Ramasubburayan Ramasamy, Amperayani Karteek Rao, Varadhi Govinda, Dhanraj Ganapathy, Athista Manoharan, Mahapatra Sonalismita, Prakash Santhiyagu
Department of Prosthodontics, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences (SIMATS), Saveetha University, Chennai, India.
Department of Organic Chemistry, Gayatri Vidya Parishad College for Degree and PG Courses (Autonomous), Andhra Pradesh, India.
J Biomol Struct Dyn. 2024;42(24):13401-13410. doi: 10.1080/07391102.2023.2275185. Epub 2023 Oct 28.
COVID-19 is a deadly pandemic caused by Corona virus leading to millions of deaths worldwide. Till today no medicine was available to cure this disease. This study selected 262 potential bioactive natural products derived from mangroves to inhibit the main protease (Mpro) and receptor-binding domain (RBD) protein of the COVID-19 virus. All the ligands were subjected to Adsorption Digestion Metabolism Excretion and Toxicity (ADMET) predictions and docking studies using AutodockVina. Among all the ligands, NP_143 (Shearinine A) and NP_242 (Amentoflavone), having the highest docking score of 10.2 and 10.1 Kj/mole, respectively, were picked for 100 ns of Molecular Dynamics using GROMACS. The trajectories generated were used to estimate Root mean square deviation (RMSD), Root mean square fluctuations (RMSF), Radius of Gyrations (RG), Solvent accessible surface area (SASA), and Hydrogen bonds. From the data generated, both the ligands have good binding ability at the active site of Mpro protein and do not deviate much. They have strong interactions with the amino acids during the 100 ns of simulations and can thus be considered potential drug candidates.Communicated by Ramaswamy H. Sarma.
新冠病毒肺炎（COVID-19）是一种由冠状病毒引起的致命大流行病，已导致全球数百万人死亡。直到如今，仍没有可治愈这种疾病的药物。本研究挑选了262种源自红树林的潜在生物活性天然产物，用于抑制新冠病毒的主要蛋白酶（Mpro）和受体结合域（RBD）蛋白。所有配体都通过AutodockVina进行了吸附、消化、代谢、排泄和毒性（ADMET）预测及对接研究。在所有配体中，对接分数最高，分别为10.2和10.1千焦/摩尔的NP_143（蛇纹宁A）和NP_242（穗花杉双黄酮），被挑选出来使用GROMACS进行100纳秒的分子动力学研究。生成的轨迹用于估计均方根偏差（RMSD）、均方根波动（RMSF）、回转半径（RG）、溶剂可及表面积（SASA）和氢键。从生成的数据来看，这两种配体在Mpro蛋白的活性位点都具有良好的结合能力，且偏差不大。在100纳秒的模拟过程中，它们与氨基酸有强烈的相互作用，因此可被视为潜在的药物候选物。由拉马斯瓦米·H·萨尔马传达。
