Literature DB >> 33577557

OpenAWSEM with Open3SPN2: A fast, flexible, and accessible framework for large-scale coarse-grained biomolecular simulations.

Wei Lu1,2, Carlos Bueno1,3, Nicholas P Schafer1,3,4, Joshua Moller5,6, Shikai Jin1,7, Xun Chen1,3, Mingchen Chen1, Xinyu Gu1,3, Aram Davtyan1, Juan J de Pablo5,6, Peter G Wolynes1,3,2,7.   

Abstract

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.

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Year:  2021        PMID: 33577557      PMCID: PMC7906472          DOI: 10.1371/journal.pcbi.1008308

Source DB:  PubMed          Journal:  PLoS Comput Biol        ISSN: 1553-734X            Impact factor:   4.475


  40 in total

1.  Role of water mediated interactions in protein-protein recognition landscapes.

Authors:  Garegin A Papoian; Johan Ulander; Peter G Wolynes
Journal:  J Am Chem Soc       Date:  2003-07-30       Impact factor: 15.419

2.  How fast-folding proteins fold.

Authors:  Kresten Lindorff-Larsen; Stefano Piana; Ron O Dror; David E Shaw
Journal:  Science       Date:  2011-10-28       Impact factor: 47.728

3.  Self-consistently optimized energy functions for protein structure prediction by molecular dynamics.

Authors:  K K Koretke; Z Luthey-Schulten; P G Wolynes
Journal:  Proc Natl Acad Sci U S A       Date:  1998-03-17       Impact factor: 11.205

4.  Coarse-grained modeling of DNA curvature.

Authors:  Gordon S Freeman; Daniel M Hinckley; Joshua P Lequieu; Jonathan K Whitmer; Juan J de Pablo
Journal:  J Chem Phys       Date:  2014-10-28       Impact factor: 3.488

5.  Predictive energy landscapes for protein-protein association.

Authors:  Weihua Zheng; Nicholas P Schafer; Aram Davtyan; Garegin A Papoian; Peter G Wolynes
Journal:  Proc Natl Acad Sci U S A       Date:  2012-11-05       Impact factor: 11.205

6.  Protein Structure Prediction in CASP13 Using AWSEM-Suite.

Authors:  Shikai Jin; Mingchen Chen; Xun Chen; Carlos Bueno; Wei Lu; Nicholas P Schafer; Xingcheng Lin; José N Onuchic; Peter G Wolynes
Journal:  J Chem Theory Comput       Date:  2020-05-22       Impact factor: 6.006

7.  Protein structure prediction: making AWSEM AWSEM-ER by adding evolutionary restraints.

Authors:  Brian J Sirovetz; Nicholas P Schafer; Peter G Wolynes
Journal:  Proteins       Date:  2017-08-27

8.  Template-Guided Protein Structure Prediction and Refinement Using Optimized Folding Landscape Force Fields.

Authors:  Mingchen Chen; Xingcheng Lin; Wei Lu; Nicholas P Schafer; José N Onuchic; Peter G Wolynes
Journal:  J Chem Theory Comput       Date:  2018-10-08       Impact factor: 6.006

9.  Learning To Fold Proteins Using Energy Landscape Theory.

Authors:  N P Schafer; B L Kim; W Zheng; P G Wolynes
Journal:  Isr J Chem       Date:  2014-08       Impact factor: 3.333

10.  OpenMM 7: Rapid development of high performance algorithms for molecular dynamics.

Authors:  Peter Eastman; Jason Swails; John D Chodera; Robert T McGibbon; Yutong Zhao; Kyle A Beauchamp; Lee-Ping Wang; Andrew C Simmonett; Matthew P Harrigan; Chaya D Stern; Rafal P Wiewiora; Bernard R Brooks; Vijay S Pande
Journal:  PLoS Comput Biol       Date:  2017-07-26       Impact factor: 4.475

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  6 in total

1.  Single-molecule conformational dynamics of a transcription factor reveals a continuum of binding modes controlling association and dissociation.

Authors:  Wei Chen; Wei Lu; Peter G Wolynes; Elizabeth A Komives
Journal:  Nucleic Acids Res       Date:  2021-11-08       Impact factor: 16.971

2.  Fibril Surface-Dependent Amyloid Precursors Revealed by Coarse-Grained Molecular Dynamics Simulation.

Authors:  Yuan-Wei Ma; Tong-You Lin; Min-Yeh Tsai
Journal:  Front Mol Biosci       Date:  2021-08-06

3.  Determining Sequence-Dependent DNA Oligonucleotide Hybridization and Dehybridization Mechanisms Using Coarse-Grained Molecular Simulation, Markov State Models, and Infrared Spectroscopy.

Authors:  Michael S Jones; Brennan Ashwood; Andrei Tokmakoff; Andrew L Ferguson
Journal:  J Am Chem Soc       Date:  2021-10-13       Impact factor: 15.419

4.  Exploring the folding energy landscapes of heme proteins using a hybrid AWSEM-heme model.

Authors:  Xun Chen; Wei Lu; Min-Yeh Tsai; Shikai Jin; Peter G Wolynes
Journal:  J Biol Phys       Date:  2022-01-09       Impact factor: 1.365

5.  Implementation of residue-level coarse-grained models in GENESIS for large-scale molecular dynamics simulations.

Authors:  Cheng Tan; Jaewoon Jung; Chigusa Kobayashi; Diego Ugarte La Torre; Shoji Takada; Yuji Sugita
Journal:  PLoS Comput Biol       Date:  2022-04-05       Impact factor: 4.779

6.  Computationally exploring the mechanism of bacteriophage T7 gp4 helicase translocating along ssDNA.

Authors:  Shikai Jin; Carlos Bueno; Wei Lu; Qian Wang; Mingchen Chen; Xun Chen; Peter G Wolynes; Yang Gao
Journal:  Proc Natl Acad Sci U S A       Date:  2022-08-01       Impact factor: 12.779

  6 in total

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