COVID-19 is an infectious disease caused by the SARS-CoV-2 virus. Worldwide, there have been over 240 million cases reported and close to 5 million deaths. Even though there are now several vaccines available for the disease, there is a clear need for the development of small molecule antivirals. One approach to the rapid discovery of such therapeutics is to apply physics-based methods to structures of the SARS-CoV-2 main protease, a key enzyme in the viral replication process. This talk will focus on the medicinal and computational chemistry driven discovery of main protease inhibitors. The challenges of coordinating this multi-company effort, the use of WaterMap to guide the design of inhibitors, and the use of Free-Energy Perturbation (FEP+) to predict the potencies of compounds to prioritize them for synthesis will be discussed. Biological results for key compounds will be presented.
Funding for this work is provided by Takeda, Schrödinger, Gilead, WuXi, and Google.
Key Learning Objectives:
- The role computational chemistry played in the discovery of main protease inhibitors
- Overcoming challenges of coordinating a multi-company project
- How Schrödinger’s tools assisted in both design and prediction
Who Should Attend:
- Computational Chemists
- Medicinal Chemists
- Drug Discovery Scientists