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Modeling virus-host interaction networks

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Modeling virus-host interaction networks Perry Evans Mahdi Sarmadi NEF interaction sites Roeth and Collins MMBR 06 HIV-1 ELMs Interaction prediction Identify ... – PowerPoint PPT presentation

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Title: Modeling virus-host interaction networks


1
Modeling virus-host interaction networks
  • Perry Evans
  • Mahdi Sarmadi

2
NEF interaction sites
Roeth and Collins MMBR 06?
3
HIV-1 ELMs
4
Interaction prediction
  • Identify ELMs on HIV-1 proteins
  • Find human proteins with functional CDs
  • Validate predictions using NIAIDs HIV, human
    interaction database of 2K experimental
    interactions

H1
H2
5
Global validation
6
HIV-1 vs. HCV ELMs
4 interesting unique ELMs
7 interesting unique ELMs
7
MAPK study
  •  

8
Hub modularity predicts interactions
  •  

9
De Novo Motif Discovery
  • Known motifs do not unveil the grammar of
    interaction between HIV-1 and human proteins
  • Computational motif discovery of de novo motifs
    is based on the virtue of Over-Representation

10
Over Representation
11
HIV-1 Protein Alignment Contains Invariant Regions
HIV-1 TAT protein (first 65 AA of the sequence is
shown)
12
H2 Motif Finding Results
Motif Pattern
HIV
H1 Protein
H2 Proteins
H2 Matches
Occ. On HIV
HPRD P-Val
NCBI P-Val
FWY.0,1C..C
TAT
EP300 (E1A binding protein p300)
207
41
100
1.45E-04
1.04E-05
GTF2H1 (General Transcription factor IIH)
26
5
5.25E-02
3.15E-02
TBP (TATA box binding protein)
83
15
1.76E-02
5.94E-03
TP53 (Tumor protein p53)
238
42
8.10E-04
6.61E-05
TP73 (Tumor protein p73 )
31
8
4.19E-03
1.83E-03
CREBBP (CREB binding protein)
199
32
1.94E-02
3.69E-03
KRKR
96
94
8.89E-10
1.53E-10
ILKQE
VPR
20
50
1.02E-07
7.46E-11
13
H2 Set Motif Alignment
14
FWY.0,1C..C on TAT
15
(No Transcript)
16
H2 Motifs Counter Motif?
17
H2 Motifs Counter Motif?
E.FIV..IL.K
18
HIV Invariant Region Motifs
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