Unveiling the molecular mechanism of SARS-CoV-2 main protease inhibition from 137 crystal structures using algebraic topology and deep learning
Duc Duy Nguyen, Kaifu Gao, Jiahui Chen, Rui Wang, Guo‐Wei Wei
Abstract
is the most attractive site to form hydrogen bonds, followed by Glu166, Cys145, and His163. We also identify 71 targeted covalent bonding inhibitors. MathDL was validated on the PDBbind v2016 core set benchmark and a carefully curated SARS-CoV-2 inhibitor dataset to ensure 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.
Topics & Concepts
ProteaseRanking (information retrieval)Topology (electrical circuits)Algebraic numberDecompositionMechanism (biology)Computational biologyAlgebraic topologySevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)ChemistryCoronavirus disease 2019 (COVID-19)StereochemistryBiologyComputer scienceEnzymeArtificial intelligenceMathematicsBiochemistryPhysicsCombinatoricsMedicinePure mathematicsDiseaseQuantum mechanicsInfectious disease (medical specialty)Organic chemistryMathematical analysisHomotopyPathologyComputational Drug Discovery MethodsSynthesis and biological activityCancer therapeutics and mechanisms