Document Detail

Extending the coverage of spectral libraries: a neighbor-based approach to predicting intensities of peptide fragmentation spectra.
MedLine Citation:
PMID:  23303707     Owner:  NLM     Status:  MEDLINE    
Searching spectral libraries in MS/MS is an important new approach to improving the quality of peptide and protein identification. The idea relies on the observation that ion intensities in an MS/MS spectrum of a given peptide are generally reproducible across experiments, and thus, matching between spectra from an experiment and the spectra of previously identified peptides stored in a spectral library can lead to better peptide identification compared to the traditional database search. However, the use of libraries is greatly limited by their coverage of peptide sequences: even for well-studied organisms a large fraction of peptides have not been previously identified. To address this issue, we propose to expand spectral libraries by predicting the MS/MS spectra of peptides based on the spectra of peptides with similar sequences. We first demonstrate that the intensity patterns of dominant fragment ions between similar peptides tend to be similar. In accordance with this observation, we develop a neighbor-based approach that first selects peptides that are likely to have spectra similar to the target peptide and then combines their spectra using a weighted K-nearest neighbor method to accurately predict fragment ion intensities corresponding to the target peptide. This approach has the potential to predict spectra for every peptide in the proteome. When rigorous quality criteria are applied, we estimate that the method increases the coverage of spectral libraries available from the National Institute of Standards and Technology by 20-60%, although the values vary with peptide length and charge state. We find that the overall best search performance is achieved when spectral libraries are supplemented by the high quality predicted spectra.
Chao Ji; Randy J Arnold; Kevin J Sokoloski; Richard W Hardy; Haixu Tang; Predrag Radivojac
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Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural     Date:  2013-02-04
Journal Detail:
Title:  Proteomics     Volume:  13     ISSN:  1615-9861     ISO Abbreviation:  Proteomics     Publication Date:  2013 Mar 
Date Detail:
Created Date:  2013-03-08     Completed Date:  2013-08-26     Revised Date:  2014-03-07    
Medline Journal Info:
Nlm Unique ID:  101092707     Medline TA:  Proteomics     Country:  Germany    
Other Details:
Languages:  eng     Pagination:  756-65     Citation Subset:  IM    
Copyright Information:
© 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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MeSH Terms
Databases, Protein*
High-Throughput Screening Assays / methods*
Peptide Library
Peptides / chemistry*
Proteomics / methods*
Tandem Mass Spectrometry / methods*
Grant Support
R01 AI090077/AI/NIAID NIH HHS; R01 AI090077/AI/NIAID NIH HHS; R01 GM103725/GM/NIGMS NIH HHS; R01 RR024236/RR/NCRR NIH HHS; R01 RR024236-01A1/RR/NCRR NIH HHS; R01GM103725-04/GM/NIGMS NIH HHS; U24 CA126480-01/CA/NCI NIH HHS
Reg. No./Substance:
0/Peptide Library; 0/Peptides

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

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