 can be suitable choices for future simulation studies of the coupled folding and binding mechanism of the KIX/c-Myb complex and potentially also other IDPs.
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Affiliation(s)
- Srinivasa M Gopal
- Theoretical Chemistry, Faculty of Chemistry and Biochemistry, Ruhr University Bochum, D-44780 Bochum, Germany
| | - Sebastian Wingbermühle
- Theoretical Chemistry, Faculty of Chemistry and Biochemistry, Ruhr University Bochum, D-44780 Bochum, Germany
| | - Jan Schnatwinkel
- Physical Chemistry I, Faculty of Chemistry and Biochemistry, Ruhr University Bochum, D-44780 Bochum, Germany
| | - Selina Juber
- Theoretical Chemistry, Faculty of Chemistry and Biochemistry, Ruhr University Bochum, D-44780 Bochum, Germany
| | - Christian Herrmann
- Physical Chemistry I, Faculty of Chemistry and Biochemistry, Ruhr University Bochum, D-44780 Bochum, Germany
| | - Lars V Schäfer
- Theoretical Chemistry, Faculty of Chemistry and Biochemistry, Ruhr University Bochum, D-44780 Bochum, Germany
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20
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Lewis-Atwell T, Townsend PA, Grayson MN. Comparisons of different force fields in conformational analysis and searching of organic molecules: A review. Tetrahedron 2021. [DOI: 10.1016/j.tet.2020.131865] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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21
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Seffernick JT, Lindert S. Hybrid methods for combined experimental and computational determination of protein structure. J Chem Phys 2020; 153:240901. [PMID: 33380110 PMCID: PMC7773420 DOI: 10.1063/5.0026025] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2020] [Accepted: 11/10/2020] [Indexed: 02/04/2023] Open
Abstract
Knowledge of protein structure is paramount to the understanding of biological function, developing new therapeutics, and making detailed mechanistic hypotheses. Therefore, methods to accurately elucidate three-dimensional structures of proteins are in high demand. While there are a few experimental techniques that can routinely provide high-resolution structures, such as x-ray crystallography, nuclear magnetic resonance (NMR), and cryo-EM, which have been developed to determine the structures of proteins, these techniques each have shortcomings and thus cannot be used in all cases. However, additionally, a large number of experimental techniques that provide some structural information, but not enough to assign atomic positions with high certainty have been developed. These methods offer sparse experimental data, which can also be noisy and inaccurate in some instances. In cases where it is not possible to determine the structure of a protein experimentally, computational structure prediction methods can be used as an alternative. Although computational methods can be performed without any experimental data in a large number of studies, inclusion of sparse experimental data into these prediction methods has yielded significant improvement. In this Perspective, we cover many of the successes of integrative modeling, computational modeling with experimental data, specifically for protein folding, protein-protein docking, and molecular dynamics simulations. We describe methods that incorporate sparse data from cryo-EM, NMR, mass spectrometry, electron paramagnetic resonance, small-angle x-ray scattering, Förster resonance energy transfer, and genetic sequence covariation. Finally, we highlight some of the major challenges in the field as well as possible future directions.
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Affiliation(s)
- Justin T. Seffernick
- Department of Chemistry and Biochemistry, Ohio State University, Columbus, Ohio 43210, USA
| | - Steffen Lindert
- Department of Chemistry and Biochemistry, Ohio State University, Columbus, Ohio 43210, USA
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22
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Lim VT, Hahn DF, Tresadern G, Bayly CI, Mobley DL. Benchmark assessment of molecular geometries and energies from small molecule force fields. F1000Res 2020; 9:Chem Inf Sci-1390. [PMID: 33604023 PMCID: PMC7863993 DOI: 10.12688/f1000research.27141.1] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/18/2020] [Indexed: 12/22/2022] Open
Abstract
Background: Force fields are used in a wide variety of contexts for classical molecular simulation, including studies on protein-ligand binding, membrane permeation, and thermophysical property prediction. The quality of these studies relies on the quality of the force fields used to represent the systems. Methods: Focusing on small molecules of fewer than 50 heavy atoms, our aim in this work is to compare nine force fields: GAFF, GAFF2, MMFF94, MMFF94S, OPLS3e, SMIRNOFF99Frosst, and the Open Force Field Parsley, versions 1.0, 1.1, and 1.2. On a dataset comprising 22,675 molecular structures of 3,271 molecules, we analyzed force field-optimized geometries and conformer energies compared to reference quantum mechanical (QM) data. Results: We show that while OPLS3e performs best, the latest Open Force Field Parsley release is approaching a comparable level of accuracy in reproducing QM geometries and energetics for this set of molecules. Meanwhile, the performance of established force fields such as MMFF94S and GAFF2 is generally somewhat worse. We also find that the series of recent Open Force Field versions provide significant increases in accuracy. Conclusions: This study provides an extensive test of the performance of different molecular mechanics force fields on a diverse molecule set, and highlights two (OPLS3e and OpenFF 1.2) that perform better than the others tested on the present comparison. Our molecule set and results are available for other researchers to use in testing.
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Affiliation(s)
- Victoria T. Lim
- Department of Chemistry, University of California, Irvine, CA, 92697, USA
| | - David F. Hahn
- Computational Chemistry, Janssen Research & Development, Beerse, B-2340, Belgium
| | - Gary Tresadern
- Computational Chemistry, Janssen Research & Development, Beerse, B-2340, Belgium
| | | | - David L. Mobley
- Department of Chemistry, University of California, Irvine, CA, 92697, USA
- Department of Pharmaceutical Sciences, University of California, Irvine, CA, 92697, USA
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23
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Kumar S, Seth D, Deshpande PA. Molecular dynamics simulations identify the regions of compromised thermostability in SazCA. Proteins 2020; 89:375-388. [PMID: 33146427 DOI: 10.1002/prot.26022] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2020] [Revised: 09/14/2020] [Accepted: 10/16/2020] [Indexed: 11/09/2022]
Abstract
The present study examined the structure and dynamics of the most active and thermostable carbonic anhydrase, SazCA, probed using molecular dynamics simulations. The molecular system was described by widely used biological force-fields (AMBER, CHARMM22, CHARMM36, and OPLS-AA) in conjunction with TIP3P water model. The comparison of molecular dynamics simulation results suggested AMBER to be a suitable choice to describe the structure and dynamics of SazCA. In addition to this, we also addressed the effect of temperature on the stability of SazCA. We performed molecular dynamics simulations at 313, 333, 353, 373, and 393 K to study the relationship between thermostability and flexibility in SazCA. The amino acid residues VAL98, ASN99, GLY100, LYS101, GLU145, and HIS207 were identified as the most flexible residues from root-mean-square fluctuations. The salt bridge analysis showed that ion-pairs ASP113-LYS81, ASP115-LYS81, ASP115-LYS114, GLU144-LYS143, and GLU144-LYS206, were responsible for the compromised thermal stability of SazCA.
