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Proteomics

Proteomics. Proteomics. Proteomics directly detects expression of proteins. . Proteome research permits the discovery of new protein markers for diagnostic purposes and of novel molecular targets for drug discovery. 1. SWISS-2DPAGE database.

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Proteomics

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  1. Proteomics

  2. Proteomics • Proteomics directly detects expression of proteins. • Proteome research permits the discovery of new protein markers for diagnostic purposes and of novel molecular targets for drug discovery.

  3. 1. SWISS-2DPAGE database • SWISS-2DPAGE is an annotated two-dimensional polyacrylamide gel electrophoresis (2-D PAGE) database established in 1993. • The SWISS-2DPAGE database is maintained by the Swiss Institute of Bioinformatics, in collaboration with the Central Clinical Chemistry Laboratory of the Geneva University Hospital.

  4. SWISS-2DPAGE Search Page

  5. View entry in original SWISS-2DPAGE format Entry name: VSP2_ARATH Primary accession number:82122 Entered in SWISS-2DPAGE inRelease 13, December 2000 Last modified inRelease 14, October 2001 Name and origin of the protein: DescriptionVegetative storage protein 2. Gene name(s)VSP2 OR AT5G24770FromArabidopsis thaliana (Mouse-ear cress). [TaxID: 3702] TaxonomyEukaryota; Viridiplantae; Streptophyta; Embryophyta; Tracheophyta; Spermatophyta; Magnoliophyta; eudicotyledons; core eudicots; Rosidae; eurosids II; Brassicales; Brassicaceae; Arabidopsis. References[1]  MAPPING ON GEL. Sarazin B., Tonella L., Marques K., Paesano S., Chane-Favre L., Sanchez J.-C., Hochstrasser D.F., Thiellement H.; Submitted (OCT-2000) to the SWISS-2DPAGE database. 2D PAGE maps for identified proteinsCompute the theoretical pI/MwHow to interpret a protein map Arabidopsis thalianaMAP LOCATIONS: SPOT 2D-001KKV: pI=6.47, Mw=29849 *** the clicked spot *** MAPPING: MASS SPECTROMETRY [1].

  6. Mass spectrometry (MS)

  7. 2. PeptIdent • PeptIdent is a tool that allows the identification of proteins using pI, MW and peptide mass fingerprinting data. Experimentally measured, user-specified peptide masses are compared with the theoretical peptides calculated for all proteins in the SWISS-PROT/TrEMBL databases.

  8. 3. Mascot • Mascot is a powerful search engine that uses mass spectrometry data to identify proteins from primary sequence databases.

  9. Concise Protein Summary Report • Switch to full Protein Summary Report • To create a bookmark for this report, right click this link: Concise Summary Report (../data/20020713/FATeiic.dat) • P82691Mass: 1011 Total score: 25 Peptides matched: 1 Pyrokinin-1 (Pea-PK-1) (FXPRL-amide) • P82041 Mass: 1736 Total score: 24 Peptides matched: 1 Uperin 3.4 1. 3. • P36396Mass: 2069 Total score: 23 Peptides matched: 1 Sex-determining region Y protein (Testis-determining factor) (Fragment)

  10. 4. FindMod • This tool examines peptide mass fingerprinting data for mass differences between empirical and theoretical peptides. Where mass differences correspond to a post-translational modification (PTM).

  11. Post-translational modifications Mass values used in FindMod • Modifications Abbreviation Monoisotopic Average __ • Acetylation ACET 42.0106 42.0373 • Amidation AMID -0.9840 -0.9847 • Beta-methylthiolation BMTH 45.9877118 46.08688 • Biotin BIOT 226.0776 226.2934 • Carbamylation CAM 43.00581 43.02502 • Citrullination CITR 0.9840276 0.98476 • C-Mannosylation CMAN 162.052823 162.1424 • Deamidation DEAM 0.9840 0.9847 • N-acyl diglyceride • cysteine (tripalmitate) DIAC 788.7258 789.3202 • Dimethylation DIMETH 28.0314 28.0538 • FAD FAD 783.1415 783.542 • Farnesylation FARN 204.1878 204.3556 • Formylation FORM 27.9949 28.0104 • Geranyl-geranyl GERA 272.2504 272.4741 • Gamma-carboxyglutamic acid GGLU 43.98983 44.0098 • O-GlcNAc GLCN 203.0794 203.1950 • Glucosylation (Glycation) GLUC 162.0528 162.1424 • Hydroxylation HYDR 15.9949 15.9994 • Lipoyl LIPY 188.033 188.3027 • Methylation METH 14.0157 14.0269 • Myristoylation MYRI 210.1984 210.3598 • Palmitoylation PALM 238.2297 238.4136 • Phosphorylation PHOS 79.9663 79.9799 • Pyridoxal phosphate PLP 229.014 229.129 • Phosphopantetheine PPAN 339.078 339.3234 • Pyrrolidone carboxylic acid PYRR -17.0266 -17.0306 • Sulfation SULF 79.9568 80.0642 • Trimethylation TRIMETH 42.0471 42.0807

  12. Biochemical Pathway Databases • Linking the biochemical pathways together and integration with the genomic data are the great tasks of biochemical pathway databases.

  13. Metabolomics:From Genes to Pathways:

  14. Where do we go? “Deconstruction of biological processes into their molecular components”.

  15. DNA (Genomics) RNA (Transcriptomics) Protein (Proteomics) Metabolites (Metabolomics)

  16. From: Gene, genome, cell, organism, population,… towardSystem Biology

  17. What are we going to do?

  18. Fact:Individual research units would not work any more! Recommendation: Team up! Go beyond your own, your institute, and your country boundaries.

  19. Fact:Genomic data are suppose to reduce time and efforts for preparation of reagents, resources and information. Recommendation: Think big! • Search and use data intelligently. • Turn attention to complex biology from various angles, i.e. have all needed specialty in your team.

  20. Fact:A mass of data is available freely! Recommendation: Learn how to use! Make use of them to develop technologies.

  21. Fact:Biology world is rapidly changing! Recommendation: Keep up with changes! • Re-establish systems with more flexibility and more freedom. • Loose regulations for funding, employment, etc. • Re-design your research project.

  22. Thanks for Your Attention

  23. Cautions: • One protein with different roles: • Alpha-enolase in liver • T-crystallin in eye lens • One structure in proteins with diverse functions: • TIM barrels in isomerases, oxidoreductase and hydrolases. • 30% error in automated annotations.

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