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AI-guided pipeline for protein–protein interaction drug discovery identifies a SARS-CoV-2 inhibitor

  • Protein–protein interactions (PPIs) offer great opportunities to expand the druggable proteome and therapeutically tackle various diseases, but remain challenging targets for drug discovery. Here, we provide a comprehensive pipeline that combines experimental and computational tools to identify and validate PPI targets and perform early-stage drug discovery. We have developed a machine learning approach that prioritizes interactions by analyzing quantitative data from binary PPI assays or AlphaFold-Multimer predictions. Using the quantitative assay LuTHy together with our machine learning algorithm, we identified high-confidence interactions among SARS-CoV-2 proteins for which we predicted three-dimensional structures using AlphaFold-Multimer. We employed VirtualFlow to target the contact interface of the NSP10-NSP16 SARS-CoV-2 methyltransferase complex by ultra-large virtual drug screening. Thereby, we identified a compound that binds to NSP10 and inhibits its interaction with NSP16, while also disrupting the methyltransferase activity of the complex, and SARS-CoV-2 replication. Overall, this pipeline will help to prioritize PPI targets to accelerate the discovery of early-stage drug candidates targeting protein complexes and pathways.

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Author:Philipp TrepteORCiD, Christopher SeckerORCiD, Julien OlivetORCiD, Jeremy BlavierORCiD, Simona Kostova, Sibusiso B MasekoORCiD, Igor Minia, Eduardo Silva RamosORCiD, Patricia Cassonnet, Sabrina Golusik, Martina Zenkner, Stephanie Beetz, Mara J Liebich, Nadine Scharek, Anja SchützORCiD, Marcel SperlingORCiD, Michael LisurekORCiD, Yang Wang, Kerstin Spirohn, Tong Hao, Michael A CalderwoodORCiD, David E HillORCiD, Markus LandthalerORCiD, Soon Gang ChoiORCiD, Jean-Claude TwizereORCiD, Marc VidalORCiD, Erich E WankerORCiD
Document Type:Article
Parent Title (English):Molecular Systems Biology
First Page:428
Last Page:457
Publisher:Springer Science and Business Media LLC
Tag:Applied Mathematics; Computational Theory and Mathematics; General Agricultural and Biological Sciences; General Biochemistry, Genetics and Molecular Biology; General Immunology and Microbiology; Information Systems
Date of first Publication:2024/03/11
Page Number:30
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