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Novel covalent and non-covalent complex-based pharmacophore models of SARS-CoV-2 main protease (Mpro) elucidated by microsecond MD simulations

نماذج جديدة من الحاملات الدوائية التساهمية وغير التساهمية القائمة على المركب من الأنزيم البروتيني الرئيسي لفيروس سارس- كوف-2 (MPRO) التي تم توضيحها من خلال عمليات محاكاة MD للميكروثانية
Authors: Yasser Hayek-Orduz; Andrés Felipe Vásquez; María F. Villegas-Torres; Paola A. Caicedo; Luke E.K. Achenie; Andrés Fernando González Barrios;

Novel covalent and non-covalent complex-based pharmacophore models of SARS-CoV-2 main protease (Mpro) elucidated by microsecond MD simulations

Abstract

AbstractAs the world enters its second year of the pandemic caused by SARS-CoV-2, intense efforts have been directed to develop an effective diagnosis, prevention, and treatment strategies. One promising drug target to design COVID-19 treatments is the SARS-CoV-2 Mpro. To date, a comparative understanding of Mprodynamic stereoelectronic interactions with either covalent or non-covalent inhibitors (depending on their interaction with a pocket called S1’ or oxyanion hole) has not been still achieved. In this study, we seek to fill this knowledge gap using a cascade in silico protocol of docking, molecular dynamics simulations, and MM/PBSA in order to elucidate pharmacophore models for both types of inhibitors. After docking and MD analysis, a set of complex-based pharmacophore models was elucidated for covalent and non-covalent categories making use of the residue bonding point feature. The highest ranked models exhibited ROC-AUC values of 0.93 and 0.73, respectively for each category. Interestingly, we observed that the active site region of Mproprotein–ligand complex undergoes large conformational changes, especially within the S2 and S4 subsites. The results reported in this article may be helpful in virtual screening (VS) campaigns to guide the design and discovery of novel small-molecule therapeutic agents against SARS-CoV-2 Mproprotein.

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Keywords

Computational chemistry, Organic chemistry, Combinatorial chemistry, Infectious disease (medical specialty), FOS: Health sciences, Biochemistry, Gene, Computational biology, Stereochemistry, Pathology, Disease, Coronavirus 3C Proteases, Heterocyclic Compounds for Drug Discovery, Q, R, Molecular Docking, Molecular Docking Simulation, Cysteine Endopeptidases, Chemistry, Infectious Diseases, Computational Theory and Mathematics, Physical Sciences, Medicine, Computational Methods in Drug Discovery, Virtual screening, Science, Docking (animal), Nursing, Molecular Dynamics Simulation, Coronavirus Disease 2019 Research, Molecular dynamics, Antiviral Agents, Article, Covalent bond, FOS: Chemical sciences, Health Sciences, Humans, Protease Inhibitors, Biology, Pharmacophore, SARS-CoV-2, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Organic Chemistry, In silico, COVID-19 Drug Treatment, Coronavirus disease 2019 (COVID-19), Computer Science, Small molecule

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
13
Top 10%
Average
Top 10%
Green
hybrid