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

ABSTRACT: 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 and 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

SUBMITTER: Trepte P 

PROVIDER: S-EPMC10312674 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature