Literature DB >> 18686985

SeMoP: a new computational strategy for the unrestricted search for modified peptides using LC-MS/MS data.

Christian Baumgartner1, Tomas Rejtar, Majlinda Kullolli, Lakshmi Manohar Akella, Barry L Karger.   

Abstract

A novel computational approach, termed Search for Modified Peptides (SeMoP), for the unrestricted discovery and verification of peptide modifications in shotgun proteomic experiments using low resolution ion trap MS/MS spectra is presented. Various peptide modifications, including post-translational modifications, sequence polymorphisms, as well as sample handling-induced changes, can be identified using this approach. SeMoP utilizes a three-step strategy: (1) a standard database search to identify proteins in a sample; (2) an unrestricted search for modifications using a newly developed algorithm; and (3) a second standard database search targeted to specific modifications found using the unrestricted search. This targeted approach provides verification of discovered modifications and, due to increased sensitivity, a general increase in the number of peptides with the specific modification. The feasibility of the overall strategy has been first demonstrated in the analysis of 65 plasma proteins. Various sample handling induced modifications, such as beta-elimination of disulfide bridges and pyrocarbamidomethylation, as well as biologically induced modifications, such as phosphorylation and methylation, have been detected. A subsequent targeted Sequest search has been used to verify selected modifications, and a 4-fold increase in the number of modified peptides was obtained. In a second application, 1367 proteins of a cervical cancer cell line were processed, leading to detection of several novel amino acid substitutions. By conducting the search against a database of peptides derived from proteins with decoy sequences, a false discovery rate of less than 5% for the unrestricted search resulted. SeMoP is shown to be an effective and easily implemented approach for the discovery and verification of peptide modifications.

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Year:  2008        PMID: 18686985      PMCID: PMC2556171          DOI: 10.1021/pr800277y

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  33 in total

1.  Shotgun identification of protein modifications from protein complexes and lens tissue.

Authors:  Michael J MacCoss; W Hayes McDonald; Anita Saraf; Rovshan Sadygov; Judy M Clark; Joseph J Tasto; Kathleen L Gould; Dirk Wolters; Michael Washburn; Avery Weiss; John I Clark; John R Yates
Journal:  Proc Natl Acad Sci U S A       Date:  2002-06-11       Impact factor: 11.205

2.  Identification of protein modifications using MS/MS de novo sequencing and the OpenSea alignment algorithm.

Authors:  Brian C Searle; Surendra Dasari; Phillip A Wilmarth; Mark Turner; Ashok P Reddy; Larry L David; Srinivasa R Nagalla
Journal:  J Proteome Res       Date:  2005 Mar-Apr       Impact factor: 4.466

3.  P-Mod: an algorithm and software to map modifications to peptide sequences using tandem MS data.

Authors:  Beau T Hansen; Sean W Davey; Amy-Joan L Ham; Daniel C Liebler
Journal:  J Proteome Res       Date:  2005 Mar-Apr       Impact factor: 4.466

4.  Identification of post-translational modifications by blind search of mass spectra.

Authors:  Dekel Tsur; Stephen Tanner; Ebrahim Zandi; Vineet Bafna; Pavel A Pevzner
Journal:  Nat Biotechnol       Date:  2005-11-27       Impact factor: 54.908

Review 5.  Analysis of posttranslational modifications of proteins by tandem mass spectrometry.

Authors:  Martin R Larsen; Morten B Trelle; Tine E Thingholm; Ole N Jensen
Journal:  Biotechniques       Date:  2006-06       Impact factor: 1.993

6.  Gaining knowledge from previously unexplained spectra-application of the PTM-Explorer software to detect PTM in HUPO BPP MS/MS data.

Authors:  Daniel C Chamrad; Gerhard Körting; Heike Schäfer; Christian Stephan; Herbert Thiele; Rolf Apweiler; Helmut E Meyer; Katrin Marcus; Martin Blüggel
Journal:  Proteomics       Date:  2006-09       Impact factor: 3.984

7.  Large-scale unrestricted identification of post-translation modifications using tandem mass spectrometry.

Authors:  Moshe Havilio; Assaf Wool
Journal:  Anal Chem       Date:  2007-02-15       Impact factor: 6.986

8.  Proteome-wide identification of proteins and their modifications with decreased ambiguities and improved false discovery rates using unique sequence tags.

