Evidence map›Paper›PMID 33577557›Full record

ArticlePLoS computational biology2021

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

Wei Lu, Carlos Bueno, Nicholas P Schafer, Joshua Moller, Shikai Jin, Xun Chen, Mingchen Chen, Xinyu Gu, Aram Davtyan, Juan J de Pablo and 1 more

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
3.3field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

27 citing papers in PubMed, 52 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Review
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  7. Simulating biomolecules for physiological timescales.Current opinion in structural biology · 2025
    Review
  8. Article
  9. Article
  10. The physical and evolutionary energy landscapes of devolved protein sequences corresponding to pseudogenes.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Machines on Genes through the Computational Microscope.Journal of chemical theory and computation · 2023
    Review
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 3 institutions in 1 country.

Wei LuCenter for Theoretical Biological Physics, Rice University, Houston, Texas, United States of America.ORCID 0000-0002-1572-2909
Carlos BuenoCenter for Theoretical Biological Physics, Rice University, Houston, Texas, United States of America.ORCID 0000-0001-9494-6128
Nicholas P SchaferCenter for Theoretical Biological Physics, Rice University, Houston, Texas, United States of America.
Joshua MollerPritzker School of Molecular Engineering, University of Chicago, Chicago, Illinois, United States of America.ORCID 0000-0002-2196-316X
Shikai JinCenter for Theoretical Biological Physics, Rice University, Houston, Texas, United States of America.ORCID 0000-0001-9525-4166
Xun ChenCenter for Theoretical Biological Physics, Rice University, Houston, Texas, United States of America.
Mingchen ChenCenter for Theoretical Biological Physics, Rice University, Houston, Texas, United States of America.ORCID 0000-0003-3916-7871
Xinyu GuCenter for Theoretical Biological Physics, Rice University, Houston, Texas, United States of America.ORCID 0000-0002-0125-7807
Aram DavtyanCenter for Theoretical Biological Physics, Rice University, Houston, Texas, United States of America.
Juan J de PabloPritzker School of Molecular Engineering, University of Chicago, Chicago, Illinois, United States of America.ORCID 0000-0002-3526-516X
Peter G WolynesCenter for Theoretical Biological Physics, Rice University, Houston, Texas, United States of America.ORCID 0000-0001-7975-9287
Center for Theoretical Biological Physics · USArgonne National Laboratory · USSchafer Corporation (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

SoftwareBinding SitesBiophysical PhenomenaComputational BiologyCystineDNAMolecular Dynamics SimulationNucleic Acid ConformationProtein BindingProtein ConformationProtein FoldingProteinsCystineDNAProteins

Identifiers

PMID33577557
PMCPMC7906472
OpenAlexW3126756260

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.