QSAR study of 1,4-dihydropyridine calcium channel antagonists based on gene expression programming.
The gene expression programming, a novel machine learning algorithm, is used to develop quantitative model as a potential screening mechanism for a series of 1,4-dihydropyridine calcium channel antagonists for the first time. The heuristic method was used to search the descriptor space and select the descriptors responsible for activity. A nonlinear, six-descriptor model based on gene expression programming with mean-square errors 0.19 was set up with a predicted correlation coefficient (R2) 0.92. This paper provides a new and effective method for drug design and screening.
Si
Hong Zong
HZ
Department of Chemistry, Lanzhou University, 730000 Lanzhou, PR China. sihz03@st.lzu.edu.cn
Wang
Tao
T
Zhang
Ke Jun
KJ
Hu
Zhi De
ZD
Fan
Bo Tao
BT
D000465:Algorithms; D001185:Artificial Intelligence; D002121:Calcium Channel Blockers / Q000737:chemistry* / Q000494:pharmacology*; D004095:Dihydropyridines / Q000737:chemistry* / Q000494:pharmacology*; D004353:Drug Evaluation, Preclinical / Q000379:methods* / Q000706:statistics & numerical data; D015870:Gene Expression; D021281:Quantitative Structure-Activity Relationship
D002121:Calcium Channel Blockers; D004095:Dihydropyridines; C038806:1,4-dihydropyridine