DICP OpenIR
学科主题物理化学
Classification models for CYP450 2C8 inhibitors and non-inhibitors
Dong PP(董佩佩); Ai CZ(艾纯芝); Zhang YY(张延延); Yang L(杨凌)
会议名称9th International Meeting of the International-Society-for-the-Study-of-Xenobiotics
会议日期2010-09-04
2010-09-04
会议地点土耳其
其他题名CYP2C8抑制剂和非抑制剂的模式识别模型
页码185/2
ISSN0360-2532
部门归属十八室
主办者国际药物代谢学会
英文摘要Cytochrome P450 2C8 (CYP2C8) is one of the principal drug metabolizing P450 monooxygenases expressed in human liver. It is involved in the metabolism of some therapeutically important drugs such as paclitaxel, repaglinide, rosiglitazone, and cerivastatin. The inhibition of this enzyme in many cases leads to undesired accumulation of the administered therapeutic agent. The purpose of this study is to develop in silico models that can effectively distinguish human CYP2C8 inhibitors from non-inhibitors. We present a data set of more than 200 structurally diverse drug compounds classified for their interaction (inhibitor, non-inhibitor) with CYP2C8. Structures of each drug were characterized by a lot of 2D descriptors. Feature selection was performed using Monte Carlo variable selection (MCVS) method to select key descriptors for modle building. Artificial neural network (ANN) and support vector machaine (SVM) methods were introduced for the classification of inhibitor and non-inhibitor of CYP2C8. The SVM model was better than ANN with the accuracy of 67.2% and sensitivity of 68.6%. This model is further validated by the test set where both accuracy and sensitivity were 65.8% and 66.4%, respectively. The 2D descriptors sufficiently represented the molecular features of CYP2C8 inhibitors. Our model can be used for the prediction of either CYP2C8 inhibitors or non-inhibitors in the early stages of the drug discovery process.
语种中文
WOS记录号WOS:000281147700329
引用统计
文献类型会议论文
条目标识符http://cas-ir.dicp.ac.cn/handle/321008/114326
专题中国科学院大连化学物理研究所
通讯作者Yang L(杨凌)
推荐引用方式
GB/T 7714
Dong PP,Ai CZ,Zhang YY,et al. Classification models for CYP450 2C8 inhibitors and non-inhibitors[C],2010:185/2.
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