抗病毒化合物对sars冠状病毒的分子对接和药动学特性——一种计算机方法

P. Devi, Yashi Asthana, A. Sumitha, Ivo Romauld Sagayaraj
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引用次数: 0

摘要

本研究的主要目的是确定具有药物样特性并有可能对抗SARS-CoV-2刺突糖蛋白的生物活性化合物。从蛋白数据库中选择covid-19的6LXT蛋白作为靶蛋白。从PubChem数据库中挑选出可能与靶标结合的化合物,并使用Autodock 4.2工具进行对接。利用配体的最佳构象对分子进行分子对接,并根据命中的化合物与靶蛋白的相互作用选择网格大小。利用MetaPocket 2.0预测与靶分子结合的配体位点。对50种化合物进行对接评分,并进行毒性研究。对所选化合物进行计算,以确定具有药物相似性质的最佳构象。根据它们与蛋白质和配体的结合相互作用选择了前10个化合物的结构-活性关系。然后对配体进行药代动力学分析,然后进行Lipinski分析,并对所有结果进行最终确定和分类。ManzamineA、伊马替尼和巴索替尼的结合能分别为-9.01kcal/mol、-8.71kcal/mol和-8.01kcal/mol。
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Molecular Docking and the Pharmacokinetic Properties of the Anti-Viral Compounds Towards SARS-CoV- An In-silico Approach
The main aim of this study is to determine the bioactive compounds which have drug-like properties and has the potential to combat the spike-glycoprotein of SARS-CoV-2. The 6LXT protein of covid-19 was chosen from the protein data bank as a target protein. The compounds which are potentially capable to bind with the target were picked from the PubChem database and docked using the tool Autodock 4.2. Molecular docking of the molecules was done with the best conformations of the ligands and grid size was selected according to the hit compounds' interaction with the target protein. The ligand binding sites with the target molecules were predicted using MetaPocket 2.0. The docking Score of 50 compounds wascarried out and also toxicity studies were carried out. The compounds selected were calculated to identify the best conformations having drug-likeness properties. The top 10 compounds were chosen for the structure-activity relationship based on their binding interactions with the protein and ligand. The ligands then underwent the pharmacokinetic analysis followed by Lipinski's and all the results were finalized and categorized. ManzamineA, Imatinib, and basotinib were elected as the peak compounds with the binding energy -9.01kcal/mol, -8.71kcal/mol, and -8.01kcal/mol.
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