In Silico Optimization of Inhibitors of the 3-Chymotrypsin-like Protease of SARS-CoV-2
Issouf Fofana, Brice Dali, Mawa Koné, Katarina Sujova, Eugene Megnassan, Stanislav Miertus, Vladimir Frecer
TL;DR
This study uses computer modeling to design better inhibitors for a key SARS-CoV-2 enzyme, potentially leading to more effective treatments for COVID-19.
Contribution
The study introduces a novel QSAR pharmacophore model and identifies new IPCL analogues with improved predicted potency against SARS-CoV-2 3CLpro.
Findings
A QSAR model explained 92% of the variation in 3CLpro inhibition data using free energy calculations.
39 promising IPCL analogues were identified from a virtual library of over 567,000 compounds.
The best inhibitor candidate IPCL 80-27-74-4 has a predicted IC50 of 0.8 nM, significantly better than known IPCLs.
Abstract
In this study, new improved inhibitors of the viral enzyme 3-chymotrypsin-like protease (3CLpro) were designed using structure-based drug design techniques in an effort to discover more effective treatment of coronavirus disease 2019 (COVID-19). Three-dimensional models of 3CLpro–inhibitor complexes were prepared by in situ modification of the crystal structure of the submicromolar covalent inhibitor IPCL6 for a set of 25 known inhibitors with published inhibitory potencies (IC50exp). The QSAR model was prepared with a reasonable correlation between the calculated free energies of formation of the 3CLpro-IPCL complex (∆∆Gcom) and the experimentally determined activities IC50exp, which explained approximately 92% of the variation in the 3CLpro inhibition data. A similar agreement was achieved for the QSAR pharmacophore model (PH4) built on the basis of the active conformations of the…
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Taxonomy
TopicsComputational Drug Discovery Methods · Protein Structure and Dynamics · Pharmacological Receptor Mechanisms and Effects