Hannes Stark

BoltzProt-1 improves nanobody design for protein targets by increasing hit rates and developability compared to existing methods.

An all-atom diffusion model unifying biomolecular structure prediction and sequence-structure generation designs experimentally validated nanobodies, mini-proteins, and linear or cyclic peptides across 26 diverse targets.

Boltz-2 predicts protein–ligand affinity from its co-folded structures, nearing free-energy perturbation accuracy (average Pearson 0.66 on a 4-target FEP+ subset) at over 1000× lower compute.

PLINDER provides a large, annotated PLI dataset with diverse annotations and improved evaluation splits to better assess computational methods for drug design.

PINDER provides a benchmark dataset for evaluating protein-protein interaction docking models, revealing overestimation of performance on leaky test sets and showing improvements with interface-clustered training.