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OpenAWSEM with Open3SPN2: A fast, flexible, and accessible framework for large-scale coarse-grained biomolecular simulations.
Lu, Wei; Bueno, Carlos; Schafer, Nicholas P; Moller, Joshua; Jin, Shikai; Chen, Xun; Chen, Mingchen; Gu, Xinyu; Davtyan, Aram; de Pablo, Juan J; Wolynes, Peter G.
Afiliación
  • Lu W; Center for Theoretical Biological Physics, Rice University, Houston, Texas, United States of America.
  • Bueno C; Department of Physics, Rice University, Houston, Texas, United States of America.
  • Schafer NP; Center for Theoretical Biological Physics, Rice University, Houston, Texas, United States of America.
  • Moller J; Department of Chemistry, Rice University, Houston, Texas, United States of America.
  • Jin S; Center for Theoretical Biological Physics, Rice University, Houston, Texas, United States of America.
  • Chen X; Department of Chemistry, Rice University, Houston, Texas, United States of America.
  • Chen M; Schafer Science, LLC, Houston, Texas United States of America.
  • Gu X; Pritzker School of Molecular Engineering, University of Chicago, Chicago, Illinois, United States of America.
  • Davtyan A; Argonne National Laboratory, Lemont, Illinois, United States of America.
  • de Pablo JJ; Center for Theoretical Biological Physics, Rice University, Houston, Texas, United States of America.
  • Wolynes PG; Department of Biosciences, Rice University, Houston, Texas, United States of America.
PLoS Comput Biol ; 17(2): e1008308, 2021 02.
Article en En | MEDLINE | ID: mdl-33577557
We present OpenAWSEM and Open3SPN2, new cross-compatible implementations of coarse-grained models for protein (AWSEM) and DNA (3SPN2) molecular dynamics simulations within the OpenMM framework. These new implementations retain the chemical accuracy and intrinsic efficiency of the original models while adding GPU acceleration and the ease of forcefield modification provided by OpenMM's Custom Forces software framework. By utilizing GPUs, we achieve around a 30-fold speedup in protein and protein-DNA simulations over the existing LAMMPS-based implementations running on a single CPU core. We showcase the benefits of OpenMM's Custom Forces framework by devising and implementing two new potentials that allow us to address important aspects of protein folding and structure prediction and by testing the ability of the combined OpenAWSEM and Open3SPN2 to model protein-DNA binding. The first potential is used to describe the changes in effective interactions that occur as a protein becomes partially buried in a membrane. We also introduced an interaction to describe proteins with multiple disulfide bonds. Using simple pairwise disulfide bonding terms results in unphysical clustering of cysteine residues, posing a problem when simulating the folding of proteins with many cysteines. We now can computationally reproduce Anfinsen's early Nobel prize winning experiments by using OpenMM's Custom Forces framework to introduce a multi-body disulfide bonding term that prevents unphysical clustering. Our protein-DNA simulations show that the binding landscape is funneled towards structures that are quite similar to those found using experiments. In summary, this paper provides a simulation tool for the molecular biophysics community that is both easy to use and sufficiently efficient to simulate large proteins and large protein-DNA systems that are central to many cellular processes. These codes should facilitate the interplay between molecular simulations and cellular studies, which have been hampered by the large mismatch between the time and length scales accessible to molecular simulations and those relevant to cell biology.
Asunto(s)

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Programas Informáticos / ADN / Proteínas / Simulación de Dinámica Molecular Tipo de estudio: Prognostic_studies Idioma: En Revista: PLoS Comput Biol Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2021 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Asunto principal: Programas Informáticos / ADN / Proteínas / Simulación de Dinámica Molecular Tipo de estudio: Prognostic_studies Idioma: En Revista: PLoS Comput Biol Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2021 Tipo del documento: Article