Dataset Information

Molecular docking analysis of N-substituted Oseltamivir derivatives with the SARS-CoV-2 main protease.

ABSTRACT: The identification of chemotherapeutic drugs against Novel Coronavirus (2019-nCoV) is a significant requirement due to the rapid rise in deaths due to Corona Viral Infection all around the world. Therefore, it is of interest to document the molecular docking analysis data of 32 N-substituted Oseltamivir derivatives inhibitors of influenza virus H5N1 with the Novel Coronavirus main protease (2019-nCoV). We describe the optimal binding features of Oseltamivir derivatives with the SARS-Cov-2 main protease (Code PDB: 6LU7) for further consideration.

SUBMITTER: Belhassan A

PROVIDER: S-EPMC7434956 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Molecular docking analysis of N-substituted Oseltamivir derivatives with the SARS-CoV-2 main protease.

Belhassan Assia A Chtita Samir S Zaki Hanane H Lakhlifi Tahar T Bouachrine Mohammed M

Bioinformation 20200531 5

The identification of chemotherapeutic drugs against Novel Coronavirus (2019-nCoV) is a significant requirement due to the rapid rise in deaths due to Corona Viral Infection all around the world. Therefore, it is of interest to document the molecular docking analysis data of 32 N-substituted Oseltamivir derivatives inhibitors of influenza virus H5N1 with the Novel Coronavirus main protease (2019-nCoV). We describe the optimal binding features of Oseltamivir derivatives with the SARS-Cov-2 main p ...[more]

PMID: 32831522

Similar Datasets

Project description:BackgroundDue to the migratory flow of infected people with severe acute respiratory syndrome virus (SARS COV-2), the number of confirmed cases of coronavirus disease 2019 (COVID-19) is accelerating globally; preclinical evidence of antiviral agents that can combat this pandemic is still elusive. We identified published articles on SARS-COV efficacy experiments in which some selected compounds were used to test the reduction of the virus load in mice.MethodsA systematic search of articles was conducted in PubMed, Web of Science, and Scopus. We then developed a combined model based on a systematic review, meta-analyses, and molecular docking studies to evaluate the effect size of preclinical studies of compounds that have been tested against SARS-COV. Because substantial heterogeneity was expected, random effect model meta-analyses were carried out to estimate the overall pooled disease's prevalence. All meta-analyses were performed with Stata version 15.0. Subgroup analyses on therapies were conducted as well. Molecular docking studies of the inhibitors in the active pocket of COVID-19 protease were also performed.ResultsFrom all screened articles, six studies were appropriate for ultimate meta-analysis and systematic review. The residual amount of heterogeneity was high (τ2 =0.02; heterogeneity I2 =85.5 % with heterogeneity chi-square =103.57, a degree of freedom =15, and p <0.001). The overall random pooled prevalence of infected mice treated with the selected compounds was 78.1 % [95 % Confidence Interval (CI): 14.7-17.0 %]. Prophylactic has a significantly higher pooled prevalence than therapeutic, with 21.8 % (95 % CI: 16.4 % to 28.8 %). Our results indicated that most of the SARS-COV inhibitors analyzed were less effective in reducing the lung virus titer of SARS-COV infection in animal models. The findings from molecular docking studies also identified COVID-19 inhibitors that are good for optimization and drug development to fight against COVID-19 infection.ConclusionsFindings from the review showed that studies on the preclinical compounds targeting SARS-COV and COVID-19 are limited. Furthermore, molecular docking studies and meta-analysis results substantiated three compounds, i.e., EIDD-2801, GS-5734, and amodiaquine. HIPPOKRATIA 2020, 24(3): 99-106.

Project description:The recent coronavirus outbreak has changed the world's economy and health sectors due to the high mortality and transmission rates. Because the development of new effective vaccines or treatments against the virus can take time, an urgent need exists for the rapid development and design of new drug candidates to combat this pathogen. Here, we obtained antiviral peptides obtained from the data repository of antimicrobial peptides (DRAMP) and screened their predicted tertiary structures for the ability to inhibit the main protease of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using multiple combinatorial docking programs, including PatchDock, FireDock, and ClusPro. The four best peptides, DRAMP00877, DRAMP02333, DRAMP02669, and DRAMP03804, had binding energies of -1125.3, -1084.5, -1005.2, and -924.2 Kcal/mol, respectively, as determined using ClusPro, and binding energies of -55.37, -50.96, -49.25, -54.81 Kcal/mol, respectively, as determined using FireDock, which were better binding energy values than observed for other peptide molecules. These peptides were found to bind with the active cavity of the SARS-CoV-2 main protease; at Glu166, Cys145, Asn142, Phe140, and Met165, in addition to the substrate-binding sites, Domain 2 and Domain 3, whereas fewer interactions were observed with Domain 1. The docking studies were further confirmed by a molecular dynamics simulation study, in which several descriptors, including the root-mean-square difference (RMSD), root-mean-square fluctuation (RMSF), solvent-accessible surface area (SASA), radius of gyration (Rg), and hydrogen bond formation, confirmed the stable nature of the peptide-main protease complexes. Toxicity and allergenicity studies confirmed the non-allergenic nature of the peptides. This present study suggests that these identified antiviral peptide molecules might inhibit the main protease of SARS-CoV-2, although further wet-lab experiments remain necessary to verify these findings.

Dataset Information

Molecular docking analysis of N-substituted Oseltamivir derivatives with the SARS-CoV-2 main protease.

Publications

Molecular docking analysis of N-substituted Oseltamivir derivatives with the SARS-CoV-2 main protease.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure