Department of Chemistry
Document Type
Article
Date of this Version
February 2006
Abstract
This article formulates the multidimensional nuclear Overhauser effect spectroscopy (NOESY) interpretation problem using graph theory and presents a novel, bottom-up, topology-constrained distance network analysis algorithm for NOESY cross peak interpretation using assigned resonances. AutoStructure is a software suite that implements this topology- constrained distance network analysis algorithm and iteratively generates structures using the three-dimensional (3D) protein structure calculation programs XPLOR/CNS or DYANA. The minimum input for AutoStructure includes the amino acid sequence, a list of resonance assignments, and lists of 2D, 3D, and/or 4D-NOESY cross peaks. AutoStructure can also analyze homodimeric proteins when X-filtered NOESY experiments are available. The quality of input data and final 3D structures is evaluated using recall, precision, and F-measure (RPF) scores, a statistical measure of goodness of fit with the input data. AutoStructure has been tested on three protein NMR data sets for which high-quality structures have previously been solved by an expert, and yields comparable high-quality distance constraint lists and 3D protein structures in hours. We also compare several protein structures determined using AutoStructure with corresponding homologous proteins determined with other independent methods. The program has been used in more than two dozen protein structure determinations, several of which have already been published.
This document includes the revised supplementary materialnot published with the printed journal edition.
Comments
Published in Proteins: Structure, Function, and Bioinformatics 62:3 (15 February 2006), pp. 587-603. Copyright © 2006 Wiley-Liss, Inc., A Wiley Company. Used by permission. Digital Object Identifier (DOI) 10.1002/prot.20820 http://www3.interscience.wiley.com/cgi-bin/jhome/36176
This document includes the revised supplementary materialnot published with the printed journal edition.