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Affiliation(s)
- Shashi Kumar
- Quantum and Molecular Engineering Laboratory, Department of Chemical Engineering, Indian Institute of Technology Kharagpur, Kharagpur, India
| | - Deepak Seth
- Quantum and Molecular Engineering Laboratory, Department of Chemical Engineering, Indian Institute of Technology Kharagpur, Kharagpur, India
| | - Parag Arvind Deshpande
- Quantum and Molecular Engineering Laboratory, Department of Chemical Engineering, Indian Institute of Technology Kharagpur, Kharagpur, India
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24
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Yan S, Peck JM, Ilgu M, Nilsen-Hamilton M, Lamm MH. Sampling Performance of Multiple Independent Molecular Dynamics Simulations of an RNA Aptamer. ACS OMEGA 2020; 5:20187-20201. [PMID: 32832772 PMCID: PMC7439393 DOI: 10.1021/acsomega.0c01867] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/22/2020] [Accepted: 07/22/2020] [Indexed: 06/11/2023]
Abstract
Using multiple independent simulations instead of one long simulation has been shown to improve the sampling performance attained with the molecular dynamics (MD) simulation method. However, it is generally not known how long each independent simulation should be, how many independent simulations should be used, or to what extent either of these factors affects the overall sampling performance achieved for a given system. The goal of the present study was to assess the sampling performance of multiple independent MD simulations, where each independent simulation begins from a different initial molecular conformation. For this purpose, we used an RNA aptamer that is 25 nucleotides long as a case study. The initial conformations of the aptamer are derived from six de novo predicted 3D structures. Each of the six de novo predicted structures is energy minimized in solution and equilibrated with MD simulations at high temperature. Ten conformations from these six high-temperature equilibration runs are selected as initial conformations for further simulations at ambient temperature. In total, we conducted 60 independent MD simulations, each with a duration of 100 ns, to study the conformation and dynamics of the aptamer. For each group of 10 independent simulations that originated from a particular de novo predicted structure, we evaluated the potential energy distribution of the RNA and used recurrence quantification analysis to examine the sampling of RNA conformational transitions. To assess the impact of starting from different de novo predicted structures, we computed the density of structure projection on principal components to compare the regions sampled by the different groups of ten independent simulations. The recurrence rate and dependence of initial conformation among the groups were also compared. We stress the necessity of using different initial configurations as simulation starting points by showing long simulations from different initial structures suffer from being trapped in different states. Finally, we summarized the sampling efficiency for the complete set of 60 independent simulations and determined regions of under-sampling on the potential energy landscape. The results suggest that conducting multiple independent simulations using a diverse set of de novo predicted structures is a promising approach to achieve sufficient sampling. This approach avoids undesirable outcomes, such as the problem of the RNA aptamer being trapped in a local minimum. For others wishing to conduct multiple independent simulations, the analysis protocol presented in this study is a guide for examining overall sampling and determining if more simulations are necessary for sufficient sampling.
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Affiliation(s)
- Shuting Yan
- Department
of Chemical and Biological Engineering, Iowa State University, Ames, Iowa 50011, United States
| | - Jason M. Peck
- Department
of Chemical and Biological Engineering, Iowa State University, Ames, Iowa 50011, United States
| | - Muslum Ilgu
- Roy
J Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, Iowa 50011, United States
- Aptalogic
Inc., Ames, Iowa 50014, United States
- Department
of Biological Sciences, Middle East Technical
University, Ankara, Ankara 06800, Turkey
| | - Marit Nilsen-Hamilton
- Roy
J Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, Iowa 50011, United States
- Aptalogic
Inc., Ames, Iowa 50014, United States
| | - Monica H. Lamm
- Department
of Chemical and Biological Engineering, Iowa State University, Ames, Iowa 50011, United States
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25
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Batys P, Morga M, Bonarek P, Sammalkorpi M. pH-Induced Changes in Polypeptide Conformation: Force-Field Comparison with Experimental Validation. J Phys Chem B 2020; 124:2961-2972. [PMID: 32182068 PMCID: PMC7590956 DOI: 10.1021/acs.jpcb.0c01475] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2020] [Indexed: 12/17/2022]
Abstract
Microsecond-long all-atom molecular dynamics (MD) simulations, circular dichroism, laser Doppler velocimetry, and dynamic light-scattering techniques have been used to investigate pH-induced changes in the secondary structure, charge, and conformation of poly l-lysine (PLL) and poly l-glutamic acid (PGA). The employed combination of the experimental methods reveals for both PLL and PGA a narrow pH range at which they are charged enough to form stable colloidal suspensions, maintaining their α-helix content above 60%; an elevated charge state of the peptides required for colloidal stability promotes the peptide solvation as a random coil. To obtain a more microscopic view on the conformations and to verify the modeling performance, peptide secondary structure and conformations rising in MD simulations are also examined using three different force fields, i.e., OPLS-AA, CHARMM27, and AMBER99SB*-ILDNP. Ramachandran plots reveal that in the examined setup the α-helix content is systematically overestimated in CHARMM27, while OPLS-AA overestimates the β-sheet fraction at lower ionization degrees. At high ionization degrees, the OPLS-AA force-field-predicted secondary structure fractions match the experimentally measured distribution most closely. However, the pH-induced changes in PLL and PGA secondary structure are reasonably captured only by the AMBER99SB*-ILDNP force field, with the exception of the fully charged PGA in which the α-helix content is overestimated. The comparison to simulations results shows that the examined force fields involve significant deviations in their predictions for charged homopolypeptides. The detailed mapping of secondary structure dependency on pH for the polypeptides, especially finding the stable colloidal α-helical regime for both examined peptides, has significant potential for practical applications of the charged homopolypeptides. The findings raise attention especially to the pH fine tuning as an underappreciated control factor in surface modification and self-assembly.
