Pub Date : 2019-01-01Epub Date: 2018-11-29DOI: 10.33011/livecoms.1.1.5957
Efrem Braun, Justin Gilmer, Heather B Mayes, David L Mobley, Jacob I Monroe, Samarjeet Prasad, Daniel M Zuckerman
This document provides a starting point for approaching molecular simulations, guiding beginning practitioners to what issues they need to know about before and while starting their first simulations, and why those issues are so critical. This document makes no claims to provide an adequate introduction to the subject on its own. Instead, our goal is to help people know what issues are critical before beginning, and to provide references to good resources on those topics. We also provide a checklist of key issues to consider before and while setting up molecular simulations which may serve as a foundation for other best practices documents.
{"title":"Best Practices for Foundations in Molecular Simulations [Article v1.0].","authors":"Efrem Braun, Justin Gilmer, Heather B Mayes, David L Mobley, Jacob I Monroe, Samarjeet Prasad, Daniel M Zuckerman","doi":"10.33011/livecoms.1.1.5957","DOIUrl":"https://doi.org/10.33011/livecoms.1.1.5957","url":null,"abstract":"<p><p>This document provides a starting point for approaching molecular simulations, guiding beginning practitioners to what issues they need to know about before and while starting their first simulations, and why those issues are so critical. This document makes no claims to provide an adequate introduction to the subject on its own. Instead, our goal is to help people know what issues are <i>critical</i> before beginning, and to provide references to good resources on those topics. We also provide a checklist of key issues to consider before and while setting up molecular simulations which may serve as a foundation for other best practices documents.</p>","PeriodicalId":74084,"journal":{"name":"Living journal of computational molecular science","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6884151/pdf/nihms-1000355.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49685874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-01DOI: 10.33011/LIVECOMS.1.1.5068
Justin A. Lemkul
This LiveCoMS document is maintained online on GitHub at https: //github.com/jalemkul/ gmx_tutorials_livecoms; to provide feedback, suggestions, or help improve it, please visit the GitHub repository and participate via the issue tracker. This version dated January 2, 2019 Abstract Molecular dynamics (MD) simulations are a popular technique for studying the atomistic behavior of any molecular system. Performing MD simulations requires a user to become familiar with the commands, options, and file formats of the chosen simulation software, none of which are consistent across different programs. Beyond these requirements, users are expected to be familiar with various aspects of physics, mathematics, computer programming, and interaction with a command-line environment, presenting critical barriers to entry in the MD simulation field. This article presents seven tutorials for instructing users in the proper methods for preparing and carrying out different types of MD simulations in the popular GROMACS simulation package. GROMACS is an open-source, free, and flexible MD package that is consistently among the fastest in the world. The tutorials presented here range from a "simple" system of a protein in aqueous solution to more advanced concepts such as force field organization and modification for a membrane-protein system, two methods of calculating free energy differences (umbrella sampling and "alchemical" methods), biphasic systems, protein-ligand complexes, and the use of virtual sites in MD simulations. In this article, users are provided the rationale and a theoretical explanation for the command-line syntax in each step in the online tutorials (available at http://www.mdtutorials.com/gmx) and the underlying settings and algorithms necessary to perform robust MD simulations in each scenario.
