Discovery of inhibitors of the SARS-CoV-2 S-protein through drug computational drug repurposing

30 June 2022, Version 1
This content is a preprint and has not undergone peer review at the time of posting.


We present here a computational multistep procedure that tries to find compounds from the Selleck FDA approved drugs and the Selleck database of Natural Products able to interact with the S-protein of SARS-CoV-2 and inhibit its interactions with human ACE2. The multistep procedure uses a sieving approach, starting from low cost computational methods that filter out compounds to pass to next, more computationally expense, stages. A standard docking is applied together with a pharmacophore biased one, and protein flexibility is taken into account from a clustering of four 3 μs trajectories. After visual inspection of the final candidates we propose a list of 10 compounds to be essayed experimentally.



Supplementary materials

MMGBSA binding energy versus time
MMGBSA binding energy versus time for each of the 4 MD runs (3 μs) obtained for RBD of SARS-CoV-2 + ACE2 (a) and RBD of SARS-CoV-1 + ACE2 (b)


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