Swarm-CG: Automatic Parametrization of Bonded Terms in MARTINI-Based Coarse-Grained Models of Simple to Complex Molecules via Fuzzy Self-Tuning Particle Swarm Optimization

Charly Empereur-Mot; Luca Pesce; Giovanni Doni; Davide Bochicchio; Riccardo Capelli; Claudio Perego; Giovanni M Pavan

doi:10.1021/acsomega.0c05469

Swarm-CG: Automatic Parametrization of Bonded Terms in MARTINI-Based Coarse-Grained Models of Simple to Complex Molecules via Fuzzy Self-Tuning Particle Swarm Optimization

ACS Omega. 2020 Dec 7;5(50):32823-32843. doi: 10.1021/acsomega.0c05469. eCollection 2020 Dec 22.

Authors

Charly Empereur-Mot¹, Luca Pesce¹, Giovanni Doni¹, Davide Bochicchio¹, Riccardo Capelli², Claudio Perego¹, Giovanni M Pavan^{2

1}

Affiliations

¹ Department of Innovative Technologies, University of Applied Sciences and Arts of Southern Switzerland, Galleria 2, Via Cantonale 2c, CH-6928 Manno, Switzerland.
² Department of Applied Science and Techology, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy.

Abstract

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.