Aims:
The present study aim was 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 was 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) as 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 have well-interacted with all the three proteins, and 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 in-vivo studies could be carried out to provide better drug therapy.
Instant determination of the artemisinin from various
Artemisia annua L
. extracts by LC‐ESI‐MS/MS and their
in‐silico
modelling and
in vitro
antiviral activity studies against SARS‐CoV‐2
