Sampling of Protein Conformational Space Using Hybrid Simulations: A Critical Assessment of Recent Methods
Recent years have seen several hybrid simulation methods for exploring the conformational space of proteins and their complexes or assemblies. These methods often combine fast analytical approaches with computationally expensive full atomic molecular dynamics (MD) simulations with the goal of rapidl...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-02-01
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| Series: | Frontiers in Molecular Biosciences |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fmolb.2022.832847/full |
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| author | Burak T. Kaynak James M. Krieger Balint Dudas Balint Dudas Balint Dudas Zakaria L. Dahmani Mauricio G. S. Costa Erika Balog Ana Ligia Scott Pemra Doruker David Perahia Ivet Bahar |
| author_facet | Burak T. Kaynak James M. Krieger Balint Dudas Balint Dudas Balint Dudas Zakaria L. Dahmani Mauricio G. S. Costa Erika Balog Ana Ligia Scott Pemra Doruker David Perahia Ivet Bahar |
| author_sort | Burak T. Kaynak |
| collection | DOAJ |
| description | Recent years have seen several hybrid simulation methods for exploring the conformational space of proteins and their complexes or assemblies. These methods often combine fast analytical approaches with computationally expensive full atomic molecular dynamics (MD) simulations with the goal of rapidly sampling large and cooperative conformational changes at full atomic resolution. We present here a systematic comparison of the utility and limits of four such hybrid methods that have been introduced in recent years: MD with excited normal modes (MDeNM), collective modes-driven MD (CoMD), and elastic network model (ENM)-based generation, clustering, and relaxation of conformations (ClustENM) as well as its updated version integrated with MD simulations (ClustENMD). We analyzed the predicted conformational spaces using each of these four hybrid methods, applied to four well-studied proteins, triosephosphate isomerase (TIM), 3-phosphoglycerate kinase (PGK), HIV-1 protease (PR) and HIV-1 reverse transcriptase (RT), which provide extensive ensembles of experimental structures for benchmarking and comparing the methods. We show that a rigorous multi-faceted comparison and multiple metrics are necessary to properly assess the differences between conformational ensembles and provide an optimal protocol for achieving good agreement with experimental data. While all four hybrid methods perform well in general, being especially useful as computationally efficient methods that retain atomic resolution, the systematic analysis of the same systems by these four hybrid methods highlights the strengths and limitations of the methods and provides guidance for parameters and protocols to be adopted in future studies. |
| first_indexed | 2024-04-11T17:30:19Z |
| format | Article |
| id | doaj.art-902b2f3af6304360bc36b423da15694c |
| institution | Directory Open Access Journal |
| issn | 2296-889X |
| language | English |
| last_indexed | 2024-04-11T17:30:19Z |
| publishDate | 2022-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Molecular Biosciences |
| spelling | doaj.art-902b2f3af6304360bc36b423da15694c2022-12-22T04:12:08ZengFrontiers Media S.A.Frontiers in Molecular Biosciences2296-889X2022-02-01910.3389/fmolb.2022.832847832847Sampling of Protein Conformational Space Using Hybrid Simulations: A Critical Assessment of Recent MethodsBurak T. Kaynak0James M. Krieger1Balint Dudas2Balint Dudas3Balint Dudas4Zakaria L. Dahmani5Mauricio G. S. Costa6Erika Balog7Ana Ligia Scott8Pemra Doruker9David Perahia10Ivet Bahar11Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United StatesDepartment of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United StatesDepartment of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United StatesLaboratoire de Biologie et Pharmacologie Appliquée, Ecole Normale Supérieure Paris-Saclay, Gif-sur-Yvette, FranceDepartment of Biophysics and Radiation Biology, Semmelweis University, Budapest, HungaryDepartment of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United StatesPrograma de Computação Científica, Vice-Presiden̂cia de Educação, Informação e Comunicação, Fundação Oswaldo Cruz, Rio de Janeiro, BrazilDepartment of Biophysics and Radiation Biology, Semmelweis University, Budapest, HungaryLaboratory of Bioinformatics and Computational Biology, Center of Mathematics, Computation and Cognition, Federal University of ABC-UFABC, Santo André, BrazilDepartment of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United StatesLaboratoire de Biologie et Pharmacologie Appliquée, Ecole Normale Supérieure Paris-Saclay, Gif-sur-Yvette, FranceDepartment of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United StatesRecent years have seen several hybrid simulation methods for exploring the conformational space of proteins and their complexes or assemblies. These methods often combine fast analytical approaches with computationally expensive full atomic molecular dynamics (MD) simulations with the goal of rapidly sampling large and cooperative conformational changes at full atomic resolution. We present here a systematic comparison of the utility and limits of four such hybrid methods that have been introduced in recent years: MD with excited normal modes (MDeNM), collective modes-driven MD (CoMD), and elastic network model (ENM)-based generation, clustering, and relaxation of conformations (ClustENM) as well as its updated version integrated with MD simulations (ClustENMD). We analyzed the predicted conformational spaces using each of these four hybrid methods, applied to four well-studied proteins, triosephosphate isomerase (TIM), 3-phosphoglycerate kinase (PGK), HIV-1 protease (PR) and HIV-1 reverse transcriptase (RT), which provide extensive ensembles of experimental structures for benchmarking and comparing the methods. We show that a rigorous multi-faceted comparison and multiple metrics are necessary to properly assess the differences between conformational ensembles and provide an optimal protocol for achieving good agreement with experimental data. While all four hybrid methods perform well in general, being especially useful as computationally efficient methods that retain atomic resolution, the systematic analysis of the same systems by these four hybrid methods highlights the strengths and limitations of the methods and provides guidance for parameters and protocols to be adopted in future studies.https://www.frontiersin.org/articles/10.3389/fmolb.2022.832847/fullconformational landscape/spacenormal mode analysismolecular simulationselastic network modelsHIV-1 proteasetriosephosphate isomerase |
| spellingShingle | Burak T. Kaynak James M. Krieger Balint Dudas Balint Dudas Balint Dudas Zakaria L. Dahmani Mauricio G. S. Costa Erika Balog Ana Ligia Scott Pemra Doruker David Perahia Ivet Bahar Sampling of Protein Conformational Space Using Hybrid Simulations: A Critical Assessment of Recent Methods Frontiers in Molecular Biosciences conformational landscape/space normal mode analysis molecular simulations elastic network models HIV-1 protease triosephosphate isomerase |
| title | Sampling of Protein Conformational Space Using Hybrid Simulations: A Critical Assessment of Recent Methods |
| title_full | Sampling of Protein Conformational Space Using Hybrid Simulations: A Critical Assessment of Recent Methods |
| title_fullStr | Sampling of Protein Conformational Space Using Hybrid Simulations: A Critical Assessment of Recent Methods |
| title_full_unstemmed | Sampling of Protein Conformational Space Using Hybrid Simulations: A Critical Assessment of Recent Methods |
| title_short | Sampling of Protein Conformational Space Using Hybrid Simulations: A Critical Assessment of Recent Methods |
| title_sort | sampling of protein conformational space using hybrid simulations a critical assessment of recent methods |
| topic | conformational landscape/space normal mode analysis molecular simulations elastic network models HIV-1 protease triosephosphate isomerase |
| url | https://www.frontiersin.org/articles/10.3389/fmolb.2022.832847/full |
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