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探索夹竹桃科、防己科和番荔枝科的次生代谢产物数据库,以选择潜在的抗 HCV 化合物。

Exploring Secondary Metabolites Database of Apocynaceae, Menispermaceae, and Annonaceae to Select Potential Anti-HCV Compounds.

机构信息

Post-Graduate Program in Natural Synthetic Bioactive Products, Federal University of Paraiba, Joao Pessoa, Brazil.

出版信息

Curr Top Med Chem. 2019;19(11):900-913. doi: 10.2174/1568026619666190510094228.

DOI:10.2174/1568026619666190510094228
PMID:31074368
Abstract

BACKGROUND

Hepatitis C is a disease that constitutes a serious global health problem, is often asymptomatic and difficult to diagnose and about 60-80% of infected patients develop chronic diseases over time. As there is no vaccine against hepatitis C virus (HCV), developing new cheap treatments is a big challenge.

OBJECTIVE

The search for new drugs from natural products has been outstanding in recent years. The aim of this study was to combine structure-based and ligand-based virtual screening (VS) techniques to select potentially active molecules against four HCV target proteins from in-house secondary metabolite dataset (SistematX).

MATERIALS AND METHODS

From the ChEMBL database, we selected four sets of 1199, 355, 290 and 237chemical structures with inhibitory activity against different targets of HCV to create random forest models with an accuracy value higher than 82% for cross-validation and test sets. Afterward, a ligandbased virtual screen of the entire 1848 secondary metabolites database stored in SistematX was performed. In addition, a structure-based virtual screening was also performed for the same set of secondary metabolites using molecular docking.

RESULTS

Finally, using consensus analyses approach combining ligand-based and structure-based VS, three alkaloids were selected as potential anti-HCV compounds.

CONCLUSION

The selected structures are a starting point for further studies in order to develop new anti- HCV compounds based on natural products.

摘要

背景

丙型肝炎是一种严重的全球健康问题,通常无症状且难以诊断,约 60-80%的感染者会随着时间的推移发展为慢性疾病。由于目前尚无针对丙型肝炎病毒(HCV)的疫苗,因此开发新的廉价治疗方法是一项重大挑战。

目的

近年来,从天然产物中寻找新药的研究取得了显著进展。本研究旨在结合基于结构和基于配体的虚拟筛选(VS)技术,从内部次级代谢产物数据集(SistematX)中选择针对 HCV 四个靶蛋白的潜在活性分子。

材料和方法

从 ChEMBL 数据库中,我们选择了四组 1199、355、290 和 237 种具有抑制 HCV 不同靶标活性的化学结构,以创建交叉验证和测试集准确性值高于 82%的随机森林模型。之后,对存储在 SistematX 中的整个 1848 种次级代谢产物数据库进行基于配体的虚拟筛选。此外,还使用分子对接对同一组次级代谢产物进行了基于结构的虚拟筛选。

结果

最终,通过结合基于配体和基于结构的 VS 的共识分析方法,选择了三种生物碱作为潜在的抗 HCV 化合物。

结论

所选结构为进一步研究开发基于天然产物的新型抗 HCV 化合物提供了起点。

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