Augustin Žídek

Designing enzymes for new-to-nature chemistry and non-natural substrates with AlphaProtein Novo

This paper introduces AlphaProtein Novo, a machine-learning pipeline for de novo enzyme design that outperforms natural sequence mining in creating enzymes for new-to-nature chemistry and substrates.

ModelCIF: An extension of PDBx/mmCIF data representation for computed structure models

ModelCIF extends the PDBx/mmCIF standard to represent predicted 3D protein models, enabling FAIR data sharing for computational structural biology.

3D-Beacons: Decreasing the gap between protein sequences and structures through a federated network of protein structure data resources

3D-Beacons provides a federated network to unify access to protein structure data from multiple sources, enabling comparative analysis of models.

Protein complex prediction with AlphaFold-Multimer

AlphaFold trained on complexes, with cross-chain paired alignments and symmetry-aware losses, gets 70% of recent heteromeric interfaces acceptable or better (DockQ ≥ 0.23), 27 points above linker-joined AlphaFold.

Highly accurate protein structure prediction with AlphaFold

AlphaFold, an attention network over sequence alignments and residue pairs, rivaled experimental accuracy in most CASP14 cases: median backbone r.m.s.d.95 0.96 Å versus 2.8 Å for the runner-up.