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Pattern Discovery in Biomolecular DataTools, Techniques, and Applications$
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Jason T. L. Wang, Bruce A. Shapiro, and Dennis Shasha

Print publication date: 1999

Print ISBN-13: 9780195119404

Published to Oxford Scholarship Online: November 2020

DOI: 10.1093/oso/9780195119404.001.0001

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PRINTED FROM OXFORD SCHOLARSHIP ONLINE (oxford.universitypressscholarship.com). (c) Copyright Oxford University Press, 2021. All Rights Reserved. An individual user may print out a PDF of a single chapter of a monograph in OSO for personal use. date: 17 June 2021

Systematic Detection of Protein Structural Motifs

Systematic Detection of Protein Structural Motifs

(p.97) Chapter 6 Systematic Detection of Protein Structural Motifs
Pattern Discovery in Biomolecular Data

Kentaro Tomii

Minoru Kanehisa

Oxford University Press

It is widely believed that the prediction of the 3D structure of a protein from its amino acid sequence is important because the structure will help understand the function. As the number of protein structures resolved is increasing, most predictive methods have become based on the knowledge of the repertoire of 3D folds taken by actual proteins. We must emphasize, however, that this type of structure prediction, or fold recognition, concerns the overall folding of the polypeptide chain. Since two similar folds could be due to entirely different sequences and even two similar sequences could have different functions, it is unlikely that successful fold recognition will uncover any functional clue that cannot otherwise be obtained by sequence analysis alone. In contrast to the global feature of 3D folds, the concept of structural motifs or local structures is far more important in understanding protein function. It has been revealed that there are common local folding patterns that appear in many proteins of globally different structures and that are involved in conserved function. In addition, the local sequence patterns associated with these local structures are also often conserved, though the whole sequences can be quite different. At the supersecondary structure level there are, for example, βαβ -unit, EF hand, and helix-turn-helix motifs. Various dehydrogenases have a common structural motif called Rossman fold, which is composed of two consecutive βαβ -units, and most of those proteins also have the sequence motif GxGxxG around the nucleotide binding region (Wierenga and Hol, 1983; Wierenga et al., 1986). The EF hand consisting of the helix-loop-helix structure (Tufty and Kretsinger, 1975) occurs in many calcium-binding domains, and the residues that participate in ligand binding are well conserved. The helix-turn-helix motif that involves about 20 residues appears in a class of DNA-binding domains, and glycine tends to be conserved at a special position in the turn whose conformation corresponds to the left-handed helix. A number of known sequence motifs are registered in the motif libraries such as PROSITE (Bairoch and Bucher, 1994) that compile the relationships between sequence patterns and functions.

Keywords:   Clustering, DSSP, EF hand, Minimum spanning tree, Needleman-Wunsch algorithm, Protein Data Bank, Quantization procedure, Structure-based matrix

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