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Affiliation(s)
- Piotr Batys
- Jerzy
Haber Institute of Catalysis and Surface Chemistry, Polish Academy of Sciences, Niezapominajek 8, PL-30239 Krakow, Poland
| | - Maria Morga
- Jerzy
Haber Institute of Catalysis and Surface Chemistry, Polish Academy of Sciences, Niezapominajek 8, PL-30239 Krakow, Poland
| | - Piotr Bonarek
- Department
of Physical Biochemistry, Faculty of Biochemistry, Biophysics and
Biotechnology, Jagiellonian University, Krakow, Poland
| | - Maria Sammalkorpi
- Department of Chemistry and Materials Science and Department of Bioproducts and Biosystems, Aalto University, P.O. Box 16100, 00076 Aalto, Finland
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Piana S, Robustelli P, Tan D, Chen S, Shaw DE. Development of a Force Field for the Simulation of Single-Chain Proteins and Protein-Protein Complexes. J Chem Theory Comput 2020; 16:2494-2507. [PMID: 31914313 DOI: 10.1021/acs.jctc.9b00251] [Citation(s) in RCA: 83] [Impact Index Per Article: 20.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
The accuracy of atomistic physics-based force fields for the simulation of biological macromolecules has typically been benchmarked experimentally using biophysical data from simple, often single-chain systems. In the case of proteins, the careful refinement of force field parameters associated with torsion-angle potentials and the use of improved water models have enabled a great deal of progress toward the highly accurate simulation of such monomeric systems in both folded and, more recently, disordered states. In living organisms, however, proteins constantly interact with other macromolecules, such as proteins and nucleic acids, and these interactions are often essential for proper biological function. Here, we show that state-of-the-art force fields tuned to provide an accurate description of both ordered and disordered proteins can be limited in their ability to accurately describe protein-protein complexes. This observation prompted us to perform an extensive reparameterization of one variant of the Amber protein force field. Our objective involved refitting not only the parameters associated with torsion-angle potentials but also the parameters used to model nonbonded interactions, the specification of which is expected to be central to the accurate description of multicomponent systems. The resulting force field, which we call DES-Amber, allows for more accurate simulations of protein-protein complexes, while still providing a state-of-the-art description of both ordered and disordered single-chain proteins. Despite the improvements, calculated protein-protein association free energies still appear to deviate substantially from experiment, a result suggesting that more fundamental changes to the force field, such as the explicit treatment of polarization effects, may simultaneously further improve the modeling of single-chain proteins and protein-protein complexes.
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Affiliation(s)
- Stefano Piana
- D. E. Shaw Research, New York, New York 10036, United States
| | - Paul Robustelli
- D. E. Shaw Research, New York, New York 10036, United States
| | - Dazhi Tan
- D. E. Shaw Research, New York, New York 10036, United States
| | - Songela Chen
- D. E. Shaw Research, New York, New York 10036, United States
| | - David E Shaw
- D. E. Shaw Research, New York, New York 10036, United States.,Department of Biochemistry and Molecular Biophysics, Columbia University, New York, New York 10032, United States
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27
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Ezerski JC, Zhang P, Jennings NC, Waxham MN, Cheung MS. Molecular Dynamics Ensemble Refinement of Intrinsically Disordered Peptides According to Deconvoluted Spectra from Circular Dichroism. Biophys J 2020; 118:1665-1678. [PMID: 32145192 PMCID: PMC7136346 DOI: 10.1016/j.bpj.2020.02.015] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2019] [Revised: 02/07/2020] [Accepted: 02/18/2020] [Indexed: 02/08/2023] Open
Abstract
We have developed a computational method of atomistically refining the structural ensemble of intrinsically disordered peptides (IDPs) facilitated by experimental measurements using circular dichroism spectroscopy (CD). A major challenge surrounding this approach stems from the deconvolution of experimental CD spectra into secondary structure features of the IDP ensemble. Currently available algorithms for CD deconvolution were designed to analyze the spectra of proteins with stable secondary structures. Herein, our work aims to minimize any bias from the peptide deconvolution analysis by implementing a non-negative linear least-squares fitting algorithm in conjunction with a CD reference data set that contains soluble and denatured proteins (SDP48). The non-negative linear least-squares method yields the best results for deconvolution of proteins with higher disordered content than currently available methods, according to a validation analysis of a set of protein spectra with Protein Data Bank entries. We subsequently used this analysis to deconvolute our experimental CD data to refine our computational model of the peptide secondary structure ensemble produced by all-atom molecular dynamics simulations with implicit solvent. We applied this approach to determine the ensemble structures of a set of short IDPs, that mimic the calmodulin binding domain of calcium/calmodulin-dependent protein kinase II and its 1-amino-acid and 3-amino-acid mutants. Our study offers a, to our knowledge, novel way to solve the ensemble secondary structures of IDPs in solution, which is important to advance the understanding of their roles in regulating signaling pathways through the formation of complexes with multiple partners.
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Affiliation(s)
- Jacob C Ezerski
- Department of Physics, University of Houston, Houston, Texas
| | - Pengzhi Zhang
- Department of Physics, University of Houston, Houston, Texas
| | | | - M Neal Waxham
- Department of Neurobiology and Anatomy, University of Texas, Health Science Center at Houston, Houston, Texas
| | - Margaret S Cheung
- Department of Physics, University of Houston, Houston, Texas; Center for Theoretical Biological Physics, Rice University, Houston, Texas.
