Structural similarity-based predictions of protein interactions between HIV-1 and Homo sapiens

We developed and applied a computational approach to predict interactions between HIV and human proteins based on structural similarity of 9 HIV-1 proteins to human proteins having known interactions. Using functional data from RNAi studies as a filter, we generated over 2000 interaction predictions between HIV proteins and 406 unique human proteins. Additional filtering based on Gene Ontology cellular component annotation reduced the number of predictions to 502 interactions involving 137 human proteins. We find numerous known interactions as well as novel interactions showing significant functional relevance based on supporting Gene Ontology and literature evidence.Understanding the interplay between HIV-1 and its human host will help in understanding the viral lifecycle and the ways in which this virus is able to manipulate its host. The results shown here provide a potential set of interactions that are amenable to further experimental manipulation as well as potential targets for therapeutic intervention.Pathogen invasion and survival requires that the pathogen interact with and manipulate its host. Human immunodefficiency virus type 1 (HIV-1) encodes only 15 proteins and must therefore rely on the host cell's machinery to accomplish vital tasks such as the transport of viral components through the cell and the transcription of viral genes [1,2]. HIV-1 infects human cells by binding to CD4 and a coreceptor, fusing with the cell membrane and uncoating the virion core in the cytoplasm [2]. The genomic RNA is then reverse transcribed and the DNA enters the nucleus as part of a viral pre-integration complex (PIC) containing both viral and host proteins. Afterwards, the viral DNA is inserted into the genome by viral integrase (IN) [1]. The integrated provirus is transcribed by host RNA polymerase II from a promoter located in the provirus long terminal repeat (LTR), and the RNA is exported to the cytoplasm [1,2]. Host machinery translates HIV-1 mRNA, and several of