Abstract #301419

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JSM 2003 Abstract #301419
Activity Number: 296
Type: Contributed
Date/Time: Tuesday, August 5, 2003 : 2:00 PM to 3:50 PM
Sponsor: Biopharmaceutical Section
Abstract - #301419
Title: Assessment of Uncertainty in Protein NMR Assignments Using Bayesian Model Averaging
Author(s): Olga Vitek*+ and Jan Vitek and Bruce A. Craig and Chris Bailey-Kellogg
Companies: Duke University and Purdue University and Purdue University and Purdue University
Address: 3430 Crawford St., West Lafayette, IN, 47906-1195,
Keywords: protein structure ; NMR spectroscopy ; Bayes factor ; model averaging
Abstract:

X-ray crystallography and nuclear magnetic resonance (NMR) spectroscopy are currently the only experimental techniques capable of determining protein structure in atomic detail. The NMR-based approach is particularly valuable for studies of 3D structure, dynamics, and intermolecular interactions of proteins in solution. However, the data it provides are noisy and incomplete, and accuracy of the result depends on the extent and quality of data that can be obtained. Despite the growing popularity of the NMR-based structure determination, little work has been done for its statistical characterization. This talk discusses a Bayesian modeling framework for backbone resonance assignment, which is an essential step of NMR-based structure determination. Bayesian modeling provides a natural measure of consistency of an assignment with the data, as well as means of finding candidate assignments. Bayesian model averaging provides estimates of quantities of interest and their standard errors while taking into account the uncertainty in data and in assignment.

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