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Medizinisches Proteom-Center (MPC) --- Decoy Database Advantages and Protein Balancing for understanding the complexity of life Dr. Christian Stephan Medizinisches Proteom-Center Ruhr-Universität Bochum Germany 02-07. Februar 2008. Proteomics.

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Medizinisches Proteom-Center (MPC)

---

Decoy Database Advantages and Protein Balancing for understanding the complexity of life

Dr. Christian Stephan

Medizinisches Proteom-Center

Ruhr-Universität Bochum

Germany

02-07. Februar 2008


Proteomics

Proteome: The set of proteins expressed by the genetic material of an organism under a given set of environmental conditions.

Proteomics can be defined as the qualitative and quantitative comparison of proteomes under different conditions to further unravel biological processes. Expasy.org

… and a valid interpretation of proteomics data


Composite decoy database
Composite Decoy Database

Definition: Decoy ≡ pitfall/trap

Composite ≡ hybrid/mixed

Goal is to determine stochastical/unspecific hits by using a trap for the search engines.

The stochastical/unspecific hits will be happen also to a shuffle generated amino acid composition.

>IPI:IPI00000001.1|SWISS-PROT:O95793-1|TREMBL:Q5JW29|REF

MSQVQVQVQNPSAALSGSQILNKNQSLLSQPLMSIPSTTSSLPSEN

>IPI:IPI00000005.1|SWISS-PROT:P01111|REFSEQ_NP:NP_002515

MTEYKLVVVGAGGVGKSALTIQLIQNHFVDEYDPTIEDSYRKQVVID

>IPI:IPI00000006.1|SWISS-PROT:P01112|TREMBL:Q9UCE2|REFS

MTEYKLVVVGAGGVGKSALTIQLIQNHFVDEYDPTIEDSYRKQVVID

>IPI:IPI00000012.4|TREMBL:Q6XR72;Q9NPW0|REFSEQ_NP:NP_0

MGRYSGKTCRLLFMLVLTVAFFVAELVSGYLGNSIALLSDSFNMFSD

>IPI:IPI00000001.1|SWISS-PROT:O95793-1|TREMBL:Q5JW29|REF

MSQVQVQVQNPSAALSGSQILNKNQSLLSQPLMSIPSTTSSLPSEN

>IPI:SHD00000001.1|SWISS-PROT:O95793-1|TREMBL:Q5JW29|RE

VQKTFSNTSPESKPVGEPEYSNTFESIALSAEGIEYTIHLSAQEPCTV

>IPI:IPI00000005.1|SWISS-PROT:P01111|REFSEQ_NP:NP_002515

MTEYKLVVVGAGGVGKSALTIQLIQNHFVDEYDPTIEDSYRKQVVID

>IPI:SHD00000005.1|SWISS-PROT:P01111|REFSEQ_NP:NP_002515

SCDVEYDTVPLYVKGFVGVQLGEEIVAYLEEMLDKQFQMTQMYKG




Advantages of decoy databases
Advantages of decoy databases

  • You can determine “true positives” (TP)

    TP is the number of correct hits with scores above threshold

  • You can determine “false positives” (FP)

    FP is the number of incorrect hits with scores above threshold

  • You can determine “false negatives” (FN)

    FN is the number of correct hits with scores below threshold

  • You can determine “true negatives” (TN)

    TN is the number incorrect hits with scores below threshold

  • False Discovery Rate





Several search engines why proteins
Several search engines, why?- Proteins -

SEQUEST

Mascot

750

689

101 (+8,0%)

132 (+10,4%)

ProteinSolver

693

Phenyx

56

31

29

669

194 (+15,3%)

113 (+8,9%)

38

118

295

52

25

27

28

31

1270 (+69,3%)


Several search engines why peptides
Several search engines, why?- Peptides -

SEQUEST

Mascot

3792

3229

212 (+4,2%)

486 (+9,6%)

ProteinSolver

3203

Phenyx

179

168

40

3186

329 (+6,5%)

380 (+7,5%)

348

501

1776

139

96

77

195

146

5072 (+33,8%)


Several search engines why peptides1

SEQUEST

Mascot

3792

3229

212 (+4,2%)

486 (+9,6%)

ProteinSolver

3203

Phenyx

179

168

40

3186

329 (+6,5%)

380 (+7,5%)

348

501

1776

139

96

77

195

146

ProteinExtractor

ProteinExtractor

Several search engines, why?- Peptides -

1068 Proteins

+42,4%

Normalize scores by a factor for each SE

5072 spectra

1325 Proteins

+76,6%

  • peptides

  • (+33,8%)


How many decoy peptides
How many decoy peptides?

  • 5% decoy proteins

    Sequest: 2,82%

    Mascot: 2,16%

    ProteinSolver: 2,15%

    Phenyx: 2,31%




Hupo test sample
HUPO Test Sample

  • 20 Human proteins

  • Expressed in E.coli BL21 Star™ (DE3)

  • purification


Hupo test sample1
HUPO Test Sample

on protein level

1st run

2nd run

28

30

23

65%

7

5

35

on peptide level

1st run

2nd run

388

417

291

57%

126

97

514



Result ii
Result II

decoy entries

target entry






Comparison of different transgenic cell lines
Comparison of different transgenic cell lines

Mao L, Zabel C, Herrmann M, Nolden T, Mertes F, Magnol L, Chabert C, Hartl D, Herault Y, Delabar JM, Manke T, Himmelbauer H, Klose J.

Proteomic shifts in embryonic stem cells with gene dose modifications suggest the presence of balancer proteins in protein regulatory networks.

PLoS ONE. 2007 Nov 28;2(11):e1218


Theorie of balancer and effector proteins i
Theorie of „Balancer“ and „Effector“ Proteins I

Balancer Proteins

protein amount

  • Deletion

  • Mutation

  • Expression change

  • Development

  • Aging

  • etc.


Theorie of balancer and effector proteins ii
Theorie of „Balancer“ and „Effector“ Proteins II

Effector Proteine

protein amount

  • Deletion

  • Mutation

  • Expression change

  • Development

  • Aging

  • etc.


Balancer und effector proteins a complex system
Balancer und Effector proteins a complex system

Mao et. al. 2007


Scheduled tasks
Scheduled tasks

  • Establish data collection center for quant. data

  • Collect quantitative data

    • Own data

    • Publications

    • Collaborations

    • Identify „balancer“ and „effector“ proteins

    • Identify „balancer“ and „effector“ attributes

    • Simulate both „balancing“ and „effects“ for identification of new “balancer” and “effector” proteins

    • Cross correlation with other Omics


Ministerium für

Wissenschaft und Forschung

des Landes

Nordrhein-Westfalen


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