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28
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Yu L, Li DW, Brüschweiler R. Balanced Amino-Acid-Specific Molecular Dynamics Force Field for the Realistic Simulation of Both Folded and Disordered Proteins. J Chem Theory Comput 2019; 16:1311-1318. [DOI: 10.1021/acs.jctc.9b01062] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
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29
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Common Secondary and Tertiary Structural Features of Aptamer-Ligand Interaction Shared by RNA Aptamers with Different Primary Sequences. Molecules 2019; 24:molecules24244535. [PMID: 31835789 PMCID: PMC6943582 DOI: 10.3390/molecules24244535] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2019] [Revised: 11/30/2019] [Accepted: 12/05/2019] [Indexed: 11/16/2022] Open
Abstract
Aptamer selection can yield many oligonucleotides with different sequences and affinities for the target molecule. Here, we have combined computational and experimental approaches to understand if aptamers with different sequences but the same molecular target share structural and dynamical features. NEO1A, with a known NMR-solved structure, displays a flexible loop that interacts differently with individual aminoglycosides, its ligand affinities and specificities are responsive to ionic strength, and it possesses an adenosine in the loop that is critical for high-affinity ligand binding. NEO2A was obtained from the same selection and, although they are only 43% identical in overall sequence, NEO1A and NEO2A share similar loop sequences. Experimental analysis by 1D NMR and 2-aminopurine reporters combined with molecular dynamics modeling revealed similar structural and dynamical characteristics in both aptamers. These results are consistent with the hypothesis that the target ligand drives aptamer structure and also selects relevant dynamical characteristics for high-affinity aptamer-ligand interaction. Furthermore, they suggest that it might be possible to “migrate” structural and dynamical features between aptamer group members with different primary sequences but with the same target ligand.
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30
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Liu H, Song D, Zhang Y, Yang S, Luo R, Chen HF. Extensive tests and evaluation of the CHARMM36IDPSFF force field for intrinsically disordered proteins and folded proteins. Phys Chem Chem Phys 2019; 21:21918-21931. [PMID: 31552948 DOI: 10.1039/c9cp03434j] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Intrinsically disordered proteins (IDPs) have received increasing attention in recent studies due to their structural heterogeneity and critical biological functions. To fully understand the structural properties and determine accurate ensembles of IDPs, molecular dynamics (MD) simulation was widely used to sample diverse conformations and reveal the structural dynamics. However, the classical state-of-the-art force fields perform well for folded proteins while being unsatisfactory for the simulations of disordered proteins reported in many previous studies. Thus, improved force fields were developed to precisely describe both folded proteins and disordered proteins. Preliminary tests show that our newly developed CHARMM36IDPSFF (C36IDPSFF) force field can well reproduce the experimental observables of several disordered proteins, but more tests on different types of proteins are needed to further evaluate the performance of C36IDPSFF. Here, we extensively simulate short peptides, disordered proteins, and fast-folding proteins as well as folded proteins, and compare the simulated results with the experimental observables. The simulation results show that C36IDPSFF could substantially reproduce the experimental observables for most of the tested proteins but some limitations are also found in the radius of gyration of large disordered proteins and the stability of fast-folding proteins. This force field will facilitate large scale studies of protein structural dynamics and functions using MD simulations.
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Affiliation(s)
- Hao Liu
- State Key Laboratory of Microbial Metabolism, Department of Bioinformatics and Biostatistics, SJTU-Yale Joint Center for Biostatistics, National Experimental Teaching Center for Life Sciences and Biotechnology, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, China.
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31
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Çınaroğlu SS, Timuçin E. Comprehensive evaluation of the MM-GBSA method on bromodomain-inhibitor sets. Brief Bioinform 2019; 21:2112-2125. [DOI: 10.1093/bib/bbz143] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2019] [Revised: 10/01/2019] [Accepted: 10/17/2019] [Indexed: 12/11/2022] Open
Abstract
Abstract
MM-PB/GBSA methods represent a higher-level scoring theory than docking. This study reports an extensive testing of different MM-GBSA scoring schemes on two bromodomain (BRD) datasets. The first set is composed of 24 BRPF1 complexes, and the second one is a nonredundant set constructed from the PDBbind and composed of 28 diverse BRD complexes. A variety of MM-GBSA schemes were analyzed to evaluate the performance of four protocols with different numbers of minimization and MD steps, 10 different force fields and three different water models. Results showed that neither additional MD steps nor unfixing the receptor atoms improved scoring or ranking power. On the contrary, our results underscore the advantage of fixing receptor atoms or limiting the number of MD steps not only for a reduction in the computational costs but also for boosting the prediction accuracy. Among Amber force fields tested, ff14SB and its derivatives rather than ff94 or polarized force fields provided the most accurate scoring and ranking results. The TIP3P water model yielded the highest scoring and ranking power compared to the others. Posing power was further evaluated for the BRPF1 set. A slightly better posing power for the protocol which uses both minimization and MD steps with a fixed receptor than the one which uses only minimization with a fully flexible receptor-ligand system was observed. Overall, this study provides insights into the usage of the MM-GBSA methods for screening of BRD inhibitors, substantiating the benefits of shorter protocols and latest force fields and maintaining the crystal waters for accuracy.
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Affiliation(s)
| | - Emel Timuçin
- Department of Biostatistics and Medical Informatics, School of Medicine, Acıbadem Mehmet Ali Aydınlar University, İstanbul, 34752, Turkey
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32
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Krupa P, Quoc Huy PD, Li MS. Properties of monomeric Aβ42 probed by different sampling methods and force fields: Role of energy components. J Chem Phys 2019. [DOI: 10.1063/1.5093184] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Affiliation(s)
- Pawel Krupa
- Institute of Physics Polish Academy of Sciences, Al. Lotników 32/46, 02-668 Warsaw, Poland
| | - Pham Dinh Quoc Huy
- Institute of Physics Polish Academy of Sciences, Al. Lotników 32/46, 02-668 Warsaw, Poland
| | - Mai Suan Li
- Institute of Physics Polish Academy of Sciences, Al. Lotników 32/46, 02-668 Warsaw, Poland
- Institute for Computational Science and Technology, SBI Building, Quang Trung Software City, Tan Chanh Hiep Ward, District 12, Ho Chi Minh City, Vietnam
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33
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Investigating targets for neuropharmacological intervention by molecular dynamics simulations. Biochem Soc Trans 2019; 47:909-918. [PMID: 31085614 DOI: 10.1042/bst20190048] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2019] [Revised: 04/11/2019] [Accepted: 04/23/2019] [Indexed: 01/09/2023]
Abstract
Medical research has identified over 500 brain disorders. Among these, there are still only very few neuropathologies whose causes are fully understood and, consequently, very few drugs whose mechanism of action is known. No FDA drug has been identified for major neurodegenerative diseases, such as Alzheimer's and Parkinson's. We still lack effective treatments and strategies for modulating progression or even early neurodegenerative disease onset diagnostic tools. A great support toward the highly needed identification of neuroactive drugs comes from computer simulation methods and, in particular, from molecular dynamics (MD). This provides insight into structure-function relationship of a target and predicts structure, dynamics and energetics of ligand/target complexes under biologically relevant conditions like temperature and physiological saline concentration. Here, we present examples of the predictive power of MD for neuroactive ligands/target complexes. This brief survey from our own research shows the usefulness of partnerships between academia and industry, and from joint efforts between experimental and theoretical groups.
