Mass Spectrometry in a drug discovery setting

1. Mass Spectrometry in a drug discovery setting Claus Andersen Senior Scientist Sienabiotech Spa

2. Overview • From genes to phenotype • Proteins an introduction • Mass Spec for protein • Mass Spec data • Mass Spec data analysis • Mass Spec database searching • Recent advances identification quantification characterization Bioinformatics and statistics in a drug discovery company

3. From genes to phenotype Genome comparison genes Regulation mRNA expression mRNA expression Degradation Structure proteins Activation/inactivation Activation/inactivation functions Interactions Kinematics metabolites Protein abundance Protein abundance pathways Metabolite levels Pharmacophore phenotypes ADME/Tox Bioinformatics and statistics in a drug discovery company

4. Proteins as functional units ATP Glucose Myosin ATP Vrrooom Bioinformatics and statistics in a drug discovery company Vale and Milligan Science 2000 D.S. Goodsell pdb.org

5. What affects the proteome Interactions Physiological role Temperature Cellular proteome Pharmaceutical substances Stress Proteasome protein degradation Ribosome protein production Environment mRNA Genome Bioinformatics and statistics in a drug discovery company

6. KKYAAELHLV KAVQQPDGLA QFHFHWGSLDQPDGLA Mass Spec on proteins Protein extraction and digestion Peptides HPLC Mass Spectrometer Control/Healthy Treated/Sick Protein peptides identification MS spectra and MS/MS spectra quantification Phosphorylation P Oxidation characterization O … post translational modifications (PTM) Bioinformatics and statistics in a drug discovery company

7. Gygi et al. Mol. Cell Bio. (1999) Mass Spec data 5 mg 3000 MS spectra 500 MB 400 MS/MS spectra 200 MB Total 700 MB Bioinformatics and statistics in a drug discovery company

8. Mass Spec data analysis • Fourier transformation (noise filtering) • Gaussian peak fitting (peak detection) • Generation of theoretical spectra (sequencespectra) • Large scale spectral comparison (DB searching) • Spectral deconvolution (de-novo sequencing) • Large scale sequence searching (DB searching) • Data fitting (quantitation) • Statistics and probability theory (reliability estimation) • Linear discriminant analysis (quality assessment) • …. and lots more Large scale spectral comparison (DB searching) Bioinformatics and statistics in a drug discovery company

9. ERPIIFLSMCYNIYSIAYIV ERPIIFLSMCYNIYSIAYI ERPIIFLSMCYNIYSIAY ERPIIFLSMCYNIYSIA ERPIIFLSMCYNIYSI ERPIIFLSMCYNIYS ERPIIFLSMCYNIY ERPIIFLSMCYNI ERPIIFLSMCYN ERPIIFLSMCY ERPIIFLSMC ERPIIFLSM … Large scale spectral comparison Mass spec data In-silico data Protein sequence DB ~2 mil MS spectrum (Mpeptide+H)+ ±Δ FLIDSSRFSYPERPIIFLSMCYNIYSIAYIVRLTVGRERISCDFEEAAEPVLIQEGLKNT Protein peptides ~60 mil MS/MS Spectrum i ERPIIFLSMCYNIYSIAYIV Peptide fragments ~2000 mil V IV YIV AYIV IAYIV SIAYIV YSIAYIV IYSIAYIV NIYSIAYIV … { Ni Ki etc. etc… Bioinformatics and statistics in a drug discovery company

10. Large scale spectral comparison PEP_PROBE by Sadygov and Yates Anal. Chem. 75 2003 Hypergeometric probability model where is the binomial coefficient Bioinformatics and statistics in a drug discovery company

11. Large scale spectral comparison Expectation value (E-value) where is the cumulative distribution function given by the hypergeometric model, is the number of all peptides in the database matching the (M+H)+ mass value. The E-value tells you how many peptides from the database are expected to have the same or better matches to the experimental spectrum by chance alone. Sadygov and Yates Anal. Chem. 2003 Bioinformatics and statistics in a drug discovery company

12. Top candidate peptides Protein name N1 K1 E-value Peptide FAS1 40 34 10-26.62 ATHILDFGPGGASGLGVLTHR SIP2 10-5.25 34 15 LTPPQLPPQLENVILNKY Large scale spectral comparison An example from yeast (Saccharomyces cerevisiae) MS/MS spectrum Yeast proteins 6200 (M+H)+ = 2076.010 ± 0.002 AMU Yeast peptides ~200000 ~5 mil Peptide fragments N=569160 K= 84150 Sadygov and Yates Anal. Chem. 2003 Bioinformatics and statistics in a drug discovery company

13. Large scale spectral comparison The protein FAS1 is part of the fatty acid biosynthesis of yeast. Its enzyme classification number is (EC 2.3.1.86) In general several peptides are found for each protein (3-10) Protein identification FAS1 www.kegg.org Bioinformatics and statistics in a drug discovery company

14. Large scale spectral comparison Other approaches • An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database. Yates’ group J.Am.Soc.Mass Spec. 5(11) 1994 • ProbID: a probabilistic algorithm to identify peptides through sequence database searching using tandem mass spectral data. Aebersold’s group Proteomics 2(10) 2002 Most recent advances • Inverted sequence DB used for background distribution estimation (PRISM) Emili’s group Mol. Cell Proteomics, 2(2), p96-106, 2003 • Number of Sibling peptides (ProteinProphet)Aebersold’s group Anal. Chem. 74, p5383-5392, 2004 • Suffix tree searching: Lu and Chen Bioinformatics 19(2), pii113-ii121, 2003 • Bayesian approach:Chen Biosilico in press 2004 Bioinformatics and statistics in a drug discovery company