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From NMR chemical shifts to amino acid types: Investigation of the predictive power carried by nuclei
Authors:Antoine Marin  Thérèse E Malliavin  Pierre Nicolas  Marc-André Delsuc
Institution:Laboratoire de Biochimie Théorique, CNRS UPR 9080, Institut de Biologie Physico-Chimique, 13 rue P. et M. Curie, 75005 Paris, France.
Abstract: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 RESCUE and PLATON 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 C(beta) and H(beta), in agreement with observations made in Grzesiek and Bax, 1993. Based on four nuclei: H(beta), C(beta), C(alpha) 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.
Keywords:automatic assignment  Bayes theorem  Bayesian decision  BioMagResBank  chemical shift  NMR  structural proteomics
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