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arXiv · 2105.05890

Polyply: a python suite for facilitating simulations of (bio-)macromolecules and nanomaterials

Fabian Grünewald·Riccardo Alessandri·Peter C. Kroon·Luca Monticelli·Paulo C. T. Souza·Siewert J. Marrink
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Abstract

Molecular dynamics simulations play an increasingly important role in the rational design of (nano)-materials and in the study of biomacromolecules. However, generating input files and realistic starting coordinates for these simulations is a major bottleneck, especially for high throughput protocols and for complex multi-component systems. To eliminate this bottleneck, we present the polyply software suite that leverages 1) a multi-scale graph matching algorithm designed to generate parameters quickly and for arbitrarily complex polymeric topologies, and 2) a generic multi-scale random walk protocol capable of setting up complex systems efficiently and independent of the target force-field or model resolution. We benchmark quality and performance of the approach by creating melt simulations of six different polymers using two force-fields with different resolution. We further demonstrate the power of our approach by setting up a multi lamellar microphase-separated block copolymer system for next generation batteries, and by generating a liquid-liquid phase separated polyethylene oxide-dextran system inside a lipid vesicle, featuring both branching and molecular weight distribution of the dextran component.

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Fabian Grünewald, Riccardo Alessandri, Peter C. Kroon, Luca Monticelli, Paulo C. T. Souza, Siewert J. Marrink. 2021-05-12. Polyply: a python suite for facilitating simulations of (bio-)macromolecules and nanomaterials. https://doi.org/10.1038/s41467-021-27627-4

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