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Sequential assignment of 2D-NMR spectra of proteins using genetic algorithms
R Wehrens1, C Lucasius, L Buydens
1Catholic University of Nijmegen, The Netherlands.
Journal of Chemical Information and Computer Sciences
|March 1, 1993
Summary
Genetic algorithms can solve complex protein NMR spectral assignment problems, even with noisy or incomplete data. This approach aids in determining protein structures by accurately assigning spectral patterns to amino acid sequences.
Area of Science:
- Biochemistry
- Computational Biology
- Structural Biology
Background:
- Sequential assignment of 2D protein NMR spectra is crucial for protein structure determination.
- This assignment process is often underconstrained due to more spectral patterns than amino acid positions.
- Preliminary assignments can contain uncertainties, complicating the process.
Purpose of the Study:
- To investigate the application of genetic algorithms for the sequential assignment of 2D protein NMR spectra.
- To evaluate the robustness of genetic algorithms in handling underconstrained problems and data uncertainties.
Main Methods:
- Utilized genetic algorithms to address the challenge of sequential assignment in 2D protein NMR spectroscopy.
- Explored the algorithm's performance with potentially erroneous or incomplete input data.
Main Results:
- Genetic algorithms demonstrate utility in sequential spectral assignment despite underconstrained conditions.
- The approach remains effective even when significant errors are present in the input data.
Conclusions:
- Genetic algorithms offer a viable computational strategy for protein NMR spectral assignment.
- The method shows resilience to data inaccuracies, making it practical for real-world applications.