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bioRxiv : the preprint server for biology · 2026

Systematic exploration of predicted quaternary structures within pandemic-relevant viral proteomes.

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Han Yewon, Narain Riya, Abbara Razan, Afonso Marcelo Querino Lima, Austin Jeannie, Bertoni Damian, Cha Sooyoung, Cowen-Rivers Alexander I, Ellaway Joseph, Fransos Davide, Gion Kyle, Hsu Darren, Hulo Chantal, Kim Rachel Seongeun, Kovalevskiy Oleg, Laydon Agata, Mason Jack, Nair Sreenath, Paramval Urmila, Patel Nilkanth, Patel Risha, Pidruchna Ivanna, Ratcliff Jeremy, Tsenkov Maxim, Venanzi Niccolò Alberto Elia, Vollmar Melanie, Wahome Newton, Wong Elisa L H, Fleming Jennifer, Velankar Sameer, Mirdita Milot, Le Mercier Philippe, Steinegger Martin, Dallago Christian, Grove Joe

Аннотация

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.

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

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