Polyply
AI Models Apache-2.0 (Free)
About
Generates parameters and coordinates for atomistic & coarse-grained polymer MD simulations (force-field and topology agnostic).
Citation
Grunewald, F.; Alessandri, R.; Kroon, P.C.; Monticelli, L.; Souza, P.C.T.; Marrink, S.J. Polyply: a python suite for facilitating simulations of (bio-) macromolecules and nanomaterials. Nature Communications 13, 68 (2022). DOI:10.1038/s41467-021-27627-4
Frequently Asked Questions
What is Polyply?
Polyply is a ai models application available in the Paramus App Store. Generates parameters and coordinates for atomistic & coarse-grained polymer MD simulations (force-field and topology agnostic).
Is Polyply free to use?
Yes. Polyply is distributed under the Apache-2.0 (Free) license and is available at no cost through the Paramus App Store.
How do I install Polyply?
Polyply is installed through Paramus Chemistry OS, an on-premise Windows platform for computational chemistry. Open the Paramus App Store in your local installation and select Polyply for one-click deployment.
What type of application is Polyply?
Polyply belongs to the “AI Models” category in the Paramus App Store. It runs on Paramus Chemistry OS and can also be accessed through Paramus Cloud for supported workflows.
What platform does Polyply run on?
Polyply runs on Paramus Chemistry OS, a Windows-based on-premise platform that provides local compute power for demanding simulations. It requires a Paramus OS installation with appropriate hardware resources.
Can Polyply be automated or integrated with AI workflows?
Yes. Polyply is available as part of the Paramus ecosystem which supports MCP (Model Context Protocol) tools for AI-driven automation. This enables integration with large language models and automated research pipelines.
How should I cite Polyply in publications?
The recommended citation for Polyply is: Grunewald, F.; Alessandri, R.; Kroon, P.C.; Monticelli, L.; Souza, P.C.T.; Marrink, S.J. Polyply: a python suite for facilitating simulations of (bio-) macromolecules and nanomaterials. Nature Communications 13, 68 (2022). DOI:10.1038/s41467-021-27627-4