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Using pseudo amino acid composition to predict protein structural class: Approached by incorporating 400 dipeptide components.

Authors :
Hao Lin
Qian-Zhong Li
Source :
Journal of Computational Chemistry. 2007, Vol. 28 Issue 9, p1463-1466. 4p. 3 Charts.
Publication Year :
2007

Abstract

The proteins structure can be mainly classified into four classes: all-α, all-β, α/β, and α + β protein according to their chain fold topologies. For the purpose of predicting the protein structural class, a new predicting algorithm, in which the increment of diversity combines with Quadratic Discriminant analysis, is presented to study and predict protein structural class. On the basis of the concept of the pseudo amino acid composition (Chou, Proteins: Struct Funct Genet 2001, 43, 246; Erratum: Proteins Struct Funct Genet 2001, 44, 60), 400 dipeptide components and 20 amino acid composition are, respectively, selected as parameters of diversity source. Total of 204 nonhomologous proteins constructed by Chou (Chou, Biochem Biophys Res Commun 1999, 264, 216) are used for training and testing the predictive model. The predicted results by using the pseudo amino acids approach as proposed in this paper can remarkably improve the success rates, and hence the current method may play a complementary role to other existing methods for predicting protein structural classification. © 2007 Wiley Periodicals, Inc. J Comput Chem, 2007 [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01928651
Volume :
28
Issue :
9
Database :
Academic Search Index
Journal :
Journal of Computational Chemistry
Publication Type :
Academic Journal
Accession number :
24944673
Full Text :
https://doi.org/10.1002/jcc.20554