Anti- COVID-19 drug discovery by flavonoid derivatives: an extensivecomputational drug design approach

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.

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Publication Details

Journal
Cellular and Molecular Biology
Published
2024-09-08
DOI
https://doi.org/10.14715/cmb/2024.70.8.5
Citations
1
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
0.36

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article

Anti- COVID-19 drug discovery by flavonoid derivatives: an extensivecomputational drug design approach

Kalyan Kumar Sen, Mohammad Nur‐e‐Alam, Md. Moklesur Rahman Sarker, Mohd Fahami Nur Azlina et al.
1 citations
Cellular and Molecular Biology
Computational Drug Discovery Methods
0.36
article

Anti- COVID-19 drug discovery by flavonoid derivatives: an extensivecomputational drug design approach

Kalyan Kumar Sen, Mohammad Nur‐e‐Alam, Md. Moklesur Rahman Sarker, Mohd Fahami Nur Azlina, Aziz Eftekhari, Mohsin Kazi, Sreemoy Kanti Das, Yuan Seng Wu, Raquibul Hasan, Subhasis Banerjee, Arka Das, Souvik Mukherjee
article en
1 citations

Abstract

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.

Cellular and Molecular BiologyVol. 70(8)
Mercer University (US), Krishnadevaraya College of Dental Sciences and Hospital (IN), Mercer University Health Sciences Center (US), University Kebangsaan Malaysia Medical Centre (MY), King Saud University (SA), ASA College (US), Gono University (BD), Ege University (TR), Global College (CY), Lincoln University College (MY), West Bengal State University (IN), Sunway University (MY), National University of Malaysia (MY)
King Saud University, Universiti Kebangsaan Malaysia
Openalex Percentile: Top 36%
Computational Drug Discovery Methods
0.36
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