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SS3D-P2: a three dimensional substructure search program for protein motifs based on secondary structure elements

H Kato1, Y Takahashi

  • 1Department of Knowledge-based Information Engineering, Toyohashi University of Technology, Japan. ¿hiro,taka¿@mis.tutkie.tut.ac.jp

Computer Applications in the Biosciences : CABIOS
|February 26, 1998
PubMed
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This study introduces SS3D-P2, a novel algorithm for 3D protein structure motif searching. It successfully identifies key protein motifs like the Greek key and TIM beta-barrel, advancing structural bioinformatics.

Area of Science:

  • Structural Bioinformatics
  • Computational Biology
  • Biochemistry

Background:

  • Protein structures are complex and understanding their 3D motifs is crucial for function prediction.
  • Existing methods for 3D motif searching may not be efficient or comprehensive.
  • Representing protein structures using secondary structure elements (SSEs) offers a simplified yet informative approach.

Purpose of the Study:

  • To implement and validate a novel three-dimensional (3D) structure motif search algorithm for proteins.
  • To adapt a graph theoretical clique-finding algorithm for efficient 3D substructure searching in proteins.
  • To develop a computational tool for identifying known and novel 3D structural motifs in protein databases.

Main Methods:

  • Protein structures are represented as graphs of secondary structure elements (SSEs), specifically alpha-helices and beta-strands.

Related Experiment Videos

  • Each SSE is reduced to a two-node graph representing its start and end amino acid residues.
  • A graph theoretical clique-finding algorithm, adapted from small molecule substructure searching, is employed for motif identification.

    • Main Results:

    • The SS3D-P2 program was successfully validated using known 3D protein motifs.
    • The Greek key motif, composed of four anti-parallel beta strands, was correctly identified in the crystallin protein.
    • The algorithm efficiently searched for the complex TIM-type beta-barrel motif within the Protein Data Bank.

    Conclusions:

    • The developed SS3D-P2 program provides an effective method for 3D structure motif searching in proteins.
    • This approach facilitates the identification of conserved structural patterns, aiding in protein function and evolution studies.
    • The algorithm's adaptability suggests potential for broader applications in structural bioinformatics and drug discovery.