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SBMOpenMM: A Builder of Structure-Based Models for OpenMM

  • Martin Floor*
    Martin Floor
    Department of Basic Sciences, Faculty of Medicine and Health Sciences, Universitat Internacional de Catalunya, 08195 Sant Cugat del Vallès, Spain
    Department of Biosciences, Faculty of Sciences and Technology, Universitat de Vic−Universitat Central de Catalunya, 08500 Vic, Spain
    *Email: [email protected]
    More by Martin Floor
  • Kengjie Li
    Kengjie Li
    Warshel Institute of Computational Biology, The Chinese University of Hong Kong, 518172 Shenzhen, China
    More by Kengjie Li
  • Miquel Estévez-Gay
    Miquel Estévez-Gay
    CompBioLab Group, Institut de Química Computacional i Catàlisi (IQCC) and Departament de Química, Universitat de Girona, 17071 Girona, Spain
  • Luis Agulló
    Luis Agulló
    Faculty of Medicine, Universitat de Vic−Universitat Central de Catalunya, 08500 Vic, Spain
    More by Luis Agulló
  • Pau Marc Muñoz-Torres
    Pau Marc Muñoz-Torres
    Department of Basic Sciences, Faculty of Medicine and Health Sciences, Universitat Internacional de Catalunya, 08195 Sant Cugat del Vallès, Spain
  • Jenn K. Hwang
    Jenn K. Hwang
    Warshel Institute of Computational Biology, The Chinese University of Hong Kong, 518172 Shenzhen, China
  • Sílvia Osuna
    Sílvia Osuna
    CompBioLab Group, Institut de Química Computacional i Catàlisi (IQCC) and Departament de Química, Universitat de Girona, 17071 Girona, Spain
    ICREA, Pg. Lluís Companys 23, 08010 Barcelona, Spain
  • , and 
  • Jordi Villà-Freixa
    Jordi Villà-Freixa
    Department of Basic Sciences, Faculty of Medicine and Health Sciences, Universitat Internacional de Catalunya, 08195 Sant Cugat del Vallès, Spain
    Department of Biosciences, Faculty of Sciences and Technology, Universitat de Vic−Universitat Central de Catalunya, 08500 Vic, Spain
Cite this: J. Chem. Inf. Model. 2021, 61, 7, 3166–3171
Publication Date (Web):July 12, 2021
https://doi.org/10.1021/acs.jcim.1c00122
Copyright © 2021 American Chemical Society

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    Abstract

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    Molecular dynamics (MD) simulations have become a standard tool to correlate the structure and function of biomolecules and significant advances have been made in the study of proteins and their complexes. A major drawback of conventional MD simulations is the difficulty and cost of obtaining converged results, especially when exploring potential energy surfaces containing considerable energy barriers. This limits the wide use of MD calculations to determine the thermodynamic properties of biomolecular processes. Indeed, this is true when considering the conformational entropy of such processes, which is ultimately critical in assessing the simulations’ convergence. Alternatively, a wide range of structure-based models (SBMs) has been used in the literature to unravel the basic mechanisms of biomolecular dynamics. These models introduce simplifications that focus on the relevant aspects of the physical process under study. Because of this, SBMs incorporate the need to modify the force field definition and parameters to target specific biophysical simulations. Here we introduce SBMOpenMM, a Python library to build force fields for SBMs, that uses the OpenMM framework to create and run SBM simulations. The code is flexible and user-friendly and profits from the high customizability and performance provided by the OpenMM platform.

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    The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.jcim.1c00122.

    • It includes more detailed explanation of how the folding SBM molecular dynamics of FoxP1 were run and how the Markov-state model analysis was carried out. Validations and a description of the implemented force objects in the SBMOpenMM library and the available default SBMs (PDF)

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    Cited By

    This article is cited by 2 publications.

    1. Angy Liseth Dávalos, José David Rivera Echeverri, Denize C. Favaro, Ronaldo Junio de Oliveira, Gustavo Penteado Battesini Carretero, Caroline Lacerda, Iolanda Midea Cuccovia, Marcus Vinicius Cangussu Cardoso, Chuck S. Farah, Roberto Kopke Salinas. Uncovering the Association Mechanism between Two Intrinsically Flexible Proteins. ACS Chemical Biology 2024, 19 (3) , 669-686. https://doi.org/10.1021/acschembio.3c00649
    2. Andres Bustamante, Rodrigo Rivera, Martin Floor, Jorge Babul, Mauricio Baez. Single-molecule optical tweezers reveals folding steps of the domain swapping mechanism of a protein. Biophysical Journal 2021, 120 (21) , 4809-4818. https://doi.org/10.1016/j.bpj.2021.09.026

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