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MUSTANG: a multiple structural alignment algorithm.

Arun S Konagurthu1, James C Whisstock, Peter J Stuckey

  • 1Department of Computer Science and Software Engineering, The University of Melbourne, Parkville, Melbourne, Victoria, 3010 Australia.

Proteins
|June 1, 2006
PubMed
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MUSTANG is a new algorithm for aligning multiple protein structures, offering reliable and robust results. It excels in aligning distantly related proteins and those with conformational changes, outperforming other methods on challenging datasets.

Area of Science:

  • Structural bioinformatics
  • Computational genomics
  • Protein structure analysis

Background:

  • Multiple structural alignment is crucial for understanding protein function and evolution.
  • Existing algorithms face challenges with distantly related proteins or conformational variations.

Purpose of the Study:

  • To introduce MUSTANG (MUltiple STructural AligNment AlGorithm), a novel algorithm for multiple protein structure alignment.
  • To evaluate MUSTANG's accuracy and robustness compared to existing methods.

Main Methods:

  • MUSTANG utilizes spatial information from C(alpha) atoms for alignment.
  • The algorithm employs a progressive pairwise heuristic with advanced refinement phases.
  • Structural alignments are validated against curated databases and benchmark datasets.

Related Experiment Videos

Main Results:

  • MUSTANG demonstrates comparable performance to established tools for closely related proteins.
  • The algorithm shows superior reliability on datasets with distantly related proteins or conformational changes.
  • MUSTANG generates both multiple sequence alignments and structural superpositions.

Conclusions:

  • MUSTANG provides a reliable and robust solution for multiple protein structure alignment.
  • The algorithm is particularly effective for challenging datasets, advancing structural genomics research.