{"title":"From Proteins to Perturbed Hamiltonians: A Suite of Tutorials for the GROMACS-2018 Molecular Simulation Package [Article v1.0]","authors":"Justin A. Lemkul","doi":"10.33011/LIVECOMS.1.1.5068","DOIUrl":"https://doi.org/10.33011/LIVECOMS.1.1.5068","url":null,"abstract":"This LiveCoMS document is maintained online on GitHub at https: //github.com/jalemkul/ gmx_tutorials_livecoms; to provide feedback, suggestions, or help improve it, please visit the GitHub repository and participate via the issue tracker. This version dated January 2, 2019 Abstract Molecular dynamics (MD) simulations are a popular technique for studying the atomistic behavior of any molecular system. Performing MD simulations requires a user to become familiar with the commands, options, and file formats of the chosen simulation software, none of which are consistent across different programs. Beyond these requirements, users are expected to be familiar with various aspects of physics, mathematics, computer programming, and interaction with a command-line environment, presenting critical barriers to entry in the MD simulation field. This article presents seven tutorials for instructing users in the proper methods for preparing and carrying out different types of MD simulations in the popular GROMACS simulation package. GROMACS is an open-source, free, and flexible MD package that is consistently among the fastest in the world. The tutorials presented here range from a \"simple\" system of a protein in aqueous solution to more advanced concepts such as force field organization and modification for a membrane-protein system, two methods of calculating free energy differences (umbrella sampling and \"alchemical\" methods), biphasic systems, protein-ligand complexes, and the use of virtual sites in MD simulations. In this article, users are provided the rationale and a theoretical explanation for the command-line syntax in each step in the online tutorials (available at http://www.mdtutorials.com/gmx) and the underlying settings and algorithms necessary to perform robust MD simulations in each scenario.","PeriodicalId":74084,"journal":{"name":"Living journal of computational molecular science","volume":"11 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69480733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-01DOI: 10.33011/LIVECOMS.1.1.5965
C. Wehmeyer, Martin K. Scherer, Tim Hempel, B. Husic, S. Olsson, F. Noé
{"title":"Introduction to Markov state modeling with the PyEMMA software [Article v1.0]","authors":"C. Wehmeyer, Martin K. Scherer, Tim Hempel, B. Husic, S. Olsson, F. Noé","doi":"10.33011/LIVECOMS.1.1.5965","DOIUrl":"https://doi.org/10.33011/LIVECOMS.1.1.5965","url":null,"abstract":"","PeriodicalId":74084,"journal":{"name":"Living journal of computational molecular science","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69480742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-01Epub Date: 2019-10-04DOI: 10.33011/livecoms.1.2.10607
Anthony T Bogetti, Barmak Mostofian, Alex Dickson, A J Pratt, Ali S Saglam, Page O Harrison, Joshua L Adelman, Max Dudek, Paul A Torrillo, Alex J DeGrave, Upendra Adhikari, Matthew C Zwier, Daniel M Zuckerman, Lillian T Chong
The weighted ensemble (WE) strategy has been demonstrated to be highly efficient in generating pathways and rate constants for rare events such as protein folding and protein binding using atomistic molecular dynamics simulations. Here we present five tutorials instructing users in the best practices for preparing, carrying out, and analyzing WE simulations for various applications using the WESTPA software. Users are expected to already have significant experience with running standard molecular dynamics simulations using the underlying dynamics engine of interest (e.g. Amber, Gromacs, OpenMM). The tutorials range from a molecular association process in explicit solvent to more complex processes such as host-guest association, peptide conformational sampling, and protein folding.
{"title":"A Suite of Tutorials for the WESTPA Rare-Events Sampling Software [Article v1.0].","authors":"Anthony T Bogetti, Barmak Mostofian, Alex Dickson, A J Pratt, Ali S Saglam, Page O Harrison, Joshua L Adelman, Max Dudek, Paul A Torrillo, Alex J DeGrave, Upendra Adhikari, Matthew C Zwier, Daniel M Zuckerman, Lillian T Chong","doi":"10.33011/livecoms.1.2.10607","DOIUrl":"https://doi.org/10.33011/livecoms.1.2.10607","url":null,"abstract":"<p><p>The weighted ensemble (WE) strategy has been demonstrated to be highly efficient in generating pathways and rate constants for rare events such as protein folding and protein binding using atomistic molecular dynamics simulations. Here we present five tutorials instructing users in the best practices for preparing, carrying out, and analyzing WE simulations for various applications using the WESTPA software. Users are expected to already have significant experience with running standard molecular dynamics simulations using the underlying dynamics engine of interest (e.g. Amber, Gromacs, OpenMM). The tutorials range from a molecular association process in explicit solvent to more complex processes such as host-guest association, peptide conformational sampling, and protein folding.</p>","PeriodicalId":74084,"journal":{"name":"Living journal of computational molecular science","volume":"1 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7213600/pdf/nihms-1584279.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37924090","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-01DOI: 10.33011/livecoms.1.2.10841
Shailesh Kumar Panday, Mihiri H. B. Shashikala, Mahesh Koirala, S. Pahari, Arghya Chakrvorty, Yunhui Peng, Lin Li, Zhe Jia, Chuan Li, E. Alexov
This LiveCoMS document is maintained online on GitHub at https: //github.com/delphi001/ delphi_tutorial_livecoms; to provide feedback, suggestions, or help improve it, please visit the GitHub repository and participate via the issue tracker. This version dated November 25, 2019 Abstract Electrostatics play an indispensable role in practically any process in molecular biology. Indeed, at distances larger than several Angstroms, all other forces are negligibly small and electrostatic force dominates. However, modeling electrostatics in molecular biology is a complicated task due to presence of water phase, mobile ions and irregularly shaped inhomogeneous biological macromolecules. A particular approach to calculating electrostatics in such systems is to apply the Poisson-Boltzmann equation (PBE). Here, we provide a tutorial for the popular DelPhi package that solves PBE using a finite-difference method and delivers the electrostatic potential distribution throughout the modeling box. The tutorial comes with a detailed description of different tasks that DelPhi can handle, an assessment of the accuracy against cases with analytical solutions and recommendations about DelPhi usage. Furthermore, since electrostatics is a key component of virtually any modeling in molecular biology, we have created many additional resources utilizing DelPhi to model various biology relevant quantities. Tutorials for these resources are also provided along with examples of their usage.
