QSAR study of anti-HIV HEPT analogues based on multi-objective genetic programming and counter-propagation neural network

被引：24

作者：

Arakawa, Masamoto

Hasegawa, Kiyoshi

Funatsu, Kimito

机构：

[1] Univ Tokyo, Dept Chem Syst Engn, Bunkyo Ku, Tokyo 1138656, Japan

[2] Chugai Pharmaceut Co Ltd, Kamakura Res Labs, Kamakura, Kanagawa 2478530, Japan

来源：

CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS | 2006年 / 83卷 / 02期

关键词：

multi-objective optimization; variable selection; HEPT; genetic programming; quantitative structure-activity relationship;

D O I：

10.1016/j.chemolab.2006.01.009

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Quantitative structure-activity relationship (QSAR) has been developed for a set of inhibitors of the human immunodeficiency virus 1 (HIV-1) reverse transcriptase, derivatives of 1-[(2-hydroxyethoxy)methyl]-6-(phenylthio)thymine (HEPT). Structural descriptors used in this study are Hansch constants for each substituent and topological descriptors. We have applied the variable selection method based on multi-objective genetic programming (GP) to the HEPT data and constructed the nonlinear QSAR model using counter-propagation (CP) neural network with the selected variables. The obtained network is accurate and interpretable. Moreover in order to confirm a predictive ability of the model, a validation test was performed. (c) 2006 Elsevier B.V. All rights reserved.

引用

页码：91 / 98

页数：8

共 36 条

[1]

[Anonymous], 1989, GENETIC ALGORITHM SE

[2] Development of neural network QSPR models for Hansch substituent constants. 2. Applications in QSAR studies of HIV-1 reverse transcriptase and dihydrofolate reductase inhibitors [J].