Title: Modeling virus-host interaction networks
1Modeling virus-host interaction networks
- Perry Evans
- Mahdi Sarmadi
2NEF interaction sites
Roeth and Collins MMBR 06?
3HIV-1 ELMs
4Interaction 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
5Global validation
6HIV-1 vs. HCV ELMs
4 interesting unique ELMs
7 interesting unique ELMs
7MAPK study
8Hub modularity predicts interactions
9De 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
10Over Representation
11HIV-1 Protein Alignment Contains Invariant Regions
HIV-1 TAT protein (first 65 AA of the sequence is
shown)
12H2 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
13H2 Set Motif Alignment
14FWY.0,1C..C on TAT
15(No Transcript)
16H2 Motifs Counter Motif?
17H2 Motifs Counter Motif?
E.FIV..IL.K
18HIV Invariant Region Motifs