Till Siebenmorgen

The paper trains a machine-learning model on native protein structures to predict interaction preferences and energetics without using affinity or mutation labels, achieving performance comparable to existing methods on a benchmark.

The paper introduces a machine learning model that learns spatial preference maps for drug-receptor interactions to guide drug discovery.

The paper introduces MISATO, a dataset combining quantum mechanics properties and molecular dynamics simulations of protein-ligand complexes to support structure-based drug discovery.