The novel Wuhan coronavirus (SARS-CoV-2) has been sequenced, and the virus shares substantial similarity with SARS-CoV. Here, using a computational model of the spike protein (S-protein) of SARS-CoV-2 interacting with the human ACE2 receptor, we make use of the world's most powerful supercomputer, SUMMIT, to enact an ensemble docking virtual high-throughput screening campaign and identify small-molecules which bind to either the isolated Viral S-protein at its host receptor region or to the S protein-human ACE2 interface. We hypothesize the identified small-molecules may be repurposed to limit viral recognition of host cells and/or disrupt host-virus interactions. A ranked list of compounds is given that can be tested experimentally
Additional snippet:
Here we combine restrained temperature replica-exchangemolecular dynamics (restrained T-REMD) simulations with virtual high-throughput screening in an ensemble docking campaign to identify well-characterized drugs, metabolites, and/or natural products that may disrupt S-protein:ACE2 receptor interface stability or the ability of the S-protein to recognize the ACE2 receptor. From this ensemble docking campaign,we provide a ranking of the predicted binding affinities ofover 8000 drugs, metabolites, and natural products (and their isomers)with regards to the COVID-19 S-protein and the S-protein:ACE2 receptor. Further, we highlight seven of our top ranked compounds, which are currently available and have had either regulatory approval as drugs or have had multiple prior studies which indicating high-potential for therapeuticuse