QSAR study of 4-phenylpiperidine derivatives as mu opioid agonists by neural network method.
A nonlinear QSAR study was conducted on a series of 4-phenylpiperidine derivatives (4PPs) acting as mu opioid agonists by three-layer back-propagation neural network (NN) method. At first a variety of molecular descriptors were calculated and then selected with two-stage least squares combining partial least squares (PLS) method. The selected four molecular descriptors, out of 292 ones, were correlated with the known analgesic activities of 38 4PPs by NN method. The established QSAR model was further validated by five additional 4PPs, as an external testing set. Moreover, a pharmacophore model was hypothesized based on the results, which would be helpful for structural optimization of 4PPs.
Wang
Xing-hai
XH
Department of Medicinal Chemistry, School of Pharmacy, Fudan University, 138 Yixueyuan Road, Shanghai 200032, China.
Tang
Yun
Y
Xie
Qiong
Q
Qiu
Zhui-bai
ZB
D000701:Analgesics, Opioid / Q000737:chemistry / Q000494:pharmacology*; D015195:Drug Design; D016018:Least-Squares Analysis; D016571:Neural Networks, Computer; D010880:Piperidines / Q000737:chemistry / Q000494:pharmacology*; D021281:Quantitative Structure-Activity Relationship; D017450:Receptors, Opioid, mu / Q000819:agonists*
D000701:Analgesics, Opioid; D010880:Piperidines; D017450:Receptors, Opioid, mu; C048151:4-phenylpiperidine