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

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Mass spectrometry in a drug discovery setting

Mass Spectrometry in a drug discovery setting

Claus Andersen

Senior Scientist

Sienabiotech Spa


Overview
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


From genes to phenotype
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


Proteins as functional units
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


What affects the proteome
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


Mass spec on proteins

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


Mass spec data

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


Mass spec data analysis
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


Large scale spectral comparison

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


Large scale spectral comparison1
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


Large scale spectral comparison2
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


Large scale spectral comparison3

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


Large scale spectral comparison4
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


Large scale spectral comparison5
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


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