Prediction of HIV-1 virus-host protein interactions using virus and host sequence motifs.
BACKGROUND
Host protein-protein interaction networks are altered by invading virus proteins, which create new interactions, and modify or destroy others. The resulting network topology favors excessive amounts of virus production in a stressed host cell network. Short linear peptide motifs common to both virus and host provide the basis for host network modification.


METHODS
We focused our host-pathogen study on the binding and competing interactions of HIV-1 and human proteins. We showed that peptide motifs conserved across 70% of HIV-1 subtype B and C samples occurred in similar positions on HIV-1 proteins, and we documented protein domains that interact with these conserved motifs. We predicted which human proteins may be targeted by HIV-1 by taking pairs of human proteins that may interact via a motif conserved in HIV-1 and the corresponding interacting protein domain.


RESULTS
Our predictions were enriched with host proteins known to interact with HIV-1 proteins ENV, NEF, and TAT (p-value < 4.26E-21). Cellular pathways statistically enriched for our predictions include the T cell receptor signaling, natural killer cell mediated cytotoxicity, cell cycle, and apoptosis pathways. Gene Ontology molecular function level 5 categories enriched with both predicted and confirmed HIV-1 targeted proteins included categories associated with phosphorylation events and adenyl ribonucleotide binding.


CONCLUSIONS
A list of host proteins highly enriched with those targeted by HIV-1 proteins can be obtained by searching for host protein motifs along virus protein sequences. The resulting set of host proteins predicted to be targeted by virus proteins will become more accurate with better annotations of motifs and domains. Nevertheless, our study validates the role of linear binding motifs shared by virus and host proteins as an important part of the crosstalk between virus and host.
Evans
Perry
P
Genomics and Computational Biology and Department of Computer and Information Science, University of Pennsylvania, Levine Hall, 3330 Walnut Street, Philadelphia, PA 19104, USA. evansjp@mail.med.upenn.edu
Dampier
William
W
Ungar
Lyle
L
Tozeren
Aydin
A