Unraveling the SARS-CoV-2 Main Protease Mechanism Using Multiscale Methods.
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ABSTRACT:
SUBMITTER: Ramos-Guzman CA
PROVIDER: S-EPMC7556163 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Herein, we investigate the structure and flexibility of the hydrated SARS-CoV-2 main protease by means of 2.0 μs molecular dynamics (MD) simulations in explicit solvent. After having performed electrostatic pKa calculations on several X-ray structures, we consider both the native (unbound) configuration of the enzyme and its noncovalent complex with a model peptide, Ace-Ala-Val-Leu-Gln∼Ser-Nme, which mimics the polyprotein sequence recognized at the active site. For each configuration, we also study their monomeric and homodimeric forms. The simulations of the unbound systems show that the relative orientation of domain III is not stable in the monomeric form and provide further details about interdomain motions, protomer-protomer interactions, inter-residue contacts, accessibility at the catalytic site, etc. In the presence of the peptide substrate, the monomeric protease exhibits a stable interdomain arrangement, but the relative orientation between the scissile peptide bond and the catalytic dyad is not favorable for catalysis. By means of comparative analysis, we further assess the catalytic impact of the enzyme dimerization, the actual flexibility of the active site region, and other structural effects induced by substrate binding. Overall, our computational results complement previous crystallographic studies on the SARS-CoV-2 enzyme and, together with other simulation studies, should contribute to outline useful structure-activity relationships.
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Project description:The Severe Acute Respiratory Syndrome Corona Virus 2 (SARS-CoV-2) pandemic represents a global challenge. SARS-CoV-2's ability to replicate in host cells relies on the action of its non-structural proteins, like its main protease (Mpro). This cysteine protease acts by processing the viruses' precursor polyproteins. As proteases, together with polymerases, are main targets of antiviral drug design, we here have performed biochemical high throughput screening (HTS) with recombinantly expressed SARS-CoV-2 Mpro. A fluorescent assay was used to identify inhibitors in a compound library containing known drugs, bioactive molecules and natural products. These screens led to the identification of 13 inhibitors with IC50 values ranging from 0.2 μM to 23 μM. The screens confirmed several known SARS-CoV Mpro inhibitors as inhibitors of SARS-CoV-2 Mpro, such as the organo-mercuric compounds thimerosal and phenylmercuric acetate. Benzophenone derivatives could also be identified among the most potent screening hits. Additionally, Evans blue, a sulfonic acid-containing dye, could be identified as an Mpro inhibitor. The obtained compounds could be of interest as lead compounds for the development of future SARS-CoV-2 drugs.
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Project description:The unprecedented pandemic of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is threatening global health. The virus emerged in late 2019 and can cause a severe disease associated with significant mortality. Several vaccine development and drug discovery campaigns are underway. The SARS-CoV-2 main protease is considered a promising drug target, as it is dissimilar to human proteases. Sequence and structure of the main protease are closely related to those from other betacoronaviruses, facilitating drug discovery attempts based on previous lead compounds. Covalently binding peptidomimetics and small molecules are investigated. Various compounds show antiviral activity in infected human cells.
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Project description:In silico research was executed on forty unsymmetrical aromatic disulfide derivatives as inhibitors of the SARS Coronavirus (SARS-CoV-1). Density functional theory (DFT) calculation with B3LYP functional employing 6-311 ?+ ?G(d,p) basis set was used to calculate quantum chemical descriptors. Topological, physicochemical and thermodynamic parameters were calculated using ChemOffice software. The dataset was divided randomly into training and test sets consisting of 32 and 8 compounds, respectively. In attempt to explore the structural requirements for bioactives molecules with significant anti-SARS-CoV activity, we have built valid and robust statistics models using QSAR approach. Hundred linear pentavariate and quadrivariate models were established by changing training set compounds and further applied in test set to calculate predicted IC50 values of compounds. Both built models were individually validated internally as well as externally along with Y-Randomization according to the OECD principles for the validation of QSAR model and the model acceptance criteria of Golbraikh and Tropsha's. Model 34 is chosen with higher values of R2, R2 test and Q2cv (R2 ?= ?0.838, R2 test ?= ?0.735, Q2 cv ?= ?0.757). It is very important to notice that anti-SARS-CoV main protease of these compounds appear to be mainly governed by five descriptors, i.e. highest occupied molecular orbital energy (EHOMO), energy of molecular orbital below HOMO energy (EHOMO-1), Balaban index (BI), bond length between the two sulfur atoms (S1S2) and bond length between sulfur atom and benzene ring (S2Bnz). Here the possible action mechanism of these compounds was analyzed and discussed, in particular, important structural requirements for great SARS-CoV main protease inhibitor will be by substituting disulfides with smaller size electron withdrawing groups. Based on the best proposed QSAR model, some new compounds with higher SARS-CoV inhibitors activities have been designed. Further, in silico prediction studies on ADMET pharmacokinetics properties were conducted.
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