PHISTO: pathogen-host interaction search tool.

SUMMARY: Knowledge of pathogen-host protein interactions is required to better understand infection mechanisms. The pathogen-host interaction search tool (PHISTO) is a web-accessible platform that provides 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 targeted human proteins, BLAST search and text mining for detecting missing experimental methods. PHISTO will facilitate PHI studies that provide potential therapeutic targets for infectious diseases. AVAILABILITY: http://www.phisto.org. CONTACT: saliha.durmus@boun.edu.tr SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Reconstruction of protein-protein interaction network of insulin signaling in Homo sapiens.

Diabetes is one of the most prevalent diseases in the world. Type 1 diabetes is characterized by the failure of synthesizing and secreting of insulin because of destroyed pancreatic ß-cells. Type 2 diabetes, on the other hand, is described by the decreased synthesis and secretion of insulin because of the defect in pancreatic ß-cells as well as by the failure of responding to insulin because of malfunctioning of insulin signaling. In order to understand the signaling mechanisms of responding to insulin, it is necessary to identify all components in the insulin signaling network. Here, an interaction network consisting of proteins that have statistically high probability of being biologically related to insulin signaling in Homo sapiens was reconstructed by integrating Gene Ontology (GO) annotations and interactome data. Furthermore, within this reconstructed network, interacting proteins which mediate the signal from insulin hormone to glucose transportation were identified using linear paths. The identification of key components functioning in insulin action on glucose metabolism is crucial for the efforts of preventing and treating type 2 diabetes mellitus.

Drug targets for tumorigenesis: insights from structural analysis of EGFR signaling network.

Deciphering the complex network structure is crucial in drug target identification. This study presents a framework incorporating graph theoretic and network decomposition methods to analyze system-level properties of the comprehensive map of the epidermal growth factor receptor (EGFR) signaling, which is a good candidate model system to study the general mechanisms of signal transduction. The graph theoretic analysis of the EGFR network indicates that it has small-world characteristics with scale-free topology. The employment of network decomposition analysis enlightened the system-level properties, such as network cross-talk, specific molecules in each pathway and participation of molecules in the network. Participating in a significant fraction of the fundamental paths connecting the ligands to the phenotypes, cofactor GTP and complex Gbeta/Ggamma were identified as "housekeeping" molecules, through which all pathways of EGFR network are cross-talking. c-Src-Shc complex is identified as important due to its role in all fundamental paths through tumorigenesis and being specific to this phenotype. Inhibitors of this complex may be good anti-cancer agents having very little or no effect on other phenotypes.

Analysis of enzymopathies in the human red blood cells by constraint-based stoichiometric modeling approaches.

The human red blood cell (RBC) metabolism is investigated by calculating steady state fluxes using constraint-based stoichiometric modeling approaches. For the normal RBC metabolism, flux balance analysis (FBA) is performed via optimization of various alternative objective functions, and the maximization of production of ATP and NADPH is found to be the primary objective of the RBC metabolism. FBA and two novel approaches, minimization of metabolic adjