SO3LR-SF is out: a physics-based, explainable scoring function for protein–ligand binding

Our preprint “Explainable ML force-field for evaluating protein–ligand binding energy using SO3LR” is now out on ChemRxiv!

In our SO3LR-SF project, we introduce a fast and explainable scoring function for protein–ligand binding built on the pretrained SO3LR machine-learned force field. It brings near-quantum-mechanical accuracy to structure-based drug design at a fraction of the cost, and shows why a ligand scores the way it does. The code is available on GitHub.

Many thanks to our collaborators Sergio Suárez-Dou, Adil Kabylda, and Alexandre Tkatchenko (University of Luxembourg) for working together on this project.