Evidence map›Paper›PMID 37695778›Full record

ArticlePLoS computational biology2023

OpenABC enables flexible, simplified, and efficient GPU accelerated simulations of biomolecular condensates.

Shuming Liu, Cong Wang, Andrew P Latham, Xinqiang Ding, Bin Zhang

Abstract read
In one paragraph

Article in PLoS computational biology, 2023. 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
–field-weighted citation impact
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.

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  9. Investigating Phase Separation in Genome Folding via Multiscale Computational Modeling.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Shuming LiuDepartment of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.
Cong WangDepartment of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.
Andrew P LathamDepartment of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.ORCID 0000-0002-9338-7253
Xinqiang DingDepartment of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.
Bin ZhangDepartment of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.ORCID 0000-0002-3685-7503

Funding

Probing and Perturbing Transcriptional Condensates with Multiscale Modeling and Deep LearningR35GM133580 · NIGMS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI Bin Zhang · 2019 to 2026
$3.1M
NIGMS NIH HHS R35 GM133580
6 · The paper itself

Abstract

Biomolecular condensates are important structures in various cellular processes but are challenging to study using traditional experimental techniques. In silico simulations with residue-level coarse-grained models strike a balance between computational efficiency and chemical accuracy. They could offer valuable insights by connecting the emergent properties of these complex systems with molecular sequences. However, existing coarse-grained models often lack easy-to-follow tutorials and are implemented in software that is not optimal for condensate simulations. To address these issues, we introduce OpenABC, a software package that greatly simplifies the setup and execution of coarse-grained condensate simulations with multiple force fields using Python scripting. OpenABC seamlessly integrates with the OpenMM molecular dynamics engine, enabling efficient simulations with performance on a single GPU that rivals the speed achieved by hundreds of CPUs. We also provide tools that convert coarse-grained configurations to all-atom structures for atomistic simulations. We anticipate that OpenABC will significantly facilitate the adoption of in silico simulations by a broader community to investigate the structural and dynamical properties of condensates.

Indexed as

Biomolecular CondensatesComputer SimulationResearch DesignSoftware

Identifiers

PMID37695778
PMCPMC10513381

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.