GEMS – Enhancing Generalizable Binding Affinity Prediction by Removing Data Leakage and Integrating Language Model Embeddings into Graph Neural Networks

For fast reproduction of our results, we provide PyTorch datasets of precomputed interaction graphs for the entire PDBbind database on Zenodo. To enable quick establishment of leakage-free evaluation setups with PDBbind, we also provide pairwise similarity matrices for the entire PDBbind dataset on Zenodo. Version 2 - Updated to improve the accuracy of Tanimoto Scores in the pairwise similarity matrices, which also caused minor changes in the composition of PDBbind CleanSplit.