Anti- COVID-19 drug discovery by flavonoid derivatives: an extensive computational drug design approach: Natural flavonoids to treat COVID-19 - Banerjee, Subhasis; Mukherjee, Souvik; Mohsin Kazi; Sen, Kalyan Kumar; Das, Arka; Hasan, Raquibul; Wu, Yuan-Seng; Eftekhari, Aziz; Das, Sreemoy Kanti; Nur-e-Alam, Mohammad; Sarker, Md. Moklesur Rahman; Nur Azlina, Mohd Fahami (Cellular and Molecular Biology, 2024)
The present study deals with the in-silico analyses of several flavonoid derivatives to explore COVID-19 through pharmacophore modelling, molecular docking, molecular dynamics, drug-likeness, and ADME properties. The initial literature study revealed that many flavonoids, including luteolin, quercetin, kaempferol, and baicalin may be useful against SARS β-coronaviruses, prompting the selection of their potential derivatives to investigate their abilities as inhibitors of COVID-19. The findings were streamlined using in silico molecular docking, which revealed promising energy-binding interactions between all flavonoid derivatives and the targeted protein. Notably, compounds 8, 9, 13, and 15 demonstrated higher potency against the coronavirus Mpro protein (PDB ID 6M2N). Compound 8 has a -7.2 Kcal/mol affinity for the protein and binds to it by hydrogen bonding with Gln192 and π-sulfur bonding with Met-165. Compound 9 exhibited a significant interaction with the main protease, demonstrating an affinity of -7.9 kcal/mol. Gln-192, Glu-189, Pro-168, and His-41 were the principle amino acid residues involved in this interaction. The docking score for compound 13 is -7.5 Kcal/mol, and it binds to the protease enzyme by making interactions with Leu-41, π-sigma, and Gln-189. These interactions include hydrogen bonding and π-sulfur. The major protease and compound 15 were found to bind with a favourable affinity of -6.8 Kcal/mol. This finding was further validated through molecular dynamic simulation for 1ns, analysing parameters such as RMSD, RMSF, and RoG profiles. The RoG values for all four of the compounds varied significantly (35.2–36.4). The results demonstrated the stability of the selected compounds during the simulation. After passing the stability testing, the compounds underwent screening for ADME and drug-likeness properties, fulfilling all the necessary criteria. The findings of the study may support further efforts for the discovery and development of safe drugs to treat COVID-19.