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Optimization of multiple-sequence alignment based on multiple-structure alignment.

Maxim Shatsky1, Ruth Nussinov, Haim J Wolfson

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

Proteins
|November 19, 2005
PubMed
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This study introduces a novel method unifying sequence and structure information for more accurate protein alignments. This approach enhances multiple sequence alignments, protein conformational change analysis, and structure-sequence conservation predictions.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Structural Biology

Background:

  • Current multiple-sequence alignment methods rely solely on sequence data, leading to potential inaccuracies.
  • Existing multiple-structure alignment methods prioritize structural alignment, neglecting valuable sequence information.

Purpose of the Study:

  • To develop an alignment method that integrates both sequence and three-dimensional structure information.
  • To improve the accuracy of multiple sequence alignments and related biological analyses.

Main Methods:

  • A novel optimization method was developed, unifying sequence and structure data.
  • The alignment score incorporates standard amino acid substitution probabilities and novel 3D structure alignment probabilities.

Related Experiment Videos

Main Results:

  • The unified method produces more accurate multiple sequence alignments compared to sequence-only methods.
  • Demonstrated utility in analyzing protein conformational changes.
  • Enabled accurate computation of amino acid structure-sequence conservation for protein-protein docking.

Conclusions:

  • Integrating sequence and structure information significantly enhances alignment accuracy.
  • The developed method offers a powerful tool for various bioinformatics applications, including protein interaction prediction.
  • The method and its applications are publicly available online.