期刊
JOURNAL OF CHEMICAL INFORMATION AND MODELING
卷 51, 期 11, 页码 2948-2960出版社
AMER CHEMICAL SOC
DOI: 10.1021/ci200271d
关键词
-
类别
资金
- U.S. Department of Defense [BC085871]
- American Cancer Society [IRG-08-061-01]
- MDACC-UT Austin CTT-TI3D
Blockade of human ether-a-go-go related gene (hERG) channel prolongs the duration of the cardiac action potential and is a common reason for drug failure in preclinical safety trials. Therefore, it is of great importance to develop robust in silico tools to predict potential hERG blockers in the early stages of drug discovery and development. Herein we described comprehensive approaches to assess the discrimination of hERG-active and -inactive compounds by combining quantitative structure activity relationship (QSAR) modeling, pharmacophore analysis, and molecular docking. Our consensus models demonstrated high-predictive capacity and improved enrichment and could correctly classify 91.8% of 147 hERG blockers from 351 inactives. To further enhance our modeling effort, hERG homology models were constructed, and molecular docking studies were conducted, resulting in high correlations (R-2 = 0.81) between predicted and experimental pIC(50)s. We expect our unique models can be applied to efficient screening for hERG blockades, and our extensive understanding of the hERG-inhibitor interactions will facilitate the rational design of drugs devoid of hERG channel activity and hence with reduced cardiac toxicities.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据