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通过药物信息学方法阐明 HCV 非结构复制蛋白的生命周期和计算机分析。

The Life Cycle and in silico Elucidation of Non-structural Replicating Proteins of HCV Through a Pharmacoinformatics Approach.

机构信息

Department of Biosciences, COMSATS University Islamabad, Sahiwal Campus,Pakistan | Key Laboratory of Molecular Medicine and Biotherapy in the Ministry of Industry and Information Technology, Department of Biology, School of Life Sciences, Beijing Institute of Technology, Beijing, China.

Department of Biosciences, COMSATS University Islamabad, Sahiwal Campus,Pakistan.

出版信息

Comb Chem High Throughput Screen. 2022;25(4):689-701. doi: 10.2174/1386207324666210217144306.

Abstract

BACKGROUND

Hepatitis C virus (HCV) is an enveloped and positive-stranded RNA virus that is a major causative agent of chronic liver diseases worldwide. HCV has become the main cause of liver transplantations and there is no effective drug for all hepatitis genotypes. Elucidation of the life cycle and non-structural proteins of HCV, involved in viral replication, are attractive targets for the development of antiviral drugs..

METHODS

In this work, pharmacoinformatics approaches coupled with docking analyses were applied on HCV non-structural proteins to identify the novel potential hits and HCV drugs. Molecular docking analyses were carried out on HCV-approved drugs, followed by the ligandbased pharmacophore generation to screen the antiviral libraries for novel potential hits.

RESULTS

Virtual screening technique has top-ranked five novel compounds (ZINC00607900, ZINC03635748, ZINC03875543, ZINC04097464, and ZINC12503102) along with their least binding energies (-8.0 kcal/mol, -6.1 kcal/mol, -7.5 kcal/mol, -7.4 kcal/mol, and -7.3 kcal/mol, respectively) and stability with the non-structural proteins target.

CONCLUSION

These promising hits exhibited better absorption and ADMET properties as compared to the selected drug molecules. These potential compounds extracted from in silico approach may be significant in drug design and development against Hepatitis and other liver diseases.

摘要

背景

丙型肝炎病毒(HCV)是一种包膜、正链 RNA 病毒,是全球慢性肝病的主要致病因子。HCV 已成为肝移植的主要原因,而所有肝炎基因型都没有有效的药物。阐明 HCV 的生活周期和参与病毒复制的非结构蛋白是开发抗病毒药物的有吸引力的靶点。

方法

在这项工作中,我们将药物信息学方法与对接分析相结合,应用于 HCV 的非结构蛋白,以鉴定新型潜在的 HCV 药物。对 HCV 批准的药物进行分子对接分析,然后进行基于配体的药效团生成,以筛选抗病毒库中的新型潜在药物。

结果

虚拟筛选技术筛选出了五种新型化合物(ZINC00607900、ZINC03635748、ZINC03875543、ZINC04097464 和 ZINC12503102),它们的结合能最低(分别为-8.0 kcal/mol、-6.1 kcal/mol、-7.5 kcal/mol、-7.4 kcal/mol 和-7.3 kcal/mol),与非结构蛋白靶标稳定性较好。

结论

与选定的药物分子相比,这些有前途的药物具有更好的吸收和 ADMET 特性。这些从计算方法中提取的潜在化合物可能对治疗肝炎和其他肝脏疾病的药物设计和开发具有重要意义。

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