In silico identification of a new potential drug-binding pocket on the surface of the receptor-binding domain of the SARS-CoV-2 S-glycoprotein

SARS-CoV-2 is an emerging pathogen that caused the largest pandemic in modern history in 2020-2023. The surface S-glycoprotein, namely its RBD, significantly determines the pathogenesis of this virus: it allows SARS-CoV-2 to target human cells and ensures its internalization. Thus, the search for RBD inhibitors is currently considered a promising strategy for the drug development against COVID-19. In this work, we identified a new pocket on the RBD surface that could potentially bind small drug-like ligands. The FDA-approved drug compound library obtained from e-Drug3D was used as a source of drug-like chemical structures. The compounds were initially filtered by molecular weight (100-500 Da) using the Open Babel GUI. This allowed to reduce the size of the library from 2,118 to 1,749 compounds. Next, all filtered structures were docked to the RBD (PDB ID: 7T9L) using AutoDock Vina 1.1.2. The docking area was the entire RBD. Results and conclusions: We obtained a map of the uneven placement of ligands with different affinities to the target. The pocket formed by amino acids R454, R457, K458, S459, D467, S469, E471, I472, Y473, Q474, P479, N481, G482 and P491 was identified close to the functionally important ACE2-binding site of the RBD. It was able to interact with 128 ligands with the best estimated affinity of -7.8 kcal/mol for Oxymetholone. The latter interacted with the pocket through its hydroxyl and keto groups.

The study was funded under grant № 0125U002921 (contract 37/10-2025).