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Distance-dependent classification of amino acids by information theory

Pape, Susanne and Hoffgaard, Franziska and Hamacher, Kay (2010):
Distance-dependent classification of amino acids by information theory.
In: Proteins: Structure, Function, and Bioinformatics, pp. 2322-2328, 78, (10), [Online-Edition: http://dx.doi.org/10.1002/prot.22744],
[Article]

Abstract

Reduced amino acid alphabets are useful to understand molecular evolution as they reveal basal, shared properties of amino acids, which the structures and functions of proteins rely on. Several previous studies derived such reduced alphabets and linked them to the origin of life and biotechnological applications. However, all this previous work presupposes that only direct contacts of amino acids in native protein structures are relevant. We show in this work, using information-theoretical measures, that an appropriate alphabet reduction scheme is in fact a function of the maximum distance amino acids interact at. Although for small distances our results agree with previous ones, we show how long-range interactions change the overall picture and prompt for a revised understanding of the protein design process.

Item Type: Article
Erschienen: 2010
Creators: Pape, Susanne and Hoffgaard, Franziska and Hamacher, Kay
Title: Distance-dependent classification of amino acids by information theory
Language: English
Abstract:

Reduced amino acid alphabets are useful to understand molecular evolution as they reveal basal, shared properties of amino acids, which the structures and functions of proteins rely on. Several previous studies derived such reduced alphabets and linked them to the origin of life and biotechnological applications. However, all this previous work presupposes that only direct contacts of amino acids in native protein structures are relevant. We show in this work, using information-theoretical measures, that an appropriate alphabet reduction scheme is in fact a function of the maximum distance amino acids interact at. Although for small distances our results agree with previous ones, we show how long-range interactions change the overall picture and prompt for a revised understanding of the protein design process.

Journal or Publication Title: Proteins: Structure, Function, and Bioinformatics
Volume: 78
Number: 10
Uncontrolled Keywords: Bioinformatik
Divisions: 10 Department of Biology
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10 Department of Biology > Computational Biology and Simulation
20 Department of Computer Science
Date Deposited: 21 Jun 2010 17:07
Official URL: http://dx.doi.org/10.1002/prot.22744
Identification Number: doi:10.1002/prot.22744
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