Drug-Repurposing for Covid-19 with 3D-Aware Machine Learning
Award from the COVID-19 HPC Consortium
Investigators: Rafael Gomez-Bombarelli (Massachusetts Institute of Technology), Simon Axelrod (Harvard University)
Novel active therapeutics against coronaviruses like the one responsible for Covid-19 (SARS- CoV2) are in urgent need. New discovery of small-molecule drugs, however, is slow and costly. Many promising molecules that strongly interact with their biological target fail as drugs because of poor processing within the body or toxicity that is only discovered late in their development. Furthermore, the synthesis-experimentation loop is typically slow. Repurposing known drugs for the treatment of a new disease, such as Covid-19, effectively bypasses many of these challenges, since the drugs are already FDA approved.
Rafael Gomez-Bombarelli from MIT and Simon Axelrod from Harvard are exploring whether the repurposing of drugs for COVID-19 treatment can be accelerated with a combination of physical simulation and machine learning (ML). They are using affordable electronic structure simulations to calculate molecular conformations and train 3D-based message-passing neural networks from existing molecular screens against the related SARS-CoV1 and SARS-CoV2 data as it becomes available.
About NERSC and Berkeley Lab
The National Energy Research Scientific Computing Center (NERSC) is a U.S. Department of Energy Office of Science User Facility that serves as the primary high-performance computing center for scientific research sponsored by the Office of Science. Located at Lawrence Berkeley National Laboratory, the NERSC Center serves more than 7,000 scientists at national laboratories and universities researching a wide range of problems in combustion, climate modeling, fusion energy, materials science, physics, chemistry, computational biology, and other disciplines. Berkeley Lab is a DOE national laboratory located in Berkeley, California. It conducts unclassified scientific research and is managed by the University of California for the U.S. Department of Energy. »Learn more about computing sciences at Berkeley Lab.