repESP is a program used in computational chemistry to investigate different methods of assigning partial charges. It takes the name from reproducing the (molecular) electrostatic potential (ESP) from partial charges. Partial charges can be extracted from the output of Gaussian 09 or provided by the user. Current capabilities of the program include:

• comparing the reproduced ESP to the 'true' ESP (operations on cube files)
• evaluating fit quality on a provided set of fitting points
• visualization of fitting points around a molecule, coloured by ESP value or error
• averaging (or, for ESP-based methods, equivalencing) charges of symmetry-related and rapidly-exchanging atoms

The program was developed as part of Jan Szopinski's MSci project at the Hunt Research Group, Imperial College London. The program was used to investigate and develop the following novel concepts:

• charge 'flexibility'
• 'adjusted rational' charges

repESP implemented a lot of functionalities, which can be used to examine the various methods of assigning partial charges. Many of these functionalities are exposed to users as command line (CLI) scripts and are easy to use. The scripts perform well-defined, modular tasks and can be woven together to create one's own work flow (Unix style). The following chart presents some of the repESP capabilities:

The monospaced text above arrows shows the names of the relevant command line scripts.

When the out-of-the-box functionalities are not sufficient or flexible enough, users can create their own scripts by using the repESP library.

The overview of the available scripts can be found here and the command line interface help can be found here. Library documentation is hosted at http://jszopi.github.io/repESP.

The following instructions are for Unix-like systems, like MacOS and Linux. There shouldn't be anything stopping repESP from running on Windows but that hasn't been tested.

repESP needs input from computational chemistry software to obtain the ESP and partial charges. Currently only the output from Gaussian 09 is known to be recognized, please open issues for other Gaussian versions or other software. Further, to run repESP you need Python 3.7 and two other free programs, which need to be in your PATH.

resp is a free program necessary to perform ESP-fitting. Download link can be found at the bottom of this documentation page. To install you'll have to compile the Fortran source and put the resulting binary in your PATH.

resp and repESP need information about atom equivalence in the form of .respin files. AmberTools is a suite of free programs (link). However, it requires compilation from C, C++ and Fortran sources, which proved tricky on MacOS.

To create the necessary input for a methane molecule, first create the .ac file from Gaussian .log using antechamber:

antechamber -i methane.log -fi gout -o methane.ac -fo ac

Then run respgen twice:

respgen -i methane.ac -o methane.respin1 -f resp1
respgen -i methane.ac -o methane.respin2 -f resp2

Installing repESP is standard and simple:

1. Choose and go to an installation directory (e.g. ~/bin)
2. Get the code: git clone https://github.com/jszopi/repESP
3. From inside the repESP directory run: pip3 install .

With the following caveats regarding the final point:

• While version 0.2.0 is being actively developed it is recommended to stay up-to-date with the latest code on the master branch. Passing -e to pip3 install will ensure that the repESP version installed reflects what's in your local git repo. To later update the code to latest version run: git fetch --all ; git pull.
• If you want to generate documentation, you'll need to append [docs] to the install command, i.e. run pip3 install .[docs] instead.

repESP is free software released under the Gnu Public Licence version 3. All contributions are very welcome, from improving the content of this overview to tweaking the code.

There's still plenty you can do! First, have a look at GitHub's "How to contribute".

• If you'd like to improve any of the documentation, fork this repository and submit a pull request.

• If something doesn't work or should be improved, open an issue here on GitHub
• If you think a new feature would be nice, open an issue
• If you need a feature for your project (i.e. within a certain time frame), contact the maintainer directly to discuss whether it can be implemented time. Then we'll open an issue.

This program needs some work to get where it wants to be. If you want to help out, please coordinate with the maintainer.