A Computational Pipeline to Identify and Characterize Binding Sites and Interacting Chemotypes in SARS-CoV-2

Minimizing the human and economic costs of the COVID-19pandemicand future pandemics requires the ability to develop and deploy effectivetreatments for novel pathogens as soon as possible after they emerge.To this end, we introduce a new computational pipeline for the rapididentification and characterization of binding sites in viral proteinsalong with the key chemical features, which we call chemotypes, ofthe compounds predicted to interact with those same sites. The compositionof source organisms for the structural models associated with an individualbinding site is used to assess the site's degree of structuralconservation across different species, including other viruses andhumans. We propose a search strategy for novel therapeutics that involvesthe selection of molecules preferentially containing the most structurallyrich chemotypes identified by our algorithm. While we demonstratethe pipeline on SARS-CoV-2, it is generalizable to any new virus,as long as either experimentally solved structures for its proteinsare available or sufficiently accurate predicted structures can beconstructed.