Literature DB >> 18842605

IPEP: an in silico tool to examine proteolytic peptides for mass spectrometry.

Dihui Lu1, Richard Z Liu, Victoria Izumi, David Fenstermacher, Eric B Haura, John Koomen, Steven A Eschrich.   

Abstract

UNLABELLED: Peptide-based proteomics supports identification and quantification as well as localization of post-translational modifications (PTMs) within proteins extracted from biological samples. The 'bottom-up' approach involves the digestion of proteins into peptide fragments that can be detected and sequenced with liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). A web-based application, iPEP, was developed to compare the effectiveness of different proteolytic digests in detecting specific sequences. Furthermore, peptide populations can be examined to help optimize detection of certain groups of proteins relative to the proteome and the digested peptidome. The application reports proteolytic peptide sequences, theoretical molecular weights and functional annotations using Gene Ontology (GO) terms. The iPEP tool can assist with experimental design by maximizing the detection of proteins, consensus sites and modified residues of interest for individual proteins or as part of large-scale proteomic assays. AVAILABILITY: http://ipep.moffitt.org

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Year:  2008        PMID: 18842605     DOI: 10.1093/bioinformatics/btn511

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  6 in total

1.  Acid hydrolysis of proteins in matrix assisted laser desorption ionization matrices.

Authors:  Elizabeth Remily-Wood; Hayley Dirscherl; John M Koomen
Journal:  J Am Soc Mass Spectrom       Date:  2009-07-14       Impact factor: 3.109

Review 2.  Methods for investigation of targeted kinase inhibitor therapy using chemical proteomics and phosphorylation profiling.

Authors:  Bin Fang; Eric B Haura; Keiran S Smalley; Steven A Eschrich; John M Koomen
Journal:  Biochem Pharmacol       Date:  2010-03-31       Impact factor: 5.858

3.  ProteaseGuru: A Tool for Protease Selection in Bottom-Up Proteomics.

Authors:  Rachel M Miller; Khairina Ibrahim; Lloyd M Smith
Journal:  J Proteome Res       Date:  2021-03-04       Impact factor: 4.466

4.  Comparative Proteomic Analysis of saccharopolyspora spinosa SP06081 and PR2 strains reveals the differentially expressed proteins correlated with the increase of spinosad yield.

Authors:  Yushuang Luo; Xuezhi Ding; Liqiu Xia; Fan Huang; Wenping Li; Shaoya Huang; Ying Tang; Yunjun Sun
Journal:  Proteome Sci       Date:  2011-07-16       Impact factor: 2.480

5.  Differential proteomic profiling reveals regulatory proteins and novel links between primary metabolism and spinosad production in Saccharopolyspora spinosa.

Authors:  Qi Yang; Xuezhi Ding; Xuemei Liu; Shuang Liu; Yunjun Sun; Ziquan Yu; Shengbiao Hu; Jie Rang; Hao He; Lian He; Liqiu Xia
Journal:  Microb Cell Fact       Date:  2014-02-21       Impact factor: 5.328

6.  Effects of acuC on the growth development and spinosad biosynthesis of Saccharopolyspora spinosa.

Authors:  Zhudong Liu; Jie Xiao; Jianli Tang; Yang Liu; Ling Shuai; Li Cao; Ziyuan Xia; Xuezhi Ding; Jie Rang; Liqiu Xia
Journal:  Microb Cell Fact       Date:  2021-07-22       Impact factor: 5.328

  6 in total

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