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Detection of circular permutations within protein structures using CE-CP.

Spencer E Bliven1, Philip E Bourne1, Andreas Prlić2

  • 1Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA 92093, USA, National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA and RCSB Protein Data Bank, San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA 92093, USA Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA 92093, USA, National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA and RCSB Protein Data Bank, San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA 92093, USA.

Bioinformatics (Oxford, England)
|December 16, 2014
PubMed
Summary
This summary is machine-generated.

We developed Combinatorial Extension for Circular Permutations (CE-CP), a new algorithm for comparing circularly permuted protein structures. This user-friendly tool is integrated into the RCSB Protein Data Bank for broader accessibility.

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Area of Science:

  • Structural bioinformatics
  • Computational biology
  • Protein science

Background:

  • Circular permutation is a significant protein rearrangement impacting protein function, stability, and evolution.
  • Detecting relationships in circularly permuted proteins is challenging for standard sequence and structure comparison algorithms.
  • Artificial circular permutations are valuable tools in protein research.

Purpose of the Study:

  • To develop a novel algorithm for the structural comparison of circularly permuted proteins.
  • To create a user-friendly tool integrated with a major protein database.
  • To facilitate the study and analysis of protein circular permutations.

Main Methods:

  • Development of the Combinatorial Extension for Circular Permutations (CE-CP) algorithm.
  • Integration of CE-CP into the RCSB Protein Data Bank.
  • Testing the algorithm on curated collections of circularly permuted proteins.
  • Implementation of visualization tools (Jmol) for web and desktop applications.

Main Results:

  • The CE-CP algorithm enables effective structural comparison of circularly permuted proteins.
  • The tool is accessible via the RCSB website, enhancing usability.
  • Pairwise alignments generated by CE-CP are visualizable and exportable in multiple formats.

Conclusions:

  • CE-CP provides a specialized and accessible solution for analyzing circularly permuted protein structures.
  • The algorithm and its integration facilitate research into protein evolution, function, and design.
  • Availability through RCSB and BioJava promotes wider adoption and further development.