Skip to content

This pipeline is executing a RE-EDS run for relative free energy calculations. It can be used for example for calculation of hydration free energies or ligand binding free energies.

License

Notifications You must be signed in to change notification settings

rinikerlab/reeds

Repository files navigation

REEDS

CI Documentation

Replica Exchange - Enveloping Distribution Sampling (RE-EDS) is a method to calculate the relative free energy of multiple states in a system. It can be applied to calculate relative solvation free energies or relative binding free energies with Gromos. One advantage of this method is that no alchemical transition path from one end state to another end state is required thanks to Enveloping Distribution Sampling (EDS) by Christ et al. . EDS allows to explore the end state graph during the simulation with multiple different alchemical transition paths.

The enhanced sampling method Replica Exchange was added by Sidler et al. to speed up the sampling and ease the choice of parameters. Additionally, multiple modules were described by Sidler to allow an automatization of the pipeline. In this repository, we now combined these approaches to an automatic scheme for RE-EDS.

The repository aims to make the RE-EDS pipeline accessible to everyone!

For more on RE-EDS checkout:

Further reading on EDS:

Further reading on free energies:

^ contributed equally

Structure

This Project contains the code for the RE-EDS workflow of the rinikerlab. In the example folder, you can find the system input data for the pipeline, a template script folder, and several jupyter notebooks covering and explaining certain aspects of the pipeline. The reeds folder contains some template files, a function library, and ready-to-use scripts for the RE-EDS steps.

Additional: The submodule folder contains PyGromosTools, which is used extensively in the RE-EDS code. The subfolder tests are used for the automatic code testing mainly applied to the energy offset estimation and the roundtrip optimizers.

Code

The code is written in python3 and requires a compiled version of Gromos. At the current stage, an LSF queue is required to submit the simulation jobs. The required python packages are listed in devtools/conda-envs/full_env.yaml.

Install

Using this repository, clone it (like the command below) into a directory on your machine and add the path to the repo to your python path.

git clone --recurse-submodules <repo url>

Make sure you have the required python packages from devtools/conda-envs/full_env.yaml. You can install the provided env with Anaconda like:

conda env create -f devtools/conda-envs/full_env.yaml

If you want to update the code of the PyGromos submodule, you can do this:

git submodule init
git submodule update

If you're writing code for this repository, please develop it on your own branch first.

 git branch mybranch    #generate your branch
 git checkout mybranch  #switch to your branch
 git merge main   #for adding new features from main to your branch

Copyright

Copyright (c) 2021, Benjamin Ries, Salomé Rieder, Candide Champion

Acknowledgments

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