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与非核苷类逆转录酶抑制剂(NNRTI)依非韦伦相似的FDA批准化合物的虚拟筛选、分子对接研究及密度泛函理论计算

Virtual screening, molecular docking studies and DFT calculations of FDA approved compounds similar to the non-nucleoside reverse transcriptase inhibitor (NNRTI) efavirenz.

作者信息

Jordaan Maryam A, Ebenezer Oluwakemi, Damoyi Nkululeko, Shapi Michael

机构信息

Faculty of Natural Science, Department of Chemistry, Mangosuthu University of Technology, 511 Mangosuthu Highway, Durban, 4000, South Africa.

出版信息

Heliyon. 2020 Aug 11;6(8):e04642. doi: 10.1016/j.heliyon.2020.e04642. eCollection 2020 Aug.

Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was confirmed as the causative virus of COVID-19 disease, which is currently a worldwide pandemic. Efavirenz, a non-nucleoside reverse transcriptase inhibitor (NNRTI), is one of the most potent chemical compounds proposed to treat COVID-19 infection. We, therefore, performed virtual screening on FDA approved drugs that are similar to the efavirenz moiety. Subsequently, the compounds were subjected to screening by analyzing their drug-likeness, such as Lipinski's rule of five and ADMET properties. Molecular docking study revealed that Met165, His41, His163, and Phe140 were important interacting residues for COVID-19 main protease receptor-ligand interaction. Five top-ranked compounds, podophyllotoxin, oxacillin, lovastatin, simvastatin, and gefitinib, were selected by virtual screening and docking studies. The highest occupied molecular (HOMO) orbital, lowest unoccupied molecular orbital (LUMO) and energy gap values was calculated using density functional theory (DFT). The results of the study showed that lovastatin and simvastatin might be considered as lead compounds for further development for COVID-19 main protease inhibitors.

摘要

严重急性呼吸综合征冠状病毒2(SARS-CoV-2)被确认为新型冠状病毒肺炎(COVID-19)疾病的致病病毒,目前该疾病在全球范围内大流行。依非韦伦是一种非核苷类逆转录酶抑制剂(NNRTI),是被提议用于治疗COVID-19感染的最有效化合物之一。因此,我们对与依非韦伦部分结构相似的FDA批准药物进行了虚拟筛选。随后,通过分析它们的类药性,如Lipinski五规则和ADMET性质,对这些化合物进行筛选。分子对接研究表明,Met165、His41、His163和Phe140是COVID-19主要蛋白酶受体-配体相互作用的重要相互作用残基。通过虚拟筛选和对接研究,选择了五种排名靠前的化合物,鬼臼毒素、苯唑西林、洛伐他汀、辛伐他汀和吉非替尼。使用密度泛函理论(DFT)计算了最高占据分子轨道(HOMO)、最低未占据分子轨道(LUMO)和能隙值。研究结果表明,洛伐他汀和辛伐他汀可能被视为COVID-19主要蛋白酶抑制剂进一步开发的先导化合物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6365/7426583/aacf895498f0/gr1.jpg

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