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“Proteomics & Bioinformatics”

“Proteomics & Bioinformatics”. MBI, Master's Degree Program in Helsinki, Finland. Lecture 3. 9 May, 2007. Sophia Kossida , BRF, Academy of Athens, Greece Esa Pit känen , Univeristy of Helsinki, Finland Juho Rouso , University of Helsinki, Finland. Protein Identification with MS/MS.

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“Proteomics & Bioinformatics”

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  1. “Proteomics & Bioinformatics” MBI, Master's Degree Program in Helsinki, Finland Lecture 3 9 May, 2007 Sophia Kossida, BRF, Academy of Athens, Greece Esa Pitkänen, Univeristy of Helsinki, Finland Juho Rouso, University of Helsinki, Finland

  2. Protein Identification with MS/MS Proteins The selected “parent” ion is fragmented. Peptides The peptides are ionized and separated according to their m/z ratio. One ion of interest is selected. A mass spectrum of parent ion’s fragments is acquired. Database search.Sequest, Mascot Protein identification Theoretical

  3. Fragmentation of peptides The peptide is a linear chain of amino acids N-terminus C-terminus Ionisation and fragmentation Modified from:N. Edwards, University of Maryland, College Park

  4. Fragmentation of peptides The most commonly observed cleavage is of the bond between the carbonyl oxygen and the amide nitrogen. This is cleaved to form “y-ion” and the “b-ion”. y-ion the positive charge is retained on the C-terminus of the original peptide ion. b-ion is the fragment in which the charge is remained on the N-terminal

  5. b- and y-ions When single charged ions fragment, either b- or y-ion is formed. The other half of the peptide is lost as a neutral fragment. Doubly charged ions are most likely to have charges at he opposite ends of the molecule, both b- and y- ions are formed (twice as much information)

  6. More about fragmentation c a • Amino terminal fragments: a, b, c • Carboxy terminal fragments: x, y, z • Various side chain reactions: • the fragments can also fragment, especially if have a mobile H+ • b-ions fragment to a-ions z x

  7. Fragment spectrum The sequence 1166 1080 1022 875 762 633 504 389 260 147 y-ions S G F L E E D E L K 88 145 292 405 534 663 778 907 1020 1166 b-ions Will show a spectrum like this Modified from:N. Edwards, University of Maryland, College Park

  8. Fragmentation of sequence Modified from:N. Edwards, University of Maryland, College Park

  9. Trypsin digest MS/MS MS Peptide identification De novointerpretation Sequence database search The mass of the parent ion*, and the MS/MS spectrum The amino-acid sequence of the peptide

  10. De Novo spectrum 1166 1080 1022 875 762 633 504 389 260 147 y-ions S G F L E E D E L K Distance between y5 and y4 is 129 amu, corresponding to the residue of Glutamic acid (E), the gap between y9 and y8 is 58, corresponding to Glycine (G)

  11. De Novo sequencing Identify the b- and y-ions in the spectrum Experimental MS spectrum Find valid peak pairs Search for alignement Examine all combinations of MS spectrum peak intervals, and the protein fragments the intervals may represent, and construct a most likely sequence. http://gridweb.cti.depaul.edu/twiki/pub/Main/GilKwak/HypotheticalSeqAnalyzer.pdf

  12. Advantage/Disadvantage (de novo) Gets the sequences that are not necessarily in the database Requires high quality data The best de novo interpretation may have no biological relevance Not well suited for high throughput workflow Difficulty in detecting post-translational modifications and wild-type mutants Incomplete ladders create ambiguity Modified from: http://gridweb.cti.depaul.edu/twiki/pub/Main/GilKwak/HypotheticalSeqAnalyzer.pdf

  13. De Novo Software http://www.hairyfatguy.com/lutefisk/ http://www.bioinfor.com:8080/peaksonline/

  14. Sequence Database Search AVAGCAGARCVAAGAAGRVGGACAAAR.. Experimental fragmentation spectrum Select peptides that equal the input mass, from database, - get a sequences that match. Theoretical spectra Precursor mass, charge state [M+H]=775,8 Theoretically fragment peptides, -generate virtual MS-MS spectra Compute correlation scores Rank hits Peptide/protein validation Compare virtual spectra to real spectrum

  15. Amino acids

  16. Sequence Database Search Modified from:Jimmy Eng, MS/MS Database Searching http://tools.proteomecenter.org/course/lectures/0610Day1.Eng.pdf

  17. Advantages / Disadvantages No need for complete ladders All candidates have some biological relevance Proteins with lots of identified peptides are not more likely to be present Practical for high throughput peptide identification Incomplete databases Poor quality of fragmentation

  18. Software tools for MS/MS identification The outcome of these programs depends on the quality of the MS-MS data obtained and the completeness and accuracy of the database used. Sequest Mascot(Matrix Science) OMSSA(NCBI) X!Hunter(Global Protein Machine Organization)

  19. Sequest Commercially available,distributed by Finnigan Corp. Developed by Jimmy Eng and John Yates Correlates uninterpreted tandem mass spectra of peptides with amino acid sequences from protein and nucleotide databases. Determine the amino acid sequence and thus the protein (s) and organism (s) that correspond to the mass spectrum being analyzed. http://fields.scripps.edu/sequest/

  20. Monoiotopic vs. average mass Modified from:Jimmy Eng, MS/MS Database Searching http://tools.proteomecenter.org/course/lectures/0610-Day1.Eng.pdf

  21. Missed cleavage site

  22. Parameters of MS/MS id search Modifications Cystein almost always modified Variable modifications increase search time exponentially Basic residues (K, R) at C-terminal attract ionizing charge, leading to strong y-ions Digestion Enzyme Trypsin (specific) Non-tryptic search increase time by two orders of magnitude Large sequence databases contain many irrelevant peptide candidates http://www.matrixscience.com/

  23. Mascot ms/ms ion search

  24. MS/MS ion search result It is the ions scores for individual peptide matches that are statistically significant

  25. Peptide summary The proteins are listed, by descending score, each with a table summarising the matched peptides Protein view Experimental m/z value Calculated rel mass (relative molecular mass) Expectation value for the peptide match, (the number of times we would expect to obtain an equal or higher score, purely by chance. The lower this value, the more significant the result.)

  26. Difference between the experimental and calculated masses. Hit: Plus sign indicates that multiple proteins contain a match to this peptide Ions score Peptide view

  27. Peptide fragmentation of APGFGDNR Matches (Bold Red): 9/58 fragment ions using 18 most intense peaks

  28. OMSSA http://pubchem.ncbi.nlm.nih.gov/omssa/

  29. GPM X (The Global Proteome Machine Organization), http://www.thegpm.org

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