Authors:  Yufeng Shen; Nikola Tolić; Kim K Hixson; Samuel O Purvine; Ljiljana Pasa-Tolić; Wei-Jun Qian; Joshua N Adkins; Ronald J Moore; Richard D Smith
Journal:  Anal Chem       Date:  2008-02-14       Impact factor: 6.986

9.  Proteomic analysis of high-grade dysplastic cervical cells obtained from ThinPrep slides using laser capture microdissection and mass spectrometry.

Authors:  Ye Gu; Shiaw-Lin Wu; Jane L Meyer; William S Hancock; Lawrence J Burg; James Linder; David W Hanlon; Barry L Karger
Journal:  J Proteome Res       Date:  2007-09-29       Impact factor: 4.466

10.  Surface accessibility of protein post-translational modifications.

Authors:  Chi Nam Ignatius Pang; Andrew Hayen; Marc Ronald Wilkins
Journal:  J Proteome Res       Date:  2007-04-12       Impact factor: 4.466

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  14 in total

Review 1.  The significance, development and progress of high-throughput combinatorial histone code analysis.

Authors:  Nicolas L Young; Peter A Dimaggio; Benjamin A Garcia
Journal:  Cell Mol Life Sci       Date:  2010-08-04       Impact factor: 9.261

2.  A novel approach for untargeted post-translational modification identification using integer linear optimization and tandem mass spectrometry.

Authors:  Richard C Baliban; Peter A DiMaggio; Mariana D Plazas-Mayorca; Nicolas L Young; Benjamin A Garcia; Christodoulos A Floudas
Journal:  Mol Cell Proteomics       Date:  2010-01-26       Impact factor: 5.911

3.  DeltAMT: a statistical algorithm for fast detection of protein modifications from LC-MS/MS data.

Authors:  Yan Fu; Li-Yun Xiu; Wei Jia; Ding Ye; Rui-Xiang Sun; Xiao-Hong Qian; Si-Min He
Journal:  Mol Cell Proteomics       Date:  2011-02-14       Impact factor: 5.911

Review 4.  Quantitative proteomic analysis of histone modifications.

Authors:  He Huang; Shu Lin; Benjamin A Garcia; Yingming Zhao
Journal:  Chem Rev       Date:  2015-02-17       Impact factor: 60.622

5.  PTMiner: Localization and Quality Control of Protein Modifications Detected in an Open Search and Its Application to Comprehensive Post-translational Modification Characterization in Human Proteome.

Authors:  Zhiwu An; Linhui Zhai; Wantao Ying; Xiaohong Qian; Fuzhou Gong; Minjia Tan; Yan Fu
Journal:  Mol Cell Proteomics       Date:  2018-11-12       Impact factor: 5.911

Review 6.  A survey of computational methods and error rate estimation procedures for peptide and protein identification in shotgun proteomics.

Authors:  Alexey I Nesvizhskii
Journal:  J Proteomics       Date:  2010-09-08       Impact factor: 4.044

7.  PILOT_PROTEIN: identification of unmodified and modified proteins via high-resolution mass spectrometry and mixed-integer linear optimization.

Authors:  Richard C Baliban; Peter A Dimaggio; Mariana D Plazas-Mayorca; Benjamin A Garcia; Christodoulos A Floudas
Journal:  J Proteome Res       Date:  2012-07-26       Impact factor: 4.466

8.  ETISEQ--an algorithm for automated elution time ion sequencing of concurrently fragmented peptides for mass spectrometry-based proteomics.

Authors:  Jason W H Wong; Alexander B Schwahn; Kevin M Downard
Journal:  BMC Bioinformatics       Date:  2009-08-10       Impact factor: 3.169

9.  Desulfurization of cysteine-containing peptides resulting from sample preparation for protein characterization by mass spectrometry.

Authors:  Zhouxi Wang; Tomas Rejtar; Zhaohui Sunny Zhou; Barry L Karger
Journal:  Rapid Commun Mass Spectrom       Date:  2010-02       Impact factor: 2.419

10.  MUMAL: multivariate analysis in shotgun proteomics using machine learning techniques.

Authors:  Fabio R Cerqueira; Ricardo S Ferreira; Alcione P Oliveira; Andreia P Gomes; Humberto J O Ramos; Armin Graber; Christian Baumgartner
Journal:  BMC Genomics       Date:  2012-10-19       Impact factor: 3.969

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