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Journal of Biomolecular Structure and Dynamics 2020-Oct

Molecular modeling study of tectoquinone and acteoside from Tectona grandis linn: a new SARS-CoV-2 main protease inhibitor against COVID-19

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Inicieu sessió / registreu-vos
L'enllaç es desa al porta-retalls
Anoop Kallingal
Varun Kundil
Aravind Ayyolath
Abraham Karlapudi
Tomy Joseph
Jayadevi E

Paraules clau

Resum

Coronavirus disease 2019 (COVID-19), a highly contagious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has drastically changed the lifestyle of people around the globe. Due to the lack of specific and effective antiviral drugs, transmission of the disease increases exponentially and makes it more serious and harder to control. Drugs that were assumed to be effective against COVID-19 have failed in various stages of clinical trials and this made the scientific community more disappointed. But, the race of researchers for developing new and effective antiviral to stop the disease progression still continues and our work is one among them. This study is an attempt to analyze the action of Tectoquinone and Acteoside; an important phytocompound, on SARS-CoV2 viral protease via in silico approach. The compounds were selected on the basis of their molecular docking values and they were subjected to molecular dynamics simulations about 50 ns to determine the stability and the thermodynamic feasibility between the target and the ligands. Binding energies like hydrogen bonding, hydrophobic and electrostatic interactions of the complexes were determined after MD simulations. The Pharmacokinetics and drug likeness evaluation of the compounds provide a strong evidence for the use of these compounds in developing drugs for clinical trials. Thus, the current study reveals the potential phytoconstituents present in Tectona grandis Linn to inhibit COVID-19 viral protease and thereby act as a lead therapeutic agent. Communicated by Ramaswamy H. Sarma.

Keywords: Acteoside; COVID-19; Mpro inhibitor; SARS-CoV-2; Tectoquinone; molecular modeling.

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