A Data Integration Approach to Predict Host-Pathogen
Protein-Protein Interactions: Application to Recognize Protein Interactions
between Human and a Malarial Parasite
Abstract: Lack of large-scale efforts aimed at recognizing interactions
between host and pathogens limits our understanding of many diseases. We
present a simple and generally applicable bioinformatics approach for the
analysis of possible interactions between the proteins of a parasite,
Plasmodium falciparum, and human host. In the first step, the physically
compatible interactions between the parasite and human proteins are recognized
using homology detection. This dataset of putative in vitro interactions
is combined with large-scale datasets of expression and sub-cellular
localization. This integrated approach reduces drastically the number of false
positives and hence can be used for generating testable hypotheses. We could
recognize known interactions previously suggested in the literature. We also
propose new predictions which involve interactions of some of the parasite
proteins of yet unknown function. The method described is generally applicable
to any host-pathogen pair and can thus be of general value to studies of
host-pathogen protein-protein interactions.
Keywords: Host-pathogen interactions, protein-protein interactions, data integration method