MD-SAPT is a Python package for analyzing molecular dynamics (MD) trajectories using a quantum method called symmetry-adapted perturbation theory (SAPT).

We presented it at the American Chemical Society (ACS) Spring 2022 conference in San Diego, at the Sci-Mix and Computational Chemistry poster sessions. At the Computational Chemistry session, we were one of only 7 posters that got to the second round of judging. Here’s my post detailing my trip.

If you’re wondering why I’m working on this random chemistry project despite being a CS major, that’s because my chemistry major girlfriend Alia Lescoulie needed help setting up the CI/CD pipeline, packaging, and package/documentation deployment, so I helped her out and kinda got dragged into it.

My contributions

• Providing my gfdesk server as a development machine
• Harmonizing the conda development environment so that it works on MacOS and Linux
• Fixing the CI/CD pipeline
• Setting up the Anaconda package build recipe so that all you have to do to install it is run conda install -c psi4/label/dev -c conda-forge mdsapt
• Setting up the readthedocs.io deployment
• Various code optimizations, such as reducing readthedocs.io deployment times form 500s to 100s