Protein structural class identification directly from NMR spectra using averaged chemical shifts

Research output: Contribution to journalArticle

25 Citations (Scopus)

Abstract

Knowledge of the three-dimensional structure of proteins is integral to understanding their functions, and a necessity in the era of proteomics. A wide range of computational methods is employed to estimate the secondary, tertiary, and quaternary structures of proteins. Comprehensive experimental methods, on the other hand, are limited to nuclear magnetic resonance (NMR) and X-ray crystallography. The full characterization of individual structures, using either of these techniques, is extremely time intensive. The demands of high throughput proteomics necessitate the development of new, faster experimental methods for providing structural information. As a first step toward such a method, we explore the possibility of determining the structural classes of proteins directly from their NMR spectra, prior to resonance assignment, using averaged chemical shifts. This is achieved by correlating NMR-based information with empirical structure-based information available in widely used electronic databases. The results are analyzed statistically for their significance. The robustness of the method as a structure predictor is probed by applying it to a set of proteins of unknown structure. Our results show that this NMR-based method can be used as a low-resolution tool for protein structural class identification.

Original languageEnglish (US)
Pages (from-to)2054-2064
Number of pages11
JournalBioinformatics
Volume19
Issue number16
DOIs
StatePublished - Nov 1 2003
Externally publishedYes

Fingerprint

Nuclear Magnetic Resonance
Chemical shift
Magnetic Resonance Spectroscopy
Nuclear magnetic resonance
Proteins
Protein
Proteomics
Quaternary Protein Structure
X ray crystallography
Computational methods
X Ray Crystallography
Tertiary Protein Structure
Computational Methods
High Throughput
Throughput
Class
Predictors
Assignment
Electronics
Databases

ASJC Scopus subject areas

  • Clinical Biochemistry
  • Computer Science Applications
  • Computational Theory and Mathematics

Cite this

Protein structural class identification directly from NMR spectra using averaged chemical shifts. / Mielke, S. P.; Krishnan, Viswanathan V.

In: Bioinformatics, Vol. 19, No. 16, 01.11.2003, p. 2054-2064.

Research output: Contribution to journalArticle

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