Literature DB >> 1483458

A weighting method for predicting protein structural class from amino acid composition.

G Zhou1, X Xu, C T Zhang.   

Abstract

A protein is generally classified into one of the following four structural classes: all alpha, all beta, alpha+beta and alpha/beta. In this paper, based on the weighting to the 20 constituent amino acids, a new method is proposed for predicting the structural class of a protein according to its amino acid composition. The 20 weighting parameters, which reflect the different properties of the 20 constituent amino acids, have been obtained from a training set of proteins through the linear-programming approach. The rate of correct prediction for a training set of proteins by means of the new method was 100%, whereas the highest rate of previous methods was 82.8%. Furthermore, the results showed that the more numerous training proteins, the more effective the new method.

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Year:  1992        PMID: 1483458     DOI: 10.1111/j.1432-1033.1992.tb17476.x

Source DB:  PubMed          Journal:  Eur J Biochem        ISSN: 0014-2956


  6 in total

1.  A time-series-based feature extraction approach for prediction of protein structural class.

Authors:  Ravi Gupta; Ankush Mittal; Kuldip Singh
Journal:  EURASIP J Bioinform Syst Biol       Date:  2008

2.  An analysis of protein folding type prediction by seed-propagated sampling and jackknife test.

Authors:  C T Zhang; K C Chou
Journal:  J Protein Chem       Date:  1995-10

3.  Characterization of protein secondary structure from NMR chemical shifts.

Authors:  Steven P Mielke; V V Krishnan
Journal:  Prog Nucl Magn Reson Spectrosc       Date:  2009-04-05       Impact factor: 9.795

4.  Prediction of protein structural class with Rough Sets.

Authors:  Youfang Cao; Shi Liu; Lida Zhang; Jie Qin; Jiang Wang; Kexuan Tang
Journal:  BMC Bioinformatics       Date:  2006-01-14       Impact factor: 3.169

5.  Semi-supervised protein subcellular localization.

Authors:  Qian Xu; Derek Hao Hu; Hong Xue; Weichuan Yu; Qiang Yang
Journal:  BMC Bioinformatics       Date:  2009-01-30       Impact factor: 3.169

Review 6.  The blind watchmaker and rational protein engineering.

Authors:  H W Anthonsen; A Baptista; F Drabløs; P Martel; S B Petersen
Journal:  J Biotechnol       Date:  1994-08-31       Impact factor: 3.307

  6 in total

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