Division of Pharmaceutical Chemistry, Eminent College of Pharmaceutical Technology, Moshpukur, Barbaria, Barasat, 24 PGS(N), Kolkata-700126, West Bengal, India.
Division of Pharmaceutical Technology, Gupta College of Technological Sciences, Ashram More, Asansol, 713301 West Bengal, India.
Cell Mol Biol (Noisy-le-grand). 2024 Sep 8;70(8):39-49. doi: 10.14715/cmb/2024.70.8.5.
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.
本研究通过药效团建模、分子对接、分子动力学、药物相似性和 ADME 性质对几种黄酮类衍生物进行了计算机分析，以探索 COVID-19。初步文献研究表明，许多黄酮类化合物，包括木樨草素、槲皮素、山奈酚和黄芩苷，可能对 SARS β-冠状病毒有用，这促使选择它们的潜在衍生物来研究它们作为 COVID-19 抑制剂的能力。通过计算机分子对接对发现进行了简化，该对接揭示了所有黄酮类衍生物与目标蛋白之间有希望的能量结合相互作用。值得注意的是，化合物 8、9、13 和 15 对冠状病毒 Mpro 蛋白（PDB ID 6M2N）表现出更高的抑制活性。化合物 8 与该蛋白的亲和力为-7.2 Kcal/mol，并通过与 Gln192 形成氢键和与 Met-165 形成π-硫键与该蛋白结合。化合物 9 与主蛋白酶表现出显著的相互作用，亲和力为-7.9 kcal/mol。Gln-192、Glu-189、Pro-168 和 His-41 是参与这种相互作用的主要氨基酸残基。化合物 13 的对接分数为-7.5 Kcal/mol，它通过与 Leu-41、π-σ和 Gln-189 相互作用与蛋白酶结合。这些相互作用包括氢键和π-硫键。主要蛋白酶和化合物 15 被发现与有利的亲和力-6.8 Kcal/mol 结合。这一发现通过 1ns 的分子动力学模拟进一步得到了验证，分析了 RMSD、RMSF 和 RoG 谱等参数。这四种化合物的 RoG 值差异很大（35.2-36.4）。结果表明所选化合物在模拟过程中稳定。通过稳定性测试后，对化合物进行了 ADME 和药物相似性筛选，满足所有必要标准。该研究的结果可能支持进一步努力发现和开发治疗 COVID-19 的安全药物。
