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Multiple structural alignment by secondary structures: algorithm and applications.

Oranit Dror1, Hadar Benyamini, Ruth Nussinov

  • 1School of Computer Science, Raymond and Beverly Sackler Faculty of Exact Sciences, Tel Aviv University, Tel Aviv 69978, Israel. oranit@post.tau.ac.il

Protein Science : a Publication of the Protein Society
|October 24, 2003
PubMed
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We developed MASS, a new method for multiple protein structural alignment. It efficiently identifies common structural motifs, even in subsets of proteins, aiding in tasks like protein-protein docking.

Area of Science:

  • Structural bioinformatics
  • Computational biology
  • Protein structure analysis

Background:

  • Multiple protein structural alignment is crucial for understanding protein function and evolution.
  • Existing methods often rely on pairwise comparisons, potentially missing global solutions or failing to detect non-topological motifs.
  • There is a need for efficient and robust methods capable of handling multiple protein structures simultaneously.

Purpose of the Study:

  • To introduce MASS (Multiple Alignment by Secondary Structures), a novel and efficient method for multiple protein structural alignment.
  • To enable the detection of common structural motifs, including those shared by subsets of proteins and non-topological motifs.
  • To demonstrate the utility of MASS in analyzing protein ensembles and guiding protein-protein docking.

Related Experiment Videos

Main Methods:

  • MASS employs a two-level alignment strategy, integrating secondary structure and atomic representations.
  • Secondary structure information is utilized to enhance efficiency and robustness by filtering noisy solutions.
  • The method performs truly multiple alignments, considering all input molecules simultaneously, unlike pairwise approaches.

Main Results:

  • MASS successfully aligns multiple protein molecules and detects common structural motifs across various protein ensembles.
  • The method demonstrates efficiency in handling a large number of molecules (tens).
  • MASS identifies biologically meaningful alignments within non-predefined subsets and detects nontopological motifs.
  • Application of MASS-identified conserved motifs aids in guiding protein-protein docking.

Conclusions:

  • MASS provides a robust and efficient solution for multiple protein structural alignment and motif discovery.
  • Its ability to handle large datasets and detect diverse motif types offers significant advantages over existing methods.
  • MASS has practical applications in computational biology, including facilitating protein-protein docking predictions.