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

Handle URI:
http://hdl.handle.net/10754/564350
Title:
Combining ambiguous chemical shift mapping with structure-based backbone and NOE assignment from 15N-NOESY
Authors:
Jang, Richard; Gao, Xin ( 0000-0002-7108-3574 ) ; Li, Ming
Abstract:
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.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division; Computer Science Program; Computational Bioscience Research Center (CBRC); Structural and Functional Bioinformatics Group
Publisher:
Association for Computing Machinery (ACM)
Journal:
Proceedings of the 2nd ACM Conference on Bioinformatics, Computational Biology and Biomedicine - BCB '11
Conference/Event name:
2011 ACM Conference on Bioinformatics, Computational Biology and Biomedicine, ACM-BCB 2011
Issue Date:
2011
DOI:
10.1145/2147805.2147814
Type:
Conference Paper
ISBN:
9781450307963
Appears in Collections:
Conference Papers; Structural and Functional Bioinformatics Group; Computer Science Program; Computational Bioscience Research Center (CBRC); Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorJang, Richarden
dc.contributor.authorGao, Xinen
dc.contributor.authorLi, Mingen
dc.date.accessioned2015-08-04T06:24:34Zen
dc.date.available2015-08-04T06:24:34Zen
dc.date.issued2011en
dc.identifier.isbn9781450307963en
dc.identifier.doi10.1145/2147805.2147814en
dc.identifier.urihttp://hdl.handle.net/10754/564350en
dc.description.abstractChemical 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.en
dc.publisherAssociation for Computing Machinery (ACM)en
dc.subjectChemical shift mappingen
dc.subjectChemical shift perturbationen
dc.subjectNMRen
dc.subjectNuclear magnetic resonanceen
dc.subjectResonance assignmenten
dc.subjectSAR by NMRen
dc.titleCombining ambiguous chemical shift mapping with structure-based backbone and NOE assignment from 15N-NOESYen
dc.typeConference Paperen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.contributor.departmentComputer Science Programen
dc.contributor.departmentComputational Bioscience Research Center (CBRC)en
dc.contributor.departmentStructural and Functional Bioinformatics Groupen
dc.identifier.journalProceedings of the 2nd ACM Conference on Bioinformatics, Computational Biology and Biomedicine - BCB '11en
dc.conference.date1 August 2011 through 3 August 2011en
dc.conference.name2011 ACM Conference on Bioinformatics, Computational Biology and Biomedicine, ACM-BCB 2011en
dc.conference.locationChicago, ILen
dc.contributor.institutionDavid R. Cheriton School of Computer Science, University of Waterloo, 200 University Avenue West, Waterloo, ON N2L 3G1, Canadaen
kaust.authorGao, Xinen
All Items in KAUST are protected by copyright, with all rights reserved, unless otherwise indicated.