Generative strategies for multi-target drug design: generating Mpro Pan-inhibitors
Guallar, Víctor, Vilalta Mor, Julia, Filella Merce, Isaac · UPCommons institutional repository (Universitat Politècnica de Catalunya) · 2024
Polypharmacological drugs are molecules capable of simultaneously affecting multiple targets. In the field of drug design, generative AI can be employed to train models on extensive chemical databases, enabling the generation of unseen molecules with specific properties. The presented project aims to leverage the multiobjective capability of a generative model (GM) workflow to design molecules with affinity towards multiple targets, thereby seeking to design polypharmacological drugs. Specifically, we will utilize the vast data collected during the COVID-19 pandemic and the relatively straightforward nature of viruses, to design polypharmacological inhibitors with activity against the main protease (Mpro) of SARS-CoV-2, SARS-CoV, and MERSCoV. Using this approach, the newly designed compounds will serve as a starting point to fight against new SARS-CoV-2 variants and new virulent coronavirus species.