Automated sequence-specific protein NMR assignment using the memetic algorithm MATCH
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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.
KeywordsProtein NMR Sequence-specific resonance assignment Genetic algorithm Automation
We thank Dr. B. Pedrini for sharing his experience with applications of MATCH for backbone resonance assignments in a variety of proteins. Financial support by the Schweizerischer Nationalfonds (project 3100-AO-113838) is gratefully acknowledged.
- Atreya HS, Chary KVR, Govil G (2002) Automated NMR assignments of proteins for high throughput structure determination: TATAPRO II. Curr Sci 83:1372–1376Google Scholar
- Billeter M, Basus VJ, Kuntz ID (1988) ID: a program for semi-automatic sequential resonance assignments in protein 1H nuclear magnetic resonance spectra. J Magn Reson 76:400–415Google Scholar
- Corne D, Dorigo M, Glover F (1999) New ideas in optimization. McGraw-HillGoogle Scholar
- Eghbalnia HR, Bahrami A, Wang L, Assadi A, Markley JL (2005) Probabilistic identification of spin systems and their assignments including coil-helix inference output (PISTACHIO). J Biomol NMR: 219–233Google Scholar
- Kay LE, Ikura M, Tschudin R, Bax A (1990) Three-dimensional triple-resonance NMR spectroscopy of isotopically enriched proteins. J Magn Reson 89:496–514Google Scholar
- Montelione GT, Wagner G (1990) Conformation independent sequential NMR connections in isotope-enriched polypeptides by 1H–13C-15N triple-resonance experiments. J Magn Reson 83:183–188Google Scholar
- Moscato P (1989) On evolution, search, optimization, genetic algorithms and martial arts: Towards memetic algorithms. Caltech Concurrent Computation Program, C3P ReportGoogle Scholar
- Wüthrich K (1986) NMR of Proteins and Nucleic Acids. Wiley, New YorkGoogle Scholar