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Cluster analysis of amino acid indices for prediction of protein structure and function

Nakai, Kenta, Kidera, Akinori, Kanehisa, Minoru·1988·"Protein Engineering, Design and Selection"

Abstract

The relationship among 222 published indices representing various physicochemical and biochemical properties of amino acid residues has been investigated by hierarchical cluster analysis. The clustering result is illustrated by the minimum spanning tree, which is conveniently divided into four regions: alpha and turn propensities, beta propensity, hydrophobicity and other physicochemical properties including, among others, bulkiness of amino acid residues. In addition, several subclasses of hydrophobicity scales have been identified: preference of inside and outside, accessible surface area, surrounding hydrophobicity and other mostly experimental scales including transfer free energy, partition coefficients, HPLC parameters and polarity. Representative amino acid indices are identified in each of these groups. The collection of amino acid indices is a useful resource for empirical analyses correlating sequence information with structural and functional properties of proteins. As an example, the indices that best reproduce the amino acid mutation data matrix are searched against this collection.

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Metadata

Authors
Nakai, K., Kidera, A., & Kanehisa, M.
Venue
"Protein Engineering, Design and Selection"
Published
1988
Volume
2
Issue
2
Pages
93-100
ISSN
  • 0269-2139 (ISSN-L)
  • 1741-0126
  • 1741-0134
OpenAlex
W2053411993
Cited by
226
References
0
FWCI
1.40
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Cluster analysis of amino acid indices for prediction of protein structure and function. https://app.cochat.ai/papers/10.1093/protein/2.2.93
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Nakai, K., Kidera, A., & Kanehisa, M. (1988). Cluster analysis of amino acid indices for prediction of protein structure and function. "Protein Engineering, Design and Selection". https://doi.org/10.1093/protein/2.2.93

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