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Virtual screening based on molecular docking of possible inhibitors of Covid-19 main protease.

ABSTRACT: Coronavirus (COVID-19) is an enveloped RNA virus that is diversely found in humans and that has now been declared a global pandemic by the World Health Organization. Thus, there is an urgent need to develop effective therapies and vaccines against this disease. In this context, this study aimed to evaluate in silico the molecular interactions of drugs with therapeutic indications for treatment of COVID-19 (Azithromycin, Baricitinib and Hydroxychloroquine) and drugs with similar structures (Chloroquine, Quinacrine and Ruxolitinib) in docking models from the SARS-CoV-2 main protease (M-pro) protein. The results showed that all inhibitors bound to the same enzyme site, more specifically in domain III of the SARS-CoV-2 main protease. Therefore, this study allows proposing the use of baricitinib and quinacrine, in combination with azithromycin; however, these computer simulations are just an initial step for conceiving new projects for the development of antiviral molecules.

SUBMITTER: Marinho EM

PROVIDER: S-EPMC7834391 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Virtual screening based on molecular docking of possible inhibitors of Covid-19 main protease.

Marinho Emanuelle Machado EM Batista de Andrade Neto João J Silva Jacilene J Silva Jacilene J Rocha da Silva Cecília C Cavalcanti Bruno Coelho BC Marinho Emmanuel Silva ES Nobre Júnior Hélio Vitoriano HV

Microbial pathogenesis 20200630

Coronavirus (COVID-19) is an enveloped RNA virus that is diversely found in humans and that has now been declared a global pandemic by the World Health Organization. Thus, there is an urgent need to develop effective therapies and vaccines against this disease. In this context, this study aimed to evaluate in silico the molecular interactions of drugs with therapeutic indications for treatment of COVID-19 (Azithromycin, Baricitinib and Hydroxychloroquine) and drugs with similar structures (Chlor ...[more]

PMID: 32619669

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Project description:Coronavirus (covid-19) infection is considered to be deadliest ever pandemic experienced by the human being. It has very badly affected the socio-economic health of human and stuck the scientific community to think and rethink about its complete eradication. But due to no effective treatment or unavailability of vaccine the health professional could not show any significant improvement to control the pandemic. The situation needs newer molecule, vaccine or effective treatment to control covid-19 infection. Different target in viruses has been explored and proteases enzymes were found to be therapeutically effective target for the design of potential anti-covid-19 molecule as it plays the vital role in viral replication and assembly. Structure-based drug design was employed to discover the small molecule of anti-covid-19. Here we considered the small library of naturally occurring polyphenolic compounds and molecular docking, Molecular dynamics (MD) simulations, free binding energy calculation and in-silico ADME calculations to identify the newer HITs. Based upon their score the two molecules were identified as promising candidate. The docking scores were found to be -7.643 and -7.065 for the HIT1 and HIT-2 respectively. In MD simulations study the RMSD values were found to be 4.3 Å & 4.9 Å respectively. To validate these results MM-GBSA was performed and their binding free energies were computationally determined. The prime energy values of identified HITs (-13412.45 & -13441.8 kJ/mole) were found to be very close proximity to reference molecule (-13493.05 kJ/mole). Then in-silico ADME calculations were performed to calculate the drug likeliness identified HITs. BY considering all the values comparative to reference molecule and obtained in-silico pharmacokinetic properties of identified HITs we can suggest that HIT-1 and HIT-2 would be the most promising molecules that can inhibit the main protease enzyme of covid-19. These two molecules would become the potential drug candidate for the treatment of covid-19 infections.

Dataset Information

Virtual screening based on molecular docking of possible inhibitors of Covid-19 main protease.

Publications

Virtual screening based on molecular docking of possible inhibitors of Covid-19 main protease.

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