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Title: OpenABC enables flexible, simplified, and efficient GPU accelerated simulations of biomolecular condensates
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.  more » « less
Award ID(s):
2042362
PAR ID:
10478418
Author(s) / Creator(s):
; ; ; ;
Editor(s):
Wei, Guanghong
Publisher / Repository:
PLOS Computational Biology
Date Published:
Journal Name:
PLOS Computational Biology
Volume:
19
Issue:
9
ISSN:
1553-7358
Page Range / eLocation ID:
e1011442
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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