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.
%0 Journal Article
%1 Arakawa:2006:CILS
%A Arakawa, Masamoto
%A Hasegawa, Kiyoshi
%A Funatsu, Kimito
%D 2006
%J Chemometrics and Intelligent Laboratory Systems
%K HEPT, Multi-objective Variable activity algorithms, genetic optimisation, programming, quantitative relationship selection, structure
%N 2
%P 91--98
%R doi:10.1016/j.chemolab.2006.01.009
%T QSAR study of anti-HIV HEPT analogues based on
multi-objective genetic programming and
counter-propagation neural network
%V 83
%X 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.
@article{Arakawa:2006:CILS,
abstract = {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.},
added-at = {2008-06-19T17:35:00.000+0200},
author = {Arakawa, Masamoto and Hasegawa, Kiyoshi and Funatsu, Kimito},
biburl = {https://www.bibsonomy.org/bibtex/2b780b036fddff8dd52948711372bafab/brazovayeye},
doi = {doi:10.1016/j.chemolab.2006.01.009},
interhash = {4a1110573a0235ae98b8f311b61af26b},
intrahash = {b780b036fddff8dd52948711372bafab},
journal = {Chemometrics and Intelligent Laboratory Systems},
keywords = {HEPT, Multi-objective Variable activity algorithms, genetic optimisation, programming, quantitative relationship selection, structure},
month = {15 September},
number = 2,
pages = {91--98},
timestamp = {2008-06-19T17:35:49.000+0200},
title = {{QSAR} study of anti-{HIV} {HEPT} analogues based on
multi-objective genetic programming and
counter-propagation neural network},
volume = 83,
year = 2006
}