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Modeling virus-host interaction networks

Modeling virus-host interaction networks . Perry Evans Mahdi Sarmadi. NEF interaction sites. Roeth and Collins MMBR ‘06 ‏. HIV-1 ELMs . Interaction prediction. Identify ELMs on HIV-1 proteins Find human proteins with functional CDs

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Modeling virus-host interaction networks

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  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 NIAID’s 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.{0,1}C..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 KR[KR] 96 94% 8.89E-10 1.53E-10 [IL]KQE VPR 20 50% 1.02E-07 7.46E-11

  13. H2 Set Motif Alignment

  14. [FWY].{0,1}C..C on TAT

  15. H2 Motifs: Counter Motif?

  16. H2 Motifs: Counter Motif? E.[FIV]..[IL].K

  17. HIV Invariant Region Motifs

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