Systematic exploration of predicted quaternary structures within pandemic-relevant viral proteomes
Year: 2026
Type: preprint
Abstract: Mechanistic understanding of viral protein-protein interactions enables global health security and pandemic preparedness, yet experimental characterisation remains difficult, costly, and often restricted to specialised laboratories. Here, we describe an in silico campaign using AlphaFold2 and AlphaFold-Multimer to predict monomers and dimer structures within 2,812 viral proteomes from 23 viral families relevant to human health. We report high-confidence predicted structures of 5,279 hetero-, and 2,749 homo-dimers. Structural clustering of interfaces reduces the set fivefold to 1,598 consolidated by form and function, of which 471 (29.5%) lacked detectable similarity to experimentally determined interfaces in the PDB. These clusters yielded two notable findings: new data on vaccinology-relevant glycoproteins, and accurate prediction of the specificity and cleavage-site recognition of viral proteases, which are targets for anti-viral development. Viral monomers and high-confidence dimers are available for interactive browsing in the Pandemic Preparedness Portal of the AlphaFold Database ( https://alphafold.ebi.ac.uk/ ), and the full dataset is available for bulk download.
Authors: Yewon Han, Riya Narain, Razan Abbara, Marcelo Querino Lima Afonso, Jeannie Austin, Damian Bertoni, Sooyoung Cha, Alexander I. Cowen-Rivers, Joseph Ellaway, Davide Fransos, Kyle Gion, Darren Hsu, Chantal Hulo, Rachel Seongeun Kim, Oleg Kovalevskiy, Agata Laydon, Jack Mason, Sreenath Nair, Urmila Paramval, Nilkanth Patel, Risha Patel, Ivanna Pidruchna, Jeremy Ratcliff, Maxim Tsenkov, Niccolò Alberto Elia Venanzi, Melanie Vollmar, Newton Wahome, Elisa L.H. Wong, Jennifer Fleming, Sameer Velankar, Milot Mirdita, Philippe Le Mercier, Martin Steinegger, Christian Dallago, Joe Grove
Institutions: Seoul National University, Nvidia (United States), Stanford University, European Bioinformatics Institute, Google DeepMind (United Kingdom), Coalition for Epidemic Preparedness Innovations, Coalition for Epidemic Preparedness Innovations, Sungkyunkwan University, SIB Swiss Institute of Bioinformatics, Duke University, MRC University of Glasgow Centre for Virus Research
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
Funders: National Science Foundation, Nvidia, European Bioinformatics Institute, European Molecular Biology Laboratory, UK Research and Innovation, DeepMind, University of Glasgow, National Research Foundation of Korea, Novo Nordisk, Ministry of Science and ICT, South Korea, National Institutes of Health, Medical Research Council, Biotechnology and Biological Sciences Research Council, Staatssekretariat für Bildung, Forschung und Innovation, National Institute of Allergy and Infectious Diseases
OpenAlex ID: W7215898934