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Original Article

Using multidimensional patterns of amino acid attributes for QSAR analysis of peptides

G. LiangContact Information, L. Yang1, L. Kang1, H. Mei1 and Z. Li2

(1)  College of Bioengineering, Chongqing University, 400030 Chongqing, China
(2)  College of Chemistry and Chemical Engineering, Chongqing University, Chongqing, China

Received: 3 April 2008  Accepted: 25 August 2008  Published online: 28 September 2008

Abstract  On the basis of exploratory factor analysis, six multidimensional patterns of 516 amino acid attributes, namely, factor analysis scales of generalized amino acid information (FASGAI) involving hydrophobicity, alpha and turn propensities, bulky properties, compositional characteristics, local flexibility and electronic properties, are proposed to represent structures of 48 bitter-tasting dipeptides and 58 angiotensin-converting enzyme inhibitors. Characteristic parameters related to bioactivities of the peptides studied are selected by genetic algorithm, and quantitative structure–activity relationship (QSAR) models are constructed by partial least square (PLS). Our results by a leave-one-out cross validation are compared with the previously known structure representation method and are shown to give slightly superior or comparative performance. Further, two data sets are divided into training sets and test sets to validate the characterization repertoire of FASGAI. Performance of the PLS models developed by training samples by a leave-one-out cross validation and external validation for test samples are satisfying. These results demonstrate that FASGAI is an effective representation technique of peptide structures, and that FASGAI vectors have many preponderant characteristics such as straightforward physicochemical information, high characterization competence and easy manipulation. They can be further applied to investigate the relationship between structures and functions of various peptides, even proteins.
Electronic supplementary material  The online version of this article (doi:10.1007/s00726-008-0177-8) contains supplementary material, which is available to authorized users.

Keywords  Peptide - Factor analysis scales of generalized amino acid information - Quantitative structure–activity relationship - Partial least squares - Genetic algorithm-partial least square


Contact Information G. Liang
Email: gzliang@cqu.edu.cn
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