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pyPolyBuilder: Automated Preparation of Molecular Topologies and Initial Configurations for Molecular Dynamics Simulations of Arbitrary Supramolecules

  • Mayk C. Ramos
    Mayk C. Ramos
    Instituto de Química, Universidade Federal do Rio de Janeiro, Rio de Janeiro 21941-909, Brazil
  • Patrick K. Quoika
    Patrick K. Quoika
    Institute for General, Inorganic and Theoretical Chemistry, Center for Molecular Biosciences Innsbruck (CMBI), University of Innsbruck, A-6020 Innsbruck, Austria
  • Vitor A. C. Horta
    Vitor A. C. Horta
    Insight Centre for Data Analytics at Dublin City University, Dublin 9, Ireland
  • Douglas M. Dias
    Douglas M. Dias
    Department of Electronics and Telecommunications Engineering, State University of Rio de Janeiro, Rio de Janeiro 20550-900, Brazil
  • Elan G. Costa
    Elan G. Costa
    Department of Electronics and Telecommunications Engineering, State University of Rio de Janeiro, Rio de Janeiro 20550-900, Brazil
  • Jorge L. M. do Amaral
    Jorge L. M. do Amaral
    Department of Electronics and Telecommunications Engineering, State University of Rio de Janeiro, Rio de Janeiro 20550-900, Brazil
  • Luigi M. Ribeiro
    Luigi M. Ribeiro
    Department of Electronics and Telecommunications Engineering, State University of Rio de Janeiro, Rio de Janeiro 20550-900, Brazil
  • Klaus R. Liedl
    Klaus R. Liedl
    Institute for General, Inorganic and Theoretical Chemistry, Center for Molecular Biosciences Innsbruck (CMBI), University of Innsbruck, A-6020 Innsbruck, Austria
  • , and 
  • Bruno A. C. Horta*
    Bruno A. C. Horta
    Instituto de Química, Universidade Federal do Rio de Janeiro, Rio de Janeiro 21941-909, Brazil
    *E-mail: [email protected]
Cite this: J. Chem. Inf. Model. 2021, 61, 4, 1539–1544
Publication Date (Web):April 5, 2021
https://doi.org/10.1021/acs.jcim.0c01438
Copyright © 2021 American Chemical Society

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    Abstract

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    The construction of a molecular topology file is a prerequisite for any classical molecular dynamics simulation. However, the generation of such a file may be very challenging at times, especially for large supramolecules. While many tools are available to provide topologies for large proteins and other biomolecules, the scientific community researching nonbiological systems is not equally well equipped. Here, we present a practical tool to generate topologies for arbitrary supramolecules: The pyPolyBuilder. In addition to linear polymer chains, it also provides the possibility to generate topologies of arbitrary, large, branched molecules, such as, e.g., dendrimers. Furthermore, it also generates reasonable starting structures for simulations of these molecules. pyPolyBuilder is a standalone command-line tool implemented in python. Therefore, it may be easily incorporated in persisting simulation pipelines on any operating systems and with different simulation engines. pyPolyBuilder is freely available on github: https://github.com/mssm-labmmol/pypolybuilder

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    Cited By

    This article is cited by 7 publications.

    1. Abd. Kakhar Umar, Patanachai K. Limpikirati, Jittima Amie Luckanagul. From Linear to Nets: Multiconfiguration Polymer Structure Generation with PolyFlin. Journal of Chemical Information and Modeling 2023, 63 (21) , 6717-6726. https://doi.org/10.1021/acs.jcim.3c01221
    2. Josef Kehrein, Christoph Sotriffer. Molecular Dynamics Simulations for Rationalizing Polymer Bioconjugation Strategies: Challenges, Recent Developments, and Future Opportunities. ACS Biomaterials Science & Engineering 2023, Article ASAP.
    3. Han-Wen Pei, You-Liang Zhu, Zhong-Yuan Lu, Jun-Peng Li, Zhao-Yan Sun. Automatic Multiscale Method of Building up a Cross-linked Polymer Reaction System: Bridging SMILES to the Multiscale Molecular Dynamics Simulation. The Journal of Physical Chemistry B 2023, 127 (21) , 4905-4914. https://doi.org/10.1021/acs.jpcb.3c01555
    4. Daniel Markthaler, Maximilian Fleck, Bartosz Stankiewicz, Niels Hansen. Exploring the Effect of Enhanced Sampling on Protein Stability Prediction. Journal of Chemical Theory and Computation 2022, 18 (4) , 2569-2583. https://doi.org/10.1021/acs.jctc.1c01012
    5. Harikrishna Sahu, Kuan-Hsuan Shen, Joseph H. Montoya, Huan Tran, Rampi Ramprasad. Polymer Structure Predictor (PSP): A Python Toolkit for Predicting Atomic-Level Structural Models for a Range of Polymer Geometries. Journal of Chemical Theory and Computation 2022, 18 (4) , 2737-2748. https://doi.org/10.1021/acs.jctc.2c00022
    6. Fabian Grünewald, Riccardo Alessandri, Peter C. Kroon, Luca Monticelli, Paulo C. T. Souza, Siewert J. Marrink. Polyply; a python suite for facilitating simulations of macromolecules and nanomaterials. Nature Communications 2022, 13 (1) https://doi.org/10.1038/s41467-021-27627-4
    7. L. América Chi, Somayeh Asgharpour, José Correa-Basurto, Cindy Rodríguez Bandala, Marlet Martínez-Archundia. Unveiling the G4-PAMAM capacity to bind and protect Ang-(1-7) bioactive peptide by molecular dynamics simulations. Journal of Computer-Aided Molecular Design 2022, 36 (9) , 653-675. https://doi.org/10.1007/s10822-022-00470-5

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