AI-Aided Design of Novel Inhibitors Against SARS-CoV-2

Explore the cutting-edge application of artificial intelligence in drug discovery for COVID-19 treatment in this 36-minute conference talk by Dr. Dong Xu at the Toronto Machine Learning Series. Learn about the development of a novel advanced deep Q-learning network combined with fragment-based drug design to generate potential lead compounds targeting the SARS-CoV-2 3C-like main protease (3CLpro or Mpro). Discover how this AI-driven approach addresses the urgent need for new chemical entities after the failure of drug repurposing efforts. Gain insights into the structure-based optimization policy used to obtain derivatives from lead compounds and access the resulting molecular library of 47 AI-generated lead compounds and related derivatives. Understand the extension of this method to design peptide-based drugs against SARS-CoV-2, offering valuable resources for researchers in the development of potential COVID-19 treatments.