An in silico protocol for identifying mTOR inhibitors from natural products

被引：14

作者：

Chen, Lei ^{[1
,2
]}

Wang, Ling ^{[1
,2
]}

Gu, Qiong ^{[1
,2
]}

Xu, Jun ^{[1
,2
]}

机构：

[1] Sun Yat Sen Univ, Sch Pharmaceut Sci, Res Ctr Drug Discovery, Guangzhou 510006, Guangdong, Peoples R China

[2] Sun Yat Sen Univ, Sch Pharmaceut Sci, Inst Human Virol, Guangzhou 510006, Guangdong, Peoples R China

来源：

MOLECULAR DIVERSITY | 2014年 / 18卷 / 04期

基金：

国家高技术研究发展计划(863计划); 中国国家自然科学基金;

关键词：

mTOR; ZINC natural product database; 3D-QSAR pharmacophore model; Molecular docking; MM-GBSA analysis; ANTICANCER AGENTS; DISCOVERY; CANCER; INFORMATION; THERAPY; TARGET;

D O I：

10.1007/s11030-014-9543-5

中图分类号：

Q5 [生物化学]; Q7 [分子生物学];

学科分类号：

071010 ; 081704 ;

摘要：

The mammalian target of rapamycin (mTOR) is an anti-cancer target. In this study, we propose an in silico protocol for identifying mTOR inhibitors from the ZINC natural product database. First, a three-dimensional quantitative structure-activity relationship pharmacophore model was built based on known mTOR inhibitors. The model was validated with an external test set, Fischer's randomization method, a decoy set and pharmacophore mapping conformation testing. The results showed that the model can predict the mTOR inhibition activity of the tested compounds. Virtual screening was performed based on the best pharmacophore model, and the results were then filtered using a molecular docking approach. In addition, molecular mechanics/generalized born surface area analysis was used to refine the selected candidates. The top 20 natural products were selected as potential mTOR inhibitors, and their structural scaffolds could serve as building blocks in designing drug-like molecules for mTOR inhibition.

引用

页码：841 / 852

页数：12

共 34 条

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