ISSN:
0192-8651
Keywords:
Computational Chemistry and Molecular Modeling
;
Biochemistry
Source:
Wiley InterScience Backfile Collection 1832-2000
Topics:
Chemistry and Pharmacology
,
Computer Science
Notes:
One task in the interpretation of the 2-D nuclear magnetic resonance (NMR) spectrum is to assign its signal patterns to their corresponding amino acids in proteins or polypeptides. To carry out this task of interpretation, one requires sufficient chemical knowledge and expertise to reason from a set of highly noisy data. We present a system called RUBIDIUM (a Rule-Based Identification in 2-D NMR Spectrum) to formulate the expertise and automate the process of interpretation. Given a protein or polypeptide with a known amino acid sequence and the 2-D NMR spectra (both COSY and NOESY), RUBIDIUM yields plausible assignments of lines that account for most signals observed in the spectrum and conform to prior chemical knowledge. Rules of pattern matching are used to detect plausible signal patterns. The expertise of the sequence-specific assignment task is formulated to assign a signal pattern to amino acids. To cope with ambiguities and noise, RUBIDIUM adopts various low-level data preprocessing techniques, the strategy of divide and conquer, and the relaxation technique to decrease the complexity and recover from overconstrained conditions. The polypeptides oxytocin and vasopressin are used to illustrate the performance of RUBIDIUM. © John Wiley & Sons, Inc.
Additional Material:
7 Ill.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1002/jcc.540141006
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