Polyply; a python suite for facilitating simulations of macromolecules and nanomaterials

Area of Science:

• Computational chemistry and materials science
• Biomolecular simulations
• Polymer science

Background:

• Molecular dynamics (MD) simulations are crucial for designing nanomaterials and studying biomacromolecules.
• Generating input files and realistic starting coordinates for MD simulations is a significant challenge, particularly for high-throughput studies and complex systems.
• Existing methods often lack efficiency and versatility for diverse molecular architectures.

Purpose of the Study:

• To introduce the polyply software suite, designed to eliminate bottlenecks in generating MD simulation input and coordinates.
• To provide tools for rapid parameter generation and efficient system setup, independent of force fields or model resolutions.

Main Methods:

• Development of a multi-scale graph matching algorithm for rapid parameter generation of complex polymer topologies.
• Implementation of a generic multi-scale random walk protocol for efficient setup of complex systems.
• Benchmarking using polymer melts, single-stranded DNA (ssDNA), and circular ssDNA.

Main Results:

• Polyply successfully generated realistic coordinates for various polymer systems, including polymer melts and DNA.
• Demonstrated the capability to set up complex systems like microphase-separated block copolymers and liquid-liquid phase-separated systems within lipid vesicles.
• Validated the quality and performance of the polyply approach.

Conclusions:

• The polyply software suite effectively addresses the challenge of generating simulation inputs and coordinates for complex molecular systems.
• It offers a versatile and efficient solution for accelerating research in materials design and biomolecular simulations.
• Polyply facilitates the setup of advanced systems, enabling deeper insights into material properties and biological processes.