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Automated sequence-specific protein NMR assignment using the memetic algorithm match

Academic Article
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Overview

authors

  • Volk, J.
  • Herrmann, T.
  • Wuthrich, Kurt

publication date

  • July 2008

journal

  • Journal of Biomolecular NMR  Journal

abstract

  • MATCH (Memetic Algorithm and Combinatorial Optimization Heuristics) is a new memetic algorithm for automated sequence-specific polypeptide backbone NMR assignment of proteins. MATCH employs local optimization for tracing partial sequence-specific assignments within a global, population-based search environment, where the simultaneous application of local and global optimization heuristics guarantees high efficiency and robustness. MATCH thus makes combined use of the two predominant concepts in use for automated NMR assignment of proteins. Dynamic transition and inherent mutation are new techniques that enable automatic adaptation to variable quality of the experimental input data. The concept of dynamic transition is incorporated in all major building blocks of the algorithm, where it enables switching between local and global optimization heuristics at any time during the assignment process. Inherent mutation restricts the intrinsically required randomness of the evolutionary algorithm to those regions of the conformation space that are compatible with the experimental input data. Using intact and artificially deteriorated APSY-NMR input data of proteins, MATCH performed sequence-specific resonance assignment with high efficiency and robustness.

subject areas

  • Algorithms
  • Amino Acid Sequence
  • Databases, Protein
  • Mathematics
  • Molecular Sequence Data
  • Nuclear Magnetic Resonance, Biomolecular
  • Protein Conformation
  • Sequence Analysis, Protein
  • Software
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Research

keywords

  • automation
  • genetic algorithm
  • protein NMR
  • sequence-specific resonance assignment
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Identity

International Standard Serial Number (ISSN)

  • 0925-2738

Digital Object Identifier (DOI)

  • 10.1007/s10858-008-9243-5

PubMed ID

  • 18512031
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Additional Document Info

start page

  • 127

end page

  • 138

volume

  • 41

issue

  • 3

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