Journal
ACS OMEGA
Volume 5, Issue 50, Pages 32823-32843Publisher
AMER CHEMICAL SOC
DOI: 10.1021/acsomega.0c05469
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Funding
- Swiss National Science Foundation (SNSF) [IZLIZ2_183336, 200021_175735]
- European Research Council (ERC) under European Union [818776 DYNAPOL]
- Swiss National Science Foundation (SNF) [200021_175735] Funding Source: Swiss National Science Foundation (SNF)
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We present Swarm-CG, a versatile software for the automatic iterative parametrization of bonded parameters in coarse-grained (CG) models, ideal in combination with popular CG force fields such as MARTINI. By coupling fuzzy self-tuning particle swarm optimization to Boltzmann inversion, Swarm-CG performs accurate bottom-up parametrization of bonded terms in CG models composed of up to 200 pseudo atoms within 4-24 h on standard desktop machines, using default settings. The software benefits from a user-friendly interface and two different usage modes (default and advanced). We particularly expect Swarm-CG to support and facilitate the development of new CG models for the study of complex molecular systems interesting for bio- and nanotechnology. Excellent performances are demonstrated using a benchmark of 9 molecules of diverse nature, structural complexity, and size. Swarm-CG is available with all its dependencies via the Python Package Index (PIP package: swarm-cg). Demonstration data are available at: www.github.com/GMPavanLab/SwarmCG.
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