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Algorithms, applications, and challenges of protein structure alignment.

Jianzhu Ma1, Sheng Wang1

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Advances in Protein Chemistry and Structural Biology
|March 18, 2014
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Summary
This summary is machine-generated.

Protein structure alignment, crucial for understanding protein similarity and evolution, remains an NP-hard problem. This review surveys heuristic methods for pairwise and multiple protein structure alignment, highlighting advancements and future challenges.

Keywords:
Multiple protein structure alignmentPairwise protein structure alignmentProtein structural alphabetProtein structureStructural alphabet substitution matrix

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Area of Science:

  • Computational structural biology
  • Bioinformatics
  • Protein structure analysis

Background:

  • Protein structure alignment is vital for assessing protein similarity, homology detection, and understanding evolutionary relationships.
  • Both pairwise and multiple structure alignments are fundamental in computational structural biology, with applications ranging from fold space construction to evolutionary divergence analysis.
  • The inherent complexity of protein structure alignment classifies it as an NP-hard problem, necessitating heuristic approaches for computational tractability.

Purpose of the Study:

  • To provide a comprehensive review of current protein structure alignment methods, with a focus on publicly available web servers.
  • To discuss advancements in heuristic strategies for improving pairwise alignment accuracy and multiple structure alignment efficiency.
  • To identify open challenges and future research directions in protein structure alignment, including large-scale complex alignments and rapid database searching.

Main Methods:

  • Survey of existing heuristic methods for pairwise and multiple protein structure alignment.
  • Analysis of different heuristic levels: structure representation, rigidity/flexibility, scoring functions, search algorithms, and merging strategies.
  • Focus on publicly accessible web server implementations of alignment algorithms.

Main Results:

  • Overview of various heuristic approaches applied to protein structure alignment problems.
  • Discussion of progress in enhancing the accuracy of pairwise alignments and the efficiency of multiple alignments.
  • Identification of key areas for future development, such as handling large, complex structures and optimizing database search speeds.

Conclusions:

  • Heuristic methods are essential for addressing the computational complexity of protein structure alignment.
  • Continuous advancements are being made in both pairwise and multiple alignment techniques, improving accuracy and efficiency.
  • Future research should focus on scalability, database searching, and alignment of complex protein structures.