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The multiple common point set problem and its application to molecule binding pattern detection.

Maxim Shatsky1, Alexandra Shulman-Peleg, Ruth Nussinov

  • 1School of Computer Science, Raymond and Beverly Sackler Faculty of Exact Sciences, Tel Aviv University, Israel. maxhats@post.tau.ac.il

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|April 7, 2006
PubMed
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Identifying common protein binding patterns is crucial for understanding function and drug design. Our novel MultiBind method effectively aligns multiple protein binding sites, overcoming computational challenges to reveal conserved interaction motifs.

Area of Science:

  • Computational Biology
  • Structural Bioinformatics
  • Drug Discovery

Background:

  • Recognizing common binding patterns in protein structures is vital for predicting function and designing drugs.
  • Protein binding sites are represented as 3D point sets with physico-chemical and geometrical properties relevant to protein-ligand interactions.

Purpose of the Study:

  • To develop a computational method for identifying common binding patterns across multiple protein structures.
  • To address the computational complexity of multiple binding site alignment.

Main Methods:

  • Formulated multiple binding site alignment as detecting the largest common point set.
  • Investigated the NP-hard nature of K-partite-epsilon matching and largest common point set problems.
  • Developed MultiBind, a novel computational method employing a branch-and-bound filtering procedure to overcome combinatorial explosion.

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Main Results:

  • Demonstrated the NP-hardness of K-partite-epsilon matching and the largest common point set problem for three sets.
  • MultiBind successfully performs multiple alignment of protein binding sites without relying on sequence or fold similarity.
  • Applied MultiBind to identify conserved binding patterns for small molecules like estradiol and ATP/ANP.

Conclusions:

  • The MultiBind method offers a practical solution for recognizing common binding patterns in protein structures.
  • This approach aids in understanding protein function and facilitates structure-based drug design.
  • MultiBind effectively identifies functionally relevant binding motifs across diverse protein targets.