rinikerlab / PyGromosTools

This package is a python library with tools for the Molecular Simulation - Software Gromos. It allows you to easily set up, manage and analyze simulations in python.
https://rinikerlab.github.io/PyGromosTools/
MIT License
16 stars 14 forks source link
api computational-chemistry energy-minimization gromos md molecular-dynamics openforcefield protein-simulations python rdkit simulation stochastic-dynamics wrapper

![]() PyGromosBanLight PyGromosBanLight

Welcome to PyGromosTools

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Description

The aim of the module is to bring GROMOS to the Python3 World! This repository should make it easier to work with GROMOS in Python and should enable the user to write cleaner, more reliable and adaptable code.

General informations about functions can be found in our wiki and usage example for many general functions and theire relations are shown in jupyter notebooks in the examples in the example folder.

Content

Quick Setup

Quick Start - move to the root folder of this repository:

    # build environment
    conda env create -f conda_env.yaml
    conda develop -n pygromos ${PWD}

    # activate environment
    conda activate pygromos

In case the conda develop command does not work for you, you can also use python -m pip install -e . to install PyGromosTools in a development environment. Please make sure, that you have GROMOS (www.gromos.net) binaries around, if you want to use the MD-Package. We sadly can not provide the source code for this package, as it is currently not open-source.

If you find a bug or have an feature request, please raise an Issue on GitHub.

For more information, see INSTALL.md file for more informations.

Contributions

You want to contribute? Awesome! We are happy to support you in this process. For any contribution, please check out the CODE_OF_CONDUCT.md file and the style guide in styleguide.md. There will be a small code revision for code contributions, to verify that everything is in place.

Publications

Scientific Literature using PyGromosTools:

^ contributed equally

Acknowledgements

Many thanks to Robin Wolf for the logo design!

Copyright

Copyright (c) 2020, Benjamin Ries, Marc Lehner, Salome Rieder, Felix Pultar, Paul Katzberger, Candide Champion

Project based on the Computational Molecular Science Python Cookiecutter version 1.3.