Literature DB >> 16013882

InsPecT: identification of posttranslationally modified peptides from tandem mass spectra.

Stephen Tanner1, Hongjun Shu, Ari Frank, Ling-Chi Wang, Ebrahim Zandi, Marc Mumby, Pavel A Pevzner, Vineet Bafna.   

Abstract

Reliable identification of posttranslational modifications is key to understanding various cellular regulatory processes. We describe a tool, InsPecT, to identify posttranslational modifications using tandem mass spectrometry data. InsPecT constructs database filters that proved to be very successful in genomics searches. Given an MS/MS spectrum S and a database D, a database filter selects a small fraction of database D that is guaranteed (with high probability) to contain a peptide that produced S. InsPecT uses peptide sequence tags as efficient filters that reduce the size of the database by a few orders of magnitude while retaining the correct peptide with very high probability. In addition to filtering, InsPecT also uses novel algorithms for scoring and validating in the presence of modifications, without explicit enumeration of all variants. InsPecT identifies modified peptides with better or equivalent accuracy than other database search tools while being 2 orders of magnitude faster than SEQUEST, and substantially faster than X!TANDEM on complex mixtures. The tool was used to identify a number of novel modifications in different data sets, including many phosphopeptides in data provided by Alliance for Cellular Signaling that were missed by other tools.

Mesh:

Substances:

Year:  2005        PMID: 16013882     DOI: 10.1021/ac050102d

Source DB:  PubMed          Journal:  Anal Chem        ISSN: 0003-2700            Impact factor:   6.986


  242 in total

1.  Computational analysis of unassigned high-quality MS/MS spectra in proteomic data sets.

Authors:  Kang Ning; Damian Fermin; Alexey I Nesvizhskii
Journal:  Proteomics       Date:  2010-07       Impact factor: 3.984

2.  Fast multi-blind modification search through tandem mass spectrometry.

Authors:  Seungjin Na; Nuno Bandeira; Eunok Paek
Journal:  Mol Cell Proteomics       Date:  2011-12-20       Impact factor: 5.911

3.  De novo sequencing and homology searching.

Authors:  Bin Ma; Richard Johnson
Journal:  Mol Cell Proteomics       Date:  2011-11-16       Impact factor: 5.911

4.  Protein identification using top-down.

Authors:  Xiaowen Liu; Yakov Sirotkin; Yufeng Shen; Gordon Anderson; Yihsuan S Tsai; Ying S Ting; David R Goodlett; Richard D Smith; Vineet Bafna; Pavel A Pevzner
Journal:  Mol Cell Proteomics       Date:  2011-10-25       Impact factor: 5.911

5.  Speeding up tandem mass spectral identification using indexes.

Authors:  Xiaowen Liu; Alessandro Mammana; Vineet Bafna
Journal:  Bioinformatics       Date:  2012-04-27       Impact factor: 6.937

6.  Identifying proteomic LC-MS/MS data sets with Bumbershoot and IDPicker.

Authors:  Jerry D Holman; Ze-Qiang Ma; David L Tabb
Journal:  Curr Protoc Bioinformatics       Date:  2012-03

7.  System-wide studies of N-lysine acetylation in Rhodopseudomonas palustris reveal substrate specificity of protein acetyltransferases.

Authors:  Heidi A Crosby; Dale A Pelletier; Gregory B Hurst; Jorge C Escalante-Semerena
Journal:  J Biol Chem       Date:  2012-03-13       Impact factor: 5.157

8.  A ranking-based scoring function for peptide-spectrum matches.

Authors:  Ari M Frank
Journal:  J Proteome Res       Date:  2009-05       Impact factor: 4.466

9.  Recognition of methylated peptides by Drosophila melanogaster polycomb chromodomain.

Authors:  Richard S L Stein; Nan Li; Wei He; Elizabeth Komives; Wei Wang
Journal:  J Proteome Res       Date:  2013-02-04       Impact factor: 4.466

10.  Comparison of MS(2)-only, MSA, and MS(2)/MS(3) methodologies for phosphopeptide identification.

Authors:  Peter J Ulintz; Anastasia K Yocum; Bernd Bodenmiller; Ruedi Aebersold; Philip C Andrews; Alexey I Nesvizhskii
Journal:  J Proteome Res       Date:  2009-02       Impact factor: 4.466

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.