Claus Horn

This paper introduces Geometric Protein Optimization (GPO), an AI framework that improves protein-ligand binding affinity by optimizing global geometry through diverse substitutions, achieving significant in silico improvements.

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.