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34
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Célerse F, Lagardère L, Derat E, Piquemal JP. Massively Parallel Implementation of Steered Molecular Dynamics in Tinker-HP: Comparisons of Polarizable and Non-Polarizable Simulations of Realistic Systems. J Chem Theory Comput 2019; 15:3694-3709. [DOI: 10.1021/acs.jctc.9b00199] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Frédéric Célerse
- Laboratoire de Chimie Théorique, UMR 7616 CNRS, Sorbonne Université, 75005 Paris, France
- Institut Parisien de Chimie Moléculaire, UMR 8232 CNRS, Sorbonne Université, 75005 Paris, France
| | - Louis Lagardère
- Institut des Sciences du Calcul et des Données, Sorbonne Université, 75005 Paris, France
- Institut Parisien de Chimie Physique et Théorique, FR 2622 CNRS, Sorbonne Université, 75005 Paris, France
- Laboratoire de Chimie théorique, UMR 7616 CNRS, Sorbonne Université, 75005 Paris, France
| | - Etienne Derat
- Institut Parisien de Chimie Moléculaire, UMR 8232 CNRS, Sorbonne Université, 75005 Paris, France
| | - Jean-Philip Piquemal
- Laboratoire de Chimie Théorique, UMR 7616 CNRS, Sorbonne Université, 75005 Paris, France
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas 78712, United States
- Institut Universitaire de France, 75005 Paris, France
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35
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Klijn ME, Vormittag P, Bluthardt N, Hubbuch J. High-throughput computational pipeline for 3-D structure preparation and in silico protein surface property screening: A case study on HBcAg dimer structures. Int J Pharm 2019; 563:337-346. [PMID: 30935914 DOI: 10.1016/j.ijpharm.2019.03.057] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2018] [Revised: 03/26/2019] [Accepted: 03/27/2019] [Indexed: 02/06/2023]
Abstract
Knowledge-based experimental design can aid biopharmaceutical high-throughput screening (HTS) experiments needed to identify critical manufacturability parameters. Prior knowledge can be obtained via computational methods such as protein property extraction from 3-D protein structures. This study presents a high-throughput 3-D structure preparation and refinement pipeline that supports structure screenings with an automated and data-dependent workflow. As a case study, three chimeric virus-like particle (VLP) building blocks, hepatitis B core antigen (HBcAg) dimers, were constructed. Molecular dynamics (MD) refinement quality, speed, stability, and correlation to zeta potential data was evaluated using different MD simulation settings. Settings included 2 force fields (YASARA2 and AMBER03) and 2 pKa computation methods (YASARA and H++). MD simulations contained a data-dependent termination via identification of a 2 ns Window of Stability, which was also used for robust descriptor extraction. MD simulation with YASARA2, independent of pKa computation method, was found to be most stable and computationally efficient. These settings resulted in a fast refinement (6.6-37.5 h), a good structure quality (-1.17--1.13) and a strong linear dependence between dimer surface charge and complete chimeric HBcAg VLP zeta potential. These results indicate the computational pipeline's applicability for early-stage candidate assessment and design optimization of HTS manufacturability or formulability experiments.
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Affiliation(s)
- Marieke E Klijn
- Institute of Engineering in Life Sciences, Section IV: Biomolecular Separation Engineering, Karlsruhe Institute of Technology (KIT), Fritz-Haber-Weg 2, 76131 Karlsruhe, Baden-Wuerttemberg, Germany
| | - Philipp Vormittag
- Institute of Engineering in Life Sciences, Section IV: Biomolecular Separation Engineering, Karlsruhe Institute of Technology (KIT), Fritz-Haber-Weg 2, 76131 Karlsruhe, Baden-Wuerttemberg, Germany
| | - Nicolai Bluthardt
- Institute of Engineering in Life Sciences, Section IV: Biomolecular Separation Engineering, Karlsruhe Institute of Technology (KIT), Fritz-Haber-Weg 2, 76131 Karlsruhe, Baden-Wuerttemberg, Germany
| | - Jürgen Hubbuch
- Institute of Engineering in Life Sciences, Section IV: Biomolecular Separation Engineering, Karlsruhe Institute of Technology (KIT), Fritz-Haber-Weg 2, 76131 Karlsruhe, Baden-Wuerttemberg, Germany.
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36
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Dasetty S, Barrows JK, Sarupria S. Adsorption of amino acids on graphene: assessment of current force fields. SOFT MATTER 2019; 15:2359-2372. [PMID: 30789189 DOI: 10.1039/c8sm02621a] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/27/2023]
Abstract
We compare the free energies of adsorption (ΔAads) and the structural preferences of amino acids on graphene obtained using the non-polarizable force fields-Amberff99SB-ILDN/TIP3P, CHARMM36/modified-TIP3P, OPLS-AA/M/TIP3P, and Amber03w/TIP4P/2005. The amino acid-graphene interactions are favorable irrespective of the force field. While the magnitudes of ΔAads differ between the force fields, the relative free energy of adsorption across amino acids is similar for the studied force fields. ΔAads positively correlates with amino acid-graphene and negatively correlates with graphene-water interaction energies. Using a combination of principal component analysis and density-based clustering technique, we grouped the structures observed in the graphene adsorbed state. The resulting population of clusters, and the conformation in each cluster indicate that the structures of the amino acid in the graphene adsorbed state vary across force fields. The differences in the conformations of amino acids are more severe in the graphene adsorbed state compared to the bulk state for all the force fields. Our findings suggest that the force fields studied will give qualitatively consistent relative strength of adsorption across proteins but different structural preferences in the graphene adsorbed state.
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Affiliation(s)
- Siva Dasetty
- Department of Chemical & Biomolecular Engineering, Clemson University, Clemson, SC 29634, USA.
