Published September 2004 | Version v1
Journal article

From NMR chemical shifts to amino acid types: Investigation of the predictive power carried by nuclei

  • 1. Institut de Biologie Physico-Chimique, Laboratoire de Biochimie Theorique, CNRS UPR 9080 (France)
  • 2. INRA - Domaine de Vilvert, Unite Mathematique Informatique et Genome (France)

Description

An approach to automatic prediction of the amino acid type from NMR chemical shift values of its nuclei is presented here, in the frame of a model to calculate the probability of an amino acid type given the set of chemical shifts. The method relies on systematic use of all chemical shift values contained in the BioMagResBank (BMRB). Two programs were designed, one (BMRB stats) for extracting statistical chemical shift parameters from the BMRB and another one (RESCUE2) for computing the probabilities of each amino acid type, given a set of chemical shifts. The Bayesian prediction scheme presented here is compared to other methods already proposed: PROTYP (Grzesiek and Bax, J. Biomol. NMR, 3, 185-204, 1993) RESCUE (Pons and Delsuc, J. Biomol. NMR, 15, 15-26, 1999) and PLATON (Labudde et al., J. Biomol. NMR, 25, 41-53, 2003) and is found to be more sensitive and more specific. Using this scheme, we tested various sets of nuclei. The two nuclei carrying the most information are Cβ and Hβ, in agreement with observations made in Grzesiek and Bax, 1993. Based on four nuclei: Hβ, Cβ, Cα and C', it is possible to increase correct predictions to a rate of more than 75%. Taking into account the correlations between the nuclei chemical shifts has only a slight impact on the percentage of correct predictions: indeed, the largest correlation coefficients display similar features on all amino acids

Additional details

Publishing Information

Journal Title
Journal of Biomolecular NMR
Journal Volume
30
Journal Issue
1
Journal Page Range
p. 47-60
ISSN
0925-2738

INIS

Country of Publication
Netherlands
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
39113447
Subject category
S60: APPLIED LIFE SCIENCES;
Descriptors DEI
AMINO ACIDS; CHEMICAL SHIFT; FORECASTING; NUCLEAR MAGNETIC RESONANCE; PROTEIN STRUCTURE
Descriptors DEC
CARBOXYLIC ACIDS; MAGNETIC RESONANCE; ORGANIC ACIDS; ORGANIC COMPOUNDS; RESONANCE

Optional Information

Copyright
Copyright (c) 2004 Kluwer Academic Publishers