This paper introduces a new 20-letter alphabet, TEA, derived from protein language models, enabling efficient homology searches comparable to structure-based methods without structural data.

bioRxiv · Nov 27, 2025 · PreprintBioinformatics

AlphaPulldown2 - A General Pipeline for High-Throughput Structural Modeling

Dmitry S. Molodenskiy, Valentin J. Maurer, Dingquan Yu, Grzegorz Chojnowski, Stefan Bienert, Gerardo Tauriello, Konstantin Gilep, Torsten F. Schwede, Jan Kosiński

AlphaPulldown2 provides a pipeline for high-throughput protein structural modeling with automated workflows and improved data management.

Bioinformatics · Mar 1, 2025Peer-reviewedBioinformatics

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

Brinda Kizhakke Vallat, Gerardo Tauriello, Stefan Bienert, Juergen Haas, Benjamin Webb, Augustin Žídek, Wei Hui Zheng, Ezra Peisach, Dennis W. Piehl, Ivan Anischanka, Ian Sillitoe, James L. Tolchard, Mihály Váradi, David A. Baker, Christine Anne Orengo, , John Westbrook

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

Journal of Molecular Biology · Feb 22, 2023Peer-reviewedBioinformatics

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

Mihály Váradi, Sreenath Sasidharan Nair, Ian Sillitoe, Gerardo Tauriello, Stephen Anyango, Stefan Bienert, Clemente Borges, Mandar Deshpande, Tim Green, Demis Hassabis, András Hatos, Tamás Hegedűs, Maarten L. Hekkelman, Robbie P. Joosten, John Jumper, , Sameer S Velankar

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

GigaScience · Jan 1, 2022Peer-reviewedBioinformatics