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37
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Molecular simulation of peptides coming of age: Accurate prediction of folding, dynamics and structures. Arch Biochem Biophys 2019; 664:76-88. [DOI: 10.1016/j.abb.2019.01.033] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2018] [Revised: 01/23/2019] [Accepted: 01/28/2019] [Indexed: 12/24/2022]
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38
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Jiang Z, Remsing RC, Rego NB, Patel AJ. Characterizing Solvent Density Fluctuations in Dynamical Observation Volumes. J Phys Chem B 2019; 123:1650-1661. [PMID: 30682885 DOI: 10.1021/acs.jpcb.8b11423] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Hydrophobic effects drive diverse aqueous assemblies, such as micelle formation or protein folding, wherein the solvent plays an important role. Consequently, characterizing the free energetics of solvent density fluctuations can lead to important insights into these processes. Although techniques such as the indirect umbrella sampling (INDUS) method can be used to characterize solvent fluctuations in static observation volumes of various sizes and shapes, characterizing how the solvent mediates inherently dynamic processes, such as self-assembly or conformational change, remains a challenge. In this work, we generalize the INDUS method to facilitate the enhanced sampling of solvent fluctuations in dynamical observation volumes, whose positions and shapes can evolve. We illustrate the usefulness of this generalization by characterizing water density fluctuations in dynamical volumes pertaining to the hydration of flexible solutes, the assembly of small hydrophobes, and conformational transitions in a model peptide. We also use the method to probe the dynamics of hard spheres.
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Affiliation(s)
| | - Richard C Remsing
- Institute for Computational Molecular Science , Temple University , Philadelphia , Pennsylvania 19122 , United States
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39
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Modestia SM, Malta de Sá M, Auger E, Trossini GHG, Krieger JE, Rangel-Yagui CDO. Biased Agonist TRV027 Determinants in AT1R by Molecular Dynamics Simulations. J Chem Inf Model 2019; 59:797-808. [PMID: 30668103 DOI: 10.1021/acs.jcim.8b00628] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
Functional selectivity is a phenomenon observed in G protein-coupled receptors in which intermediate active-state conformations are stabilized by mutations or ligand binding, resulting in different sets of signaling pathways. Peptides capable of selectively activating β-arrestin, known as biased agonists, have already been characterized in vivo and could correspond to a new therapeutic approach for treatment of cardiovascular diseases. Despite the potential of biased agonism, the mechanism involved in selective signaling remains unclear. In this work, molecular dynamics simulations were employed to compare the conformational profile of the angiotensin II type 1 receptor (AT1R) crystal bound to angiotensin II, bound to the biased ligand TRV027, and in the apo form. Our results show that both ligands induce changes near the NPxxY motif in transmembrane domain 7 that are related to receptor activation. However, the biased ligand does not cause the rotamer toggle alternative positioning and displays an exclusive hydrogen-bonding pattern. Our work sheds light on the biased agonism mechanism and will help in the future design of novel biased agonists for AT1R.
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Affiliation(s)
- Silvestre Massimo Modestia
- Department of Biochemical and Pharmaceutical Technology, School of Pharmaceutical Sciences , University of São Paulo , Av. Prof. Lineu Prestes 580 , 05508-900 São Paulo - SP , Brazil
| | - Matheus Malta de Sá
- Laboratory of Genetics and Molecular Cardiology, Heart Institute , University of São Paulo Medical School , Av. Dr. Enéas de Carvalho Aguiar 44 , 05403-900 São Paulo - SP , Brazil
| | - Eric Auger
- Laboratory of Genetics and Molecular Cardiology, Heart Institute , University of São Paulo Medical School , Av. Dr. Enéas de Carvalho Aguiar 44 , 05403-900 São Paulo - SP , Brazil
| | - Gustavo Henrique Goulart Trossini
- Department of Pharmacy, School of Pharmaceutical Sciences , University of São Paulo , Av. Prof. Lineu Prestes 580 , 05508-900 São Paulo - SP , Brazil
| | - José Eduardo Krieger
- Laboratory of Genetics and Molecular Cardiology, Heart Institute , University of São Paulo Medical School , Av. Dr. Enéas de Carvalho Aguiar 44 , 05403-900 São Paulo - SP , Brazil
| | - Carlota de Oliveira Rangel-Yagui
- Department of Biochemical and Pharmaceutical Technology, School of Pharmaceutical Sciences , University of São Paulo , Av. Prof. Lineu Prestes 580 , 05508-900 São Paulo - SP , Brazil
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40
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Friedman R. Simulations of Biomolecules in Electrolyte Solutions. ADVANCED THEORY AND SIMULATIONS 2019. [DOI: 10.1002/adts.201800163] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Affiliation(s)
- Ran Friedman
- Department of Chemistry and Biomedical SciencesLinnæus UniversityKalmar SE‐391 82 Sweden
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41
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Bonhenry D, Schober R, Schmidt T, Waldherr L, Ettrich RH, Schindl R. Mechanistic insights into the Orai channel by molecular dynamics simulations. Semin Cell Dev Biol 2019; 94:50-58. [PMID: 30639326 DOI: 10.1016/j.semcdb.2019.01.002] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2018] [Revised: 12/12/2018] [Accepted: 01/05/2019] [Indexed: 10/27/2022]
Abstract
Highly Ca2+ selective channels trigger a large variety of cellular signaling processes in both excitable and non-excitable cells. Among these channels, the Orai channel is unique in its activation mechanism and its structure. It mediates Ca2+ influx into the cytosol with an extremely small unitary conductance over longer time-scales, ranging from minutes up to several hours. Its activation is regulated by the Ca2+ content of the endoplasmic reticulum (ER). Depletion of luminal [Ca2+]ER is sensed by the STIM1 single transmembrane protein that directly binds and gates the Orai1 channel. Orai mediated Ca2+ influx increases cytosolic Ca2+ from 100 nM up to low micromolar range close to the pore and thereby forms Ca2+ microdomains. Hence, these features of the Orai channel can trigger long-term signaling processes without affecting the overall Ca2+ content of a single living cell. Here we focus on the architecture and dynamic conformational changes within the Orai channel. This review summarizes current achievements of molecular dynamics simulations in combination with live cell recordings to address gating and permeation of the Orai channel with molecular precision.
