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Pattern recognition study of QSAR substituent descriptors

Van de Waterbeemd, Hans
el Tayar, Nabil
Testa, Bernard
Published in Journal of computer-aided molecular design. 1989, vol. 3, no. 2, p. 111-132
Abstract Parameter values for 59 common substituents and 74 descriptors used in QSAR studies were compiled. This data matrix was analysed by a variety of multivariate techniques. Linear regression confirmed that lipophilicity can be factorized into two terms, one related to molecular bulk and the other to polarity. Principal component analysis (PCA) of parameters revealed 5 significant principal components and a grouping of lipophilic, steric and electronic parameters. The different loadings of parameters with 5 PCA were also explored. The classification of substituents by cluster analysis (CA) proved rather disappointing. In contrast, the SIMCA method classified substituents of increasing bulk into 5 groups of increasing polarity.
Keywords Analysis of VarianceModels, StatisticalPattern Recognition, AutomatedRegression AnalysisSoftwareStructure-Activity Relationship
PMID: 2778457
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VAN DE WATERBEEMD, Hans et al. Pattern recognition study of QSAR substituent descriptors. In: Journal of computer-aided molecular design, 1989, vol. 3, n° 2, p. 111-132.

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Deposited on : 2010-08-06

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