Description from GitHub: "This repository contains code and data to generate the figures presented in Setton, Hadi, Choo et al. Nature 2023. Most figures (aside from those which rely on random forest training) are found in ./notebooks/figures.ipynb. The remaining figures (Figure 5, Extended Data Figure 8, and Extended Data Figure 9) are found in ./notebooks/random_forest.ipynb. We have also made...

Description from Zenodo: "SPICE (Small-Molecule/Protein Interaction Chemical Energies) is a collection of quantum mechanical data for training potential functions. The emphasis is particularly on simulating drug-like small molecules interacting with proteins. It is described in this publication: Peter Eastman, Pavan Kumar Behara, David L. Dotson, Raimondas Galvelis, John E. Herr, Josh T. Horton,...

Description from GitHub: "This directory contains the five equivariant transformer models described in the paper Peter Eastman, Pavan Kumar Behara, David L. Dotson, Raimondas Galvelis, John E. Herr, Josh T. Horton, Yuezhi Mao, John D. Chodera, Benjamin P. Pritchard, Yuanqing Wang, Gianni De Fabritiis, and Thomas E. Markland. "SPICE, A Dataset of Drug-like Molecules and Peptides for Training Machine...

Description from GitHub: "This repository contains scripts and data files used in the creation of the SPICE dataset. It does not contain the dataset itself. It does contain a collection of QM data for training potential functions."