Abstract
Aims: The present study aimed to analyse the molecular interactions of the phytoconstituents known for their antiviral activity with the SARS-CoV-2 nonstructural proteins such as main protease (6LU7), Nsp12 polymerase (6M71), and Nsp13 helicase (6JYT). The applied in silico methodologies were molecular docking and pharmacophore modeling using Schrodinger software.
Methods: The phytoconstituents were taken from PubChem, and SARS-CoV-2 proteins were downloaded from the protein data bank. The molecular interactions, binding energy, ADMET properties, and pharmacophoric features were analysed by glide XP, prime MM-GBSA, qikprop, and phase application of Schrodinger, respectively. The antiviral activity of the selected phytoconstituents was carried out by PASS predictor online tools.
Results: The docking score analysis showed that quercetin 3-rhamnoside (-8.77 kcal/mol) and quercetin 3-rhamnoside (-7.89 kcal/mol) were excellent products to bind with their respective targets such as 6LU7, 6M71, and 6JYT. The generated pharmacophore hypothesis model validated the docking results, confirming the hydrogen bonding interactions of the amino acids. The PASS online tool predicted constituent's antiviral potentials.
Conclusion: The docked phytoconstituents showed excellent interactions with the SARS-CoV-2 proteins, and on the outset, quercetin 3-rhamnoside and quercetin 7-rhamnoside interacted well with all the three proteins; these belong to the plant Houttuynia cordata. The pharmacophore hypothesis has revealed the characteristic features responsible for their interactions, and PASS prediction data has supported their antiviral activities. Thus, these natural compounds could be developed as lead molecules for antiviral treatment against SARS-CoV-2. Further in-vitro and invivo studies could be carried out to provide better drug therapy.
Keywords: Phytoconstituents, SARS-CoV-2 proteins, molecular docking, ADMET property, pharmacophore modeling, PASS predictor.
Graphical Abstract
9