We present a de novo molecular design strategy that leverages artificial intelligence (AI) to discover new therapeutic agents against SARS-CoV-2. Several hundred new drug candidates were identified with the potential to target COVID-19.
Significance and Impact
The new drug candidates outperform existing candidates against COVID-19. Further experiments can validate the in silico AI predictions.
- A Monte Carlo tree search algorithm combined with a multitask neural network surrogate model was used to generate the drug molecules.
- Binding affinity of ligands to the virus and the virus-host interface were used as a descriptor.
- The Center for Nanoscale Materials (CNM) Carbon High Performance Computing Cluster, the Argonne Leadership Computing Facility and the National Energy Research Scientific Computing Center were used.
Work was performed in part at the CNM.
About Argonne’s Center for Nanoscale Materials
The Center for Nanoscale Materials is one of the five DOE Nanoscale Science Research Centers, premier national user facilities for interdisciplinary research at the nanoscale supported by the DOE Office of Science. Together the NSRCs comprise a suite of complementary facilities that provide researchers with state-of-the-art capabilities to fabricate, process, characterize and model nanoscale materials, and constitute the largest infrastructure investment of the National Nanotechnology Initiative. The NSRCs are located at DOE’s Argonne, Brookhaven, Lawrence Berkeley, Oak Ridge, Sandia and Los Alamos National Laboratories. For more information about the DOE NSRCs, please visit https://science.osti.gov/User-Facilities/User-Facilities-at-a-Glance.
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