Unveiling the molecular mechanism of SARS-CoV-2 main protease inhibition from 92 crystal structures

Abstract

Currently, there is no effective antiviral drugs nor vaccine for coronavirus disease 2019 caused by acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Due to its high conservativeness and low similarity with human genes, SARS-CoV-2 main protease (M pro ) is one of the most favorable drug targets. However, the current understanding of the molecular mechanism of M pro inhibition is limited by the lack of reliable binding affinity ranking and prediction of existing structures of M pro -inhibitor complexes. This work integrates mathematics and deep learning (MathDL) to provide a reliable ranking of the binding affinities of 92 SARS-CoV-2 M pro inhibitor structures. We reveal that Gly143 residue in M pro is the most attractive site to form hydrogen bonds, followed by Cys145, Glu166, and His163. We also identify 45 targeted covalent bonding inhibitors. Validation on the PDBbind v2016 core set benchmark shows the MathDL has achieved the top performance with Pearson's correlation coefficient (Rp) being 0.858. Most importantly, MathDL is validated on a carefully curated SARS-CoV-2 inhibitor dataset with the averaged Rp as high as 0.751, which endows the reliability of the present binding affinity prediction. The present binding affinity ranking, interaction analysis, and fragment decomposition offer a foundation for future drug discovery efforts.

A Blueprint for High Affinity SARS-CoV-2 Mpro Inhibitors from Activity-Based Compound Library Screening Guided by Analysis of Protein Dynamics

“…This clearly emerges from an analysis of the SARS-CoV-2 Mpro binding pocket's conformational changes (performed here) across the majority of the 196 X-ray crystal structures available in the Protein Data Bank up to September 30th 2020. 15,30−32 This flexibility makes a rational drug-design approach extremely challenging: 15,33 the screening potential of Mpro conformational space is too large, too flexible, and unpredictable, and the actual available binding space can differ significantly from ligand to ligand. 15,30,34 It is therefore imperative to identify the relationship among SARS-CoV-2 conformational space, flexibility, druggability, and ligand binding.…”