Investigation of infection mechanisms through pathogen-human protein-protein interactions by bioinformatics approaches - Tekir, Saliha Durmuş. (Thesis (Ph.D.) - Bogazici University. Institute for Graduate Studies in Social Sciences, 2013., 2013)
Since ancient times, even in today's modern world, infectious diseases cause lots of people to die. The interactions between the proteins of infectious microorganisms, pathogens and their human hosts allow the microorganisms to manipulate human cellular mechanisms to their own advantage, resulting in infection in the host organism. Improved understanding of pathogen-host molecular interactions will increase our knowledge of the mechanisms involved in infection, and allow novel therapeutic solutions to be devised. In the post-genomic era, following the advances in genomics, proteomics, and then interactomics, interspecies protein interaction data of pathogen-human systems can be produced in large-scale within very recent years. In this thesis, pathogen-host interaction search tool (PHISTO) has been developed as a Web-accessible platform providing relevant information about pathogen-host interactions (PHIs). It enables access to the most up-to-date PHI data for all pathogen types for which experimentally-verified protein interactions with human are available. The platform also offers integrated tools for visualization of PHI networks, graph theoretical analysis of human proteins targeted by pathogens and BLAST search. PHISTO aims to facilitate PHI studies that provide potential therapeutic targets for infectious diseases. Comparative interactomics analyses were performed to investigate infection mechanisms of bacteria versus viruses and then DNA viruses versus RNA viruses, using PHI data from PHISTO, constituting the first comprehensive attempts to get such comparisons. Crucial insights on common and special infection strategies used by these pathogen types were provided by bioinformatics analyses of PHI networks, focusing on the properties of the targeted human proteins.
Keywords: Bioinformatics.; Proteomics.