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QSAR study of unsymmetrical aromatic disulfides as potent avian SARS-CoV main protease inhibitors using quantum chemical descriptors and statistical methods.

ABSTRACT: 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 (E_HOMO), energy of molecular orbital below HOMO energy (E_HOMO-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.

SUBMITTER: Chtita S

PROVIDER: S-EPMC7857023 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

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QSAR study of unsymmetrical aromatic disulfides as potent avian SARS-CoV main protease inhibitors using quantum chemical descriptors and statistical methods.

Chtita Samir S Belhassan Assia A Bakhouch Mohamed M Taourati Abdelali Idrissi AI Aouidate Adnane A Belaidi Salah S Moutaabbid Mohammed M Belaaouad Said S Bouachrine Mohammed M Lakhlifi Tahar T

Chemometrics and intelligent laboratory systems : an international journal sponsored by the Chemometrics Society 20210203

<i>In silico</i> 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, resp ...[more]

PMID: 33558778

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Project description:COVID-19 pandemic caused by very severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) agent is an ongoing major global health concern. The disease has caused more than 452 million affected cases and more than 6 million death worldwide. Hence, there is an urgency to search for possible medications and drug treatments. There are no approved drugs available to treat COVID-19 yet, although several vaccine candidates are already available and some of them are listed for emergency use by the world health organization (WHO). Identifying a potential drug candidate may make a significant contribution to control the expansion of COVID-19. The in vitro biological activity of asymmetric disulfides against coronavirus through the inhibition of SARS-CoV-2 main protease (Mpro) protein was reported. Due to the lack of convincing evidence those asymmetric disulfides have favorable pharmacological properties for the clinical treatment of Coronavirus, in silico evaluation should be performed to assess the potential of these compounds to inhibit the SARS-CoV-2 Mpro. In this context, we report herein the molecular docking for a series of 40 unsymmetrical aromatic disulfides as SARS-CoV-2 Mpro inhibitor. The optimal binding features of disulfides within the binding pocket of SARS-CoV-2 endoribonuclease protein (Protein Data Bank [PDB]: 6LU7) was described. Studied compounds were ranked for potential effectiveness, and those have shown high molecular docking scores were proposed as novel drug candidates against SARS-CoV-2. Moreover, the outcomes of drug similarity and ADME (Absorption, Distribution, Metabolism, and Excretion) analyses have may have the effectiveness of acting as medicines, and would be of interest as promising starting point for designing compounds against SARS-CoV-2. Finally, the stability of these three compounds in the complex with Mpro was validated through molecular dynamics (MD) simulation, in which they displayed stable trajectory and molecular properties with a consistent interaction profile.

Dataset Information

QSAR study of unsymmetrical aromatic disulfides as potent avian SARS-CoV main protease inhibitors using quantum chemical descriptors and statistical methods.

Publications

QSAR study of unsymmetrical aromatic disulfides as potent avian SARS-CoV main protease inhibitors using quantum chemical descriptors and statistical methods.

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