{"title":"Modeling electrostatics in molecular biology: A tutorial of DelPhi and associated resources [Article v1.0]","authors":"Shailesh Kumar Panday, Mihiri H. B. Shashikala, Mahesh Koirala, S. Pahari, Arghya Chakrvorty, Yunhui Peng, Lin Li, Zhe Jia, Chuan Li, E. Alexov","doi":"10.33011/livecoms.1.2.10841","DOIUrl":"https://doi.org/10.33011/livecoms.1.2.10841","url":null,"abstract":"This LiveCoMS document is maintained online on GitHub at https: //github.com/delphi001/ delphi_tutorial_livecoms; to provide feedback, suggestions, or help improve it, please visit the GitHub repository and participate via the issue tracker. This version dated November 25, 2019 Abstract Electrostatics play an indispensable role in practically any process in molecular biology. Indeed, at distances larger than several Angstroms, all other forces are negligibly small and electrostatic force dominates. However, modeling electrostatics in molecular biology is a complicated task due to presence of water phase, mobile ions and irregularly shaped inhomogeneous biological macromolecules. A particular approach to calculating electrostatics in such systems is to apply the Poisson-Boltzmann equation (PBE). Here, we provide a tutorial for the popular DelPhi package that solves PBE using a finite-difference method and delivers the electrostatic potential distribution throughout the modeling box. The tutorial comes with a detailed description of different tasks that DelPhi can handle, an assessment of the accuracy against cases with analytical solutions and recommendations about DelPhi usage. Furthermore, since electrostatics is a key component of virtually any modeling in molecular biology, we have created many additional resources utilizing DelPhi to model various biology relevant quantities. Tutorials for these resources are also provided along with examples of their usage.","PeriodicalId":74084,"journal":{"name":"Living journal of computational molecular science","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69480794","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-01Epub Date: 2019-08-09DOI: 10.33011/livecoms.1.2.9974
Rodrigo Galindo-Murillo, Thomas E Cheatham
Nucleic acids are highly charged macromolecules sensitive to their surroundings of water, salt, and other biomolecules. Molecular dynamics simulations with accurate biomolecular force fields provide a detailed atomistic view into DNA and RNA that has been useful to study the structure and dynamics of these molecules and their biological relevance. In this work we study the Drew-Dickerson dodecamer duplex with the sequence d(GCGCAATTGCGC)2 in three different salt concentrations and using different monvalent salt types to detect possible structural influence. Overall, the DNA shows no major structural changes regardless of amount or type of monovalent ions used. Our results show that only at very high salt conditions (5M) is a small structural effect observed in the DNA duplex, which mainly consist of narrowing of the grooves due to increased residence of ions. We also present the importance of sampling time to achieve a converged ensemble, which is of major relevance in any simulation to avoid biased or non-meaningful results.