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Affiliation(s)
- Daniel Bonhenry
- Center for Nanobiology and Structural Biology, Institute of Microbiology, Academy of Sciences of the Czech Republic, Nové Hrady CZ-373 33, Czech Republic.
| | - Romana Schober
- Institute for Biophysics, Johannes Kepler University Linz, A-4040 Linz, Austria
| | - Tony Schmidt
- Gottfried Schatz Research Center, Medical University of Graz, A-8010 Graz, Austria
| | - Linda Waldherr
- Gottfried Schatz Research Center, Medical University of Graz, A-8010 Graz, Austria
| | - Rüdiger H Ettrich
- Center for Nanobiology and Structural Biology, Institute of Microbiology, Academy of Sciences of the Czech Republic, Nové Hrady CZ-373 33, Czech Republic; College of Biomedical Sciences, Larkin University, Miami, FL 33169, United States
| | - Rainer Schindl
- Gottfried Schatz Research Center, Medical University of Graz, A-8010 Graz, Austria.
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42
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Lambrughi M, Tiberti M, Allega MF, Sora V, Nygaard M, Toth A, Salamanca Viloria J, Bignon E, Papaleo E. Analyzing Biomolecular Ensembles. Methods Mol Biol 2019; 2022:415-451. [PMID: 31396914 DOI: 10.1007/978-1-4939-9608-7_18] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Several techniques are available to generate conformational ensembles of proteins and other biomolecules either experimentally or computationally. These methods produce a large amount of data that need to be analyzed to identify structure-dynamics-function relationship. In this chapter, we will cover different tools to unveil the information hidden in conformational ensemble data and to guide toward the rationalization of the data. We included routinely used approaches such as dimensionality reduction, as well as new methods inspired by high-order statistics and graph theory.
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Affiliation(s)
- Matteo Lambrughi
- Computational Biology Laboratory, Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Matteo Tiberti
- Computational Biology Laboratory, Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Maria Francesca Allega
- Computational Biology Laboratory, Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Valentina Sora
- Computational Biology Laboratory, Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Mads Nygaard
- Computational Biology Laboratory, Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Agota Toth
- Computational Biology Laboratory, Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Juan Salamanca Viloria
- Computational Biology Laboratory, Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Emmanuelle Bignon
- Computational Biology Laboratory, Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Elena Papaleo
- Computational Biology Laboratory, Danish Cancer Society Research Center, Copenhagen, Denmark.
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Buckle AM, Borg NA. Integrating Experiment and Theory to Understand TCR-pMHC Dynamics. Front Immunol 2018; 9:2898. [PMID: 30581442 PMCID: PMC6293202 DOI: 10.3389/fimmu.2018.02898] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2018] [Accepted: 11/26/2018] [Indexed: 11/13/2022] Open
Abstract
The conformational dynamism of proteins is well established. Rather than having a single structure, proteins are more accurately described as a conformational ensemble that exists across a rugged energy landscape, where different conformational sub-states interconvert. The interaction between αβ T cell receptors (TCR) and cognate peptide-MHC (pMHC) is no exception, and is a dynamic process that involves substantial conformational change. This review focuses on technological advances that have begun to establish the role of conformational dynamics and dynamic allostery in TCR recognition of the pMHC and the early stages of signaling. We discuss how the marriage of molecular dynamics (MD) simulations with experimental techniques provides us with new ways to dissect and interpret the process of TCR ligation. Notably, application of simulation techniques lags behind other fields, but is predicted to make substantial contributions. Finally, we highlight integrated approaches that are being used to shed light on some of the key outstanding questions in the early events leading to TCR signaling.
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Affiliation(s)
- Ashley M Buckle
- Infection and Immunity Program, Monash Biomedicine Discovery Institute and Department of Biochemistry and Molecular Biology, Monash University, Clayton, VIC, Australia
| | - Natalie A Borg
- Infection and Immunity Program, Monash Biomedicine Discovery Institute and Department of Biochemistry and Molecular Biology, Monash University, Clayton, VIC, Australia
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44
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Carballo-Pacheco M, Ismail AE, Strodel B. On the Applicability of Force Fields To Study the Aggregation of Amyloidogenic Peptides Using Molecular Dynamics Simulations. J Chem Theory Comput 2018; 14:6063-6075. [PMID: 30336669 DOI: 10.1021/acs.jctc.8b00579] [Citation(s) in RCA: 60] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Molecular dynamics simulations play an essential role in understanding biomolecular processes such as protein aggregation at temporal and spatial resolutions which are not attainable by experimental methods. For a correct modeling of protein aggregation, force fields must accurately represent molecular interactions. Here, we study the effect of five different force fields on the oligomer formation of Alzheimer's Aβ16-22 peptide and two of its mutants: Aβ16-22(F19V,F20V), which does not form fibrils, and Aβ16-22(F19L) which forms fibrils faster than the wild type. We observe that while oligomer formation kinetics depends strongly on the force field, structural properties, such as the most relevant protein-protein contacts, are similar between them. The oligomer formation kinetics obtained with different force fields differ more from each other than the kinetics between aggregating and nonaggregating peptides simulated with a single force field. We discuss the difficulties in comparing atomistic simulations of amyloid oligomer formation with experimental observables.
