Literature DB >> 10089199

The hydrophobic cores of proteins predicted by wavelet analysis.

H Hirakawa1, S Muta, S Kuhara.   

Abstract

MOTIVATION: In the process of protein construction, buried hydrophobic residues tend to assemble in a core of a protein. Methods used to predict these cores involve use or no use of sequential alignment. In the case of a close homology, prediction was more accurate if sequential alignment was used. If the homology was weak, predictions would be unreliable. A hydrophobicity plot involving the hydropathy index is useful for purposes of prediction, and smoothing is essential. However, the proposed methods are insufficient. We attempted to predict hydrophobic cores with a low frequency extracted from the hydrophobicity plot, using wavelet analysis.
RESULTS: The cores were predicted at a rate of 68.7%, by cross-validation. Using wavelet analysis, the cores of non-homologous proteins can be predicted with close to 70% accuracy, without sequential alignment. AVAILABILITY: The program used in this study is available from Intergalactic Reality (http://www.intergalact.com). CONTACT: hirakawa@grt.kyushu-u.ac.jp, kuhara@grt.kyushu-u.ac.jp

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Year:  1999        PMID: 10089199     DOI: 10.1093/bioinformatics/15.2.141

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  5 in total

1.  Designing human m1 muscarinic receptor-targeted hydrophobic eigenmode matched peptides as functional modulators.

Authors:  Karen A Selz; Arnold J Mandell; Michael F Shlesinger; Vani Arcuragi; Michael J Owens
Journal:  Biophys J       Date:  2004-03       Impact factor: 4.033

2.  Prediction of the types of membrane proteins based on discrete wavelet transform and support vector machines.

Authors:  Jian-Ding Qiu; Xing-Yu Sun; Jian-Hua Huang; Ru-Ping Liang
Journal:  Protein J       Date:  2010-02       Impact factor: 2.371

3.  Defining and predicting structurally conserved regions in protein superfamilies.

Authors:  Ivan K Huang; Jimin Pei; Nick V Grishin
Journal:  Bioinformatics       Date:  2012-11-28       Impact factor: 6.937

4.  Wavelet Analysis of Protein Motion.

Authors:  Noah C Benson; Valerie Daggett
Journal:  Int J Wavelets Multiresolut Inf Process       Date:  2012-07       Impact factor: 1.408

5.  A simple method for predicting transmembrane proteins based on wavelet transform.

Authors:  Bin Yu; Yan Zhang
Journal:  Int J Biol Sci       Date:  2012-12-19       Impact factor: 6.580

  5 in total

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