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A comprehensive toolkit for predicting free energies

Home Page: https://psivant.github.io/femto/

License: MIT License

Python 99.79% Makefile 0.21%

femto's Introduction

Free Energy and MD Toolkit using OpenMM

A comprehensive toolkit for predicting free energies

ci coverage license


The femto framework aims to offer not only a compact and comprehensive toolkit for predicting binding free energies using methods including ATM and SepTop, but also a full suite of utilities for running advanced simulations using OpenMM, including support for HREMD and REST2.

Warning: The ATM implementation was recently updated to make use of the new ATMForce shipped with OpenMM 8.1. While every effort was made to ensure correctness, this was a major change that is still being tested and there may be bugs. Please report any issues you encounter.

Further, the default protocols selected for the ATM and SepTop methods are still being tested and optimized, and may not be optimal. It is recommended that you run a few test calculations to ensure that the results are reasonable.

Installation

This package can be installed using conda (or mamba, a faster version of conda):

mamba install -c conda-forge femto

If you are running with MPI on an HPC cluster, you may need to instruct conda to use your local installation depending on your setup

mamba install -c conda-forge femto "openmpi=4.1.5=*external*"

where in this example you should change 4.1.5 to match the version of OpenMPI installed on your cluster / machine.

Getting Started

To get started, see the usage guide.

Acknowledgements

This framework benefited hugely from the work of Psivant's Open Science Fellows.

ATM

The ATM implementation is based upon the work and advice of E. Gallicchio et al:

SepTop

The SepTop implementation is based upon the work and advice of H. M. Baumann, D. L. Mobley et al:

femto's People

Contributors

simonboothroyd avatar

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