Combining ambiguous chemical shift mapping with structure-based backbone and NOE assignment from 15N-NOESY

Richard Jang, Xin Gao, Ming Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Chemical shift mapping is an important technique in NMRbased drug screening for identifying the atoms of a target protein that potentially bind to a drug molecule upon the molecule's introduction in increasing concentrations. The goal is to obtain a mapping of peaks with known residue assignment from the reference spectrum of the unbound protein to peaks with unknown assignment in the target spectrum of the bound protein. Although a series of perturbed spectra help to trace a path from reference peaks to target peaks, a one-to-one mapping generally is not possible, especially for large proteins, due to errors, such as noise peaks, missing peaks, missing but then reappearing, overlapped, and new peaks not associated with any peaks in the reference. Due to these difficulties, the mapping is typically done manually or semi-automatically. However, automated methods are necessary for high-throughput drug screening. We present PeakWalker, a novel peak walking algorithm for fast-exchange systems that models the errors explicitly and performs many-to-one mapping. On the proteins: hBclXL, UbcH5B, and histone H1, it achieves an average accuracy of over 95% with less than 1.5 residues predicted per target peak. Given these mappings as input, we present PeakAssigner, a novel combined structure-based backbone resonance and NOE assignment algorithm that uses just 15N-NOESY, while avoiding TOCSY experiments and 13C- labeling, to resolve the ambiguities for a one-toone mapping. On the three proteins, it achieves an average accuracy of 94% or better. Copyright © 2011 ACM.
Original languageEnglish (US)
Title of host publicationProceedings of the 2nd ACM Conference on Bioinformatics, Computational Biology and Biomedicine - BCB '11
PublisherAssociation for Computing Machinery (ACM)
Number of pages11
ISBN (Print)9781450307963
StatePublished - 2011

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01


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