Literature DB >> 3957893

The folding type of a protein is relevant to the amino acid composition.

H Nakashima, K Nishikawa, T Ooi.   

Abstract

The folding types of 135 proteins, the three-dimensional structures of which are known, were analyzed in terms of the amino acid composition. The amino acid composition of a protein was expressed as a point in a multidimensional space spanned with 20 axes, on which the corresponding contents of 20 amino acids in the protein were represented. The distribution pattern of proteins in this composition space was examined in relation to five folding types, alpha, beta, alpha/beta, alpha + beta, and irregular type. The results show that amino acid compositions of the alpha, beta, and alpha/beta types are located in different regions in the composition space, thus allowing distinct separation of proteins depending on the folding types. The points representing proteins of the alpha + beta and irregular types, however, are widely scattered in the space, and the existing regions overlap with those of the other folding types. A simple method of utilizing the "distance" in the space was found to be convenient for classification of proteins into the five folding types. The assignment of the folding type with this method gave an accuracy of 70% in the coincidence with the experimental data.

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Year:  1986        PMID: 3957893     DOI: 10.1093/oxfordjournals.jbchem.a135454

Source DB:  PubMed          Journal:  J Biochem        ISSN: 0021-924X            Impact factor:   3.387


  74 in total

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Journal:  Biophys J       Date:  1999-09       Impact factor: 4.033

2.  Support vector machines for predicting membrane protein types by using functional domain composition.

Authors:  Yu-Dong Cai; Guo-Ping Zhou; Kuo-Chen Chou
Journal:  Biophys J       Date:  2003-05       Impact factor: 4.033

3.  Predicting enzyme family class in a hybridization space.

Authors:  Kuo-Chen Chou; Yu-Dong Cai
Journal:  Protein Sci       Date:  2004-11       Impact factor: 6.725

4.  Patterns in protein primary sequences: classification, display and analysis.

Authors:  P N Saurugger; B A Metfessel
Journal:  Proc Annu Symp Comput Appl Med Care       Date:  1991

5.  Prediction of protein structural classes using hybrid properties.

Authors:  Wenjin Li; Kao Lin; Kaiyan Feng; Yudong Cai
Journal:  Mol Divers       Date:  2008-10-25       Impact factor: 2.943

6.  Monte Carlo simulation studies on the prediction of protein folding types from amino acid composition.

Authors:  C T Zhang; K C Chou
Journal:  Biophys J       Date:  1992-12       Impact factor: 4.033

7.  Prediction of protein folding types from amino acid composition by correlation angles.

Authors:  K C Chou
Journal:  Amino Acids       Date:  1994-10       Impact factor: 3.520

8.  Protein identification and quantification by two-dimensional infrared spectroscopy: implications for an all-optical proteomic platform.

Authors:  Frédéric Fournier; Elizabeth M Gardner; Darek A Kedra; Paul M Donaldson; Rui Guo; Sarah A Butcher; Ian R Gould; Keith R Willison; David R Klug
Journal:  Proc Natl Acad Sci U S A       Date:  2008-10-01       Impact factor: 11.205

9.  Sequence physical properties encode the global organization of protein structure space.

Authors:  S Rackovsky
Journal:  Proc Natl Acad Sci U S A       Date:  2009-08-12       Impact factor: 11.205

10.  The proteolytic fragments generated by vertebrate proteasomes: structural relationships to major histocompatibility complex class I binding peptides.

Authors:  G Niedermann; G King; S Butz; U Birsner; R Grimm; J Shabanowitz; D F Hunt; K Eichmann
Journal:  Proc Natl Acad Sci U S A       Date:  1996-08-06       Impact factor: 11.205

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