Discovery of structural motifs using protein structural alphabets and 1D motif-finding methods

Shih Yen Ku, Yuh-Jyh Hu*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Although the increasing number of available 3D proteins structures has made a wide variety of computational protein structure research possible, yet the success is still hindered by the high 3D computational complexity. Based on 3D information, several 1D protein structural alphabets have been developed, which can not only describe the global folding structure of a protein as a 1D sequence, but can also characterize local structures in proteins. Instead of applying computationally intensive 3D structure alignment tools, we introduce an approach that combines standard 1D motif detection methods with structural alphabets to discover locally conserved protein motifs. These 1D structural motifs can characterize protein groups at different levels, e.g., families, super families, and folds in SCOP, as group features.

Original languageEnglish
Title of host publicationAdvances in Computational Biology
EditorsHamid Arabnia
Pages117-123
Number of pages7
DOIs
StatePublished - 1 Dec 2010

Publication series

NameAdvances in Experimental Medicine and Biology
Volume680
ISSN (Print)0065-2598

Keywords

  • Motif
  • Protein structure
  • Structural alphabet

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    Ku, S. Y., & Hu, Y-J. (2010). Discovery of structural motifs using protein structural alphabets and 1D motif-finding methods. In H. Arabnia (Ed.), Advances in Computational Biology (pp. 117-123). (Advances in Experimental Medicine and Biology; Vol. 680). https://doi.org/10.1007/978-1-4419-5913-3_14