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Affiliation(s)
- Martín Carballo-Pacheco
- Institute of Complex Systems: Structural Biochemistry (ICS-6) , Forschungszentrum Jülich GmbH , 52425 Jülich , Germany.,AICES Graduate School , RWTH Aachen University , Schinkelstraße 2 , 52062 Aachen , Germany
| | - Ahmed E Ismail
- AICES Graduate School , RWTH Aachen University , Schinkelstraße 2 , 52062 Aachen , Germany.,Aachener Verfahrenstechnik, Faculty of Mechanical Engineering , RWTH Aachen University , Schinkelstraße 2 , 52062 Aachen , Germany
| | - Birgit Strodel
- Institute of Complex Systems: Structural Biochemistry (ICS-6) , Forschungszentrum Jülich GmbH , 52425 Jülich , Germany.,Institute of Theoretical and Computational Chemistry , Heinrich Heine University Düsseldorf , Universitätstrasse 1 , 40225 Düsseldorf , Germany
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45
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Ho KC, Hamelberg D. Combinatorial Coarse-Graining of Molecular Dynamics Simulations for Detecting Relationships between Local Configurations and Overall Conformations. J Chem Theory Comput 2018; 14:6026-6034. [DOI: 10.1021/acs.jctc.8b00333] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Affiliation(s)
- Ka Chun Ho
- Department of Chemistry and the Center for Diagnostics & Therapeutics, Georgia State University, Atlanta, Georgia 30302-3965, United States
| | - Donald Hamelberg
- Department of Chemistry and the Center for Diagnostics & Therapeutics, Georgia State University, Atlanta, Georgia 30302-3965, United States
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46
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Thompson HN, Thompson CE, Andrade Caceres R, Dardenne LE, Netz PA, Stassen H. Prion protein conversion triggered by acidic condition: a molecular dynamics study through different force fields. J Comput Chem 2018; 39:2000-2011. [DOI: 10.1002/jcc.25380] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2018] [Revised: 05/15/2018] [Accepted: 05/26/2018] [Indexed: 11/06/2022]
Affiliation(s)
- Helen Nathalia Thompson
- Departamento de Físico-Química, Instituto de Química; Universidade Federal do Rio Grande do Sul; 91501-970 Porto Alegre Rio Grande do Sul Brazil
| | - Claudia Elizabeth Thompson
- Departamento de Farmacociências; Universidade Federal de Ciências da Saúde de Porto Alegre; 90050-170 Porto Alegre Rio Grande do Sul Brazil
| | - Rafael Andrade Caceres
- Departamento de Farmacociências; Universidade Federal de Ciências da Saúde de Porto Alegre; 90050-170 Porto Alegre Rio Grande do Sul Brazil
| | | | - Paulo Augusto Netz
- Departamento de Físico-Química, Instituto de Química; Universidade Federal do Rio Grande do Sul; 91501-970 Porto Alegre Rio Grande do Sul Brazil
| | - Hubert Stassen
- Departamento de Físico-Química, Instituto de Química; Universidade Federal do Rio Grande do Sul; 91501-970 Porto Alegre Rio Grande do Sul Brazil
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47
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Fox SJ, Lakshminarayanan R, Beuerman RW, Li J, Verma CS. Conformational Transitions of Melittin between Aqueous and Lipid Phases: Comparison of Simulations with Experiments. J Phys Chem B 2018; 122:8698-8705. [DOI: 10.1021/acs.jpcb.8b06781] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Stephen J. Fox
- Bioinformatics Institute (A*Star), 30 Biopolis Street, #07-01 Matrix, Singapore 138671, Singapore
| | - Rajamani Lakshminarayanan
- Eye ACP, Duke-NUS Graduate Medical School, Singapore 169857, Singapore
- Anti-Infectives Research Group, Singapore Eye Research Institute, Singapore 168751, Singapore
| | - Roger W. Beuerman
- Anti-Infectives Research Group, Singapore Eye Research Institute, Singapore 168751, Singapore
| | - Jianguo Li
- Bioinformatics Institute (A*Star), 30 Biopolis Street, #07-01 Matrix, Singapore 138671, Singapore
- Eye ACP, Duke-NUS Graduate Medical School, Singapore 169857, Singapore
- Anti-Infectives Research Group, Singapore Eye Research Institute, Singapore 168751, Singapore
| | - Chandra S. Verma
- Bioinformatics Institute (A*Star), 30 Biopolis Street, #07-01 Matrix, Singapore 138671, Singapore
- Department of Biological Sciences, National University of Singapore, 16 Science Drive 4, Singapore 117558, Singapore
- School of Biological Sciences, Nanyang Technological University, 60 Nanyang Drive, 4 Singapore 637551, Singapore
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48
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Bashardanesh Z, van der Spoel D. Impact of Dispersion Coefficient on Simulations of Proteins and Organic Liquids. J Phys Chem B 2018; 122:8018-8027. [DOI: 10.1021/acs.jpcb.8b05770] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Affiliation(s)
- Zahedeh Bashardanesh
- Uppsala Center for Computational Chemistry, Department of Cell and Molecular Biology, Uppsala University, Husargatan 3, P.O. Box 596, SE-75124 Uppsala, Sweden
| | - David van der Spoel
- Uppsala Center for Computational Chemistry, Department of Cell and Molecular Biology, Uppsala University, Husargatan 3, P.O. Box 596, SE-75124 Uppsala, Sweden
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49
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Liu H, Song D, Lu H, Luo R, Chen HF. Intrinsically disordered protein-specific force field CHARMM36IDPSFF. Chem Biol Drug Des 2018; 92:1722-1735. [DOI: 10.1111/cbdd.13342] [Citation(s) in RCA: 44] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2018] [Revised: 04/26/2018] [Accepted: 04/26/2018] [Indexed: 12/25/2022]
Affiliation(s)
- Hao Liu
- State Key Laboratory of Microbial Metabolism; Department of Bioinformatics and Biostatistics; SJTU-Yale Joint Center for Biostatistics; National Experimental Teaching Center for Life Sciences and Biotechnology; School of Life Sciences and Biotechnology; Shanghai Jiao Tong University; Shanghai China
| | - Dong Song
- State Key Laboratory of Microbial Metabolism; Department of Bioinformatics and Biostatistics; SJTU-Yale Joint Center for Biostatistics; National Experimental Teaching Center for Life Sciences and Biotechnology; School of Life Sciences and Biotechnology; Shanghai Jiao Tong University; Shanghai China
| | - Hui Lu
- State Key Laboratory of Microbial Metabolism; Department of Bioinformatics and Biostatistics; SJTU-Yale Joint Center for Biostatistics; National Experimental Teaching Center for Life Sciences and Biotechnology; School of Life Sciences and Biotechnology; Shanghai Jiao Tong University; Shanghai China
| | - Ray Luo
- Departments of Molecular Biology and Biochemistry, Chemical Engineering and Materials Science, Biomedical Engineering; University of California; Irvine California
| | - Hai-Feng Chen
- State Key Laboratory of Microbial Metabolism; Department of Bioinformatics and Biostatistics; SJTU-Yale Joint Center for Biostatistics; National Experimental Teaching Center for Life Sciences and Biotechnology; School of Life Sciences and Biotechnology; Shanghai Jiao Tong University; Shanghai China
- Shanghai Center for Bioinformation Technology; Shanghai China
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50
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Molecular dynamics and ligand docking of a hinge region variant of South African HIV-1 subtype C protease. J Mol Graph Model 2018; 82:1-11. [DOI: 10.1016/j.jmgm.2018.03.006] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2017] [Revised: 02/08/2018] [Accepted: 03/25/2018] [Indexed: 11/21/2022]
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