张述伟

个人信息Personal Information

教授

硕士生导师

性别:男

毕业院校:大连理工大学

学位:硕士

所在单位:化工学院

电子邮箱:zswei@dlut.edu.cn

扫描关注

论文成果

当前位置: 中文主页 >> 科学研究 >> 论文成果

A classification study of human beta(3)-adrenergic receptor agonists using BCUT descriptors

点击次数:

论文类型:期刊论文

发表时间:2011-11-01

发表刊物:MOLECULAR DIVERSITY

收录刊物:PubMed、Scopus、SCIE

卷号:15

期号:4

页面范围:877-887

ISSN号:1381-1991

关键字:Human beta(3)-adrenergic receptor agonists; Variable selection; Dragon descriptors; Random forest

摘要:Experimental EC(50)s for 202 human beta(3)-AR agonists are used to develop classification models as a potential screening tool for a large library of target compounds before synthesis. A variable selection approach from random forests (VS-RF) is used to extract the structural information most relevant to the human beta(3)-AR activation properties of the collected data set. The obtained results indicate that the VS-RF method can be used for variable selection with smallest sets of non-redundant descriptors with highly predictive accuracy (Q(ex)%=96% for the external prediction set). Thus, the proposed VS-RF models should be helpful for screening of potential human beta(3)-AR agonists before chemical synthesis in drug development.