GEMS: Enhancing Generalizable Binding Affinity Prediction by Removing Data Leakage and Integrating Language Model Embeddings into Graph Neural Networks
David Graber, Peter Stockinger, Fabian Meyer, Siddhartha Mishra, Claus Horn, Rebecca Buller
The paper introduces GEMS, a graph neural network model that improves binding affinity prediction by removing data leakage and integrating language model embeddings, achieving high performance on independent test datasets.
bioRxiv · Dec 9, 2024 · PreprintBioinformatics