山奈酚作为病毒进入抑制剂和dl -精氨酸作为病毒复制抑制剂在印度传统药物中抗COVID-19的鉴定:一种计算机引导的体外方法

IF 1.5 4区 医学 Q4 CHEMISTRY, MEDICINAL Current computer-aided drug design Pub Date : 2023-01-01 DOI:10.2174/1573409919666230112123213
Adithya J, Maneesha Murali, Bhagyalakshmi Nair, Feby Benny, Rajalakshmi P M, Darshana Suresh, Aneesh T P, Amrutha Nisthul, Lekshmi R Nath
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引用次数: 1

摘要

背景:印度传统药用植物以其在防治病毒性疾病方面的巨大潜力而闻名。在此之前,我们报道了一种系统评价方法,对七种似是而非的印度传统药用植物抗SARS-CoV-2进行了研究。方法:与Biovia Discovery Studio进行分子对接。使用了3个刺突糖蛋白结合域(PDB ID: 6LZG、6M17、6M0J)和1个RdRp结合域(PDB ID: 7BTF)。IMPPAT数据库从7种植物中选出100种植物成分进行虚拟筛选,利用瑞士ADME预测和Lipinski规则再次筛选出最佳的6种化合物。此外,通过假病毒体实验研究了SARS-CoV-2 s1蛋白与ACE 2受体的相互作用,进一步证实了这种作用。结果:与乌米菲诺韦(33.68 Kcal/mol)相比,山奈酚(48.84 Kcal/mol)与雪桐酸(52.06 Kcal/mol)对刺突糖蛋白6LZG结合域的相互作用能明显提高。表儿茶素没食子酸酯(36.95 Kcal/mol)和花生酸(26.09 Kcal/mol)与乌米诺韦(38.20 Kcal/mol)对刺突糖蛋白6M17结合域的相互作用能相当。三羟基查尔酮(35.23 Kcal/mol)和山奈酚(36.96 Kcal/mol)与乌米诺韦(36.60 Kcal/mol)对刺突糖蛋白6M0J结合域的相互作用能相当。在分析RdRp结合区域的植物成分时,dl -精氨酸(41.78 Kcal/mol)与阳性对照remdesivir (47.61 Kcal/mol)的结果相当。使用瑞士ADME进行的ADME分析显示山奈酚和DL精氨酸具有适当的药代动力学参数的药物样特性。进一步用假病毒粒子法对山奈酚进行体外分析,证实转染HEK293T-hACE2细胞中慢病毒颗粒的减少是可以接受的。结论:山奈酚和dl -精氨酸可能是抗SARS-CoV-2及其变体的重要分子。
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Identification of Kaempferol as Viral Entry Inhibitor and DL-Arginine as Viral Replication Inhibitor from Selected Plants of Indian Traditional Medicine against COVID-19: An in silico Guided in vitro Approach.

Background: Indian traditional medicinal plants are known for their great potential in combating viral diseases. Previously, we reported a systematic review approach of seven plausible traditional Indian medicinal plants against SARS-CoV-2.

Methods: Molecular docking was conducted with Biovia Discovery Studio. Three binding domains for spike glycoprotein (PDB IDs: 6LZG, 6M17, 6M0J) and one binding domain of RdRp (PDB ID: 7BTF) were used. Among 100 phytoconstituents listed from seven plants by the IMPPAT database used for virtual screening, the best six compounds were again filtered using Swiss ADME prediction and Lipinski's rule. Additionally, a pseudovirion assay was performed to study the interaction of SARS-CoV-2 S1-protein with the ACE 2 receptor to further confirm the effect.

Results: Chebulagic acid (52.06 Kcal/mol) and kaempferol (48.84 Kcal/mol) showed increased interaction energy compared to umifenovir (33.68 Kcal/mol) for the 6LZG binding domain of spike glycoprotein. Epicatechin gallate (36.95 Kcal/mol) and arachidic acid (26.09 Kcal/mol) showed equally comparable interaction energy compared to umifenovir (38.20 Kcal/mol) for the 6M17 binding domain of spike glycoprotein. Trihydroxychalcone (35.23 Kcal/mol) and kaempferol (36.96 Kcal/mol) showed equally comparable interaction energy with umifenovir (36.60 Kcal/mol) for 6M0J binding domain of spike glycoprotein. Upon analyzing the phytoconstituents against RdRp binding domain, DL-arginine (41.78 Kcal/mol) showed comparable results with the positive control remdesivir (47.61 Kcal/mol). ADME analysis performed using Swiss ADME revealed that kaempferol and DL arginine showed drug-like properties with appropriate pharmacokinetic parameters. Further in vitro analysis of kaempferol by pseudovirion assay confirmed an acceptable decrease of the lentiviral particles in transfected HEK293T-hACE2 cells.

Conclusion: The study highlights that kaempferol and DL-arginine could be the significant molecules to exhibit potent action against SARS-CoV-2 and its variants.

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来源期刊
Current computer-aided drug design
Current computer-aided drug design 医学-计算机:跨学科应用
CiteScore
3.70
自引率
5.90%
发文量
46
审稿时长
>12 weeks
期刊介绍: Aims & Scope Current Computer-Aided Drug Design aims to publish all the latest developments in drug design based on computational techniques. The field of computer-aided drug design has had extensive impact in the area of drug design. Current Computer-Aided Drug Design is an essential journal for all medicinal chemists who wish to be kept informed and up-to-date with all the latest and important developments in computer-aided methodologies and their applications in drug discovery. Each issue contains a series of timely, in-depth reviews, original research articles and letter articles written by leaders in the field, covering a range of computational techniques for drug design, screening, ADME studies, theoretical chemistry; computational chemistry; computer and molecular graphics; molecular modeling; protein engineering; drug design; expert systems; general structure-property relationships; molecular dynamics; chemical database development and usage etc., providing excellent rationales for drug development.
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