{"title":"Lessons learned in atomistic simulation of double-stranded DNA: Solvation and salt concerns [Article v1.0].","authors":"Rodrigo Galindo-Murillo, Thomas E Cheatham","doi":"10.33011/livecoms.1.2.9974","DOIUrl":"10.33011/livecoms.1.2.9974","url":null,"abstract":"<p><p>Nucleic acids are highly charged macromolecules sensitive to their surroundings of water, salt, and other biomolecules. Molecular dynamics simulations with accurate biomolecular force fields provide a detailed atomistic view into DNA and RNA that has been useful to study the structure and dynamics of these molecules and their biological relevance. In this work we study the Drew-Dickerson dodecamer duplex with the sequence d(GCGCAATTGCGC)<sub>2</sub> in three different salt concentrations and using different monvalent salt types to detect possible structural influence. Overall, the DNA shows no major structural changes regardless of amount or type of monovalent ions used. Our results show that only at very high salt conditions (5M) is a small structural effect observed in the DNA duplex, which mainly consist of narrowing of the grooves due to increased residence of ions. We also present the importance of sampling time to achieve a converged ensemble, which is of major relevance in any simulation to avoid biased or non-meaningful results.</p>","PeriodicalId":74084,"journal":{"name":"Living journal of computational molecular science","volume":"1 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7561045/pdf/nihms-1610687.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38505758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-01-01DOI: 10.33011/LIVECOMS.1.1.6324
E. Maginn, Richard A. Messerly, Daniel J. Carlson, Daniel R. Roe, J. Richard Elliott
1Department of Chemical and Biomolecular Engineering, The University of Notre Dame; 2Thermodynamics Research Center, National Institute of Standards and Technology; 3Chemical Engineering Department, Brigham Young University; 4Laboratory of Computational Biology, National Heart Lung and Blood Institute, National Institutes of Health; 5Department of Chemical and Biomolecular Engineering, The University of Akron
{"title":"Best Practices for Computing Transport Properties 1. Self-Diffusivity and Viscosity from Equilibrium Molecular Dynamics [Article v1.0]","authors":"E. Maginn, Richard A. Messerly, Daniel J. Carlson, Daniel R. Roe, J. Richard Elliott","doi":"10.33011/LIVECOMS.1.1.6324","DOIUrl":"https://doi.org/10.33011/LIVECOMS.1.1.6324","url":null,"abstract":"1Department of Chemical and Biomolecular Engineering, The University of Notre Dame; 2Thermodynamics Research Center, National Institute of Standards and Technology; 3Chemical Engineering Department, Brigham Young University; 4Laboratory of Computational Biology, National Heart Lung and Blood Institute, National Institutes of Health; 5Department of Chemical and Biomolecular Engineering, The University of Akron","PeriodicalId":74084,"journal":{"name":"Living journal of computational molecular science","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69480745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-01-01Epub Date: 2018-10-27DOI: 10.33011/livecoms.1.1.5067
Alan Grossfield, Paul N Patrone, Daniel R Roe, Andrew J Schultz, Daniel W Siderius, Daniel M Zuckerman
The quantitative assessment of uncertainty and sampling quality is essential in molecular simulation. Many systems of interest are highly complex, often at the edge of current computational capabilities. Modelers must therefore analyze and communicate statistical uncertainties so that "consumers" of simulated data understand its significance and limitations. This article covers key analyses appropriate for trajectory data generated by conventional simulation methods such as molecular dynamics and (single Markov chain) Monte Carlo. It also provides guidance for analyzing some 'enhanced' sampling approaches. We do not discuss systematic errors arising, e.g., from inaccuracy in the chosen model or force field.
{"title":"Best Practices for Quantification of Uncertainty and Sampling Quality in Molecular Simulations [Article v1.0].","authors":"Alan Grossfield, Paul N Patrone, Daniel R Roe, Andrew J Schultz, Daniel W Siderius, Daniel M Zuckerman","doi":"10.33011/livecoms.1.1.5067","DOIUrl":"10.33011/livecoms.1.1.5067","url":null,"abstract":"<p><p>The quantitative assessment of uncertainty and sampling quality is essential in molecular simulation. Many systems of interest are highly complex, often at the edge of current computational capabilities. Modelers must therefore analyze and communicate statistical uncertainties so that \"consumers\" of simulated data understand its significance and limitations. This article covers key analyses appropriate for trajectory data generated by conventional simulation methods such as molecular dynamics and (single Markov chain) Monte Carlo. It also provides guidance for analyzing some 'enhanced' sampling approaches. We do not discuss <i>systematic</i> errors arising, e.g., from inaccuracy in the chosen model or force field.</p>","PeriodicalId":74084,"journal":{"name":"Living journal of computational molecular science","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6286151/pdf/nihms-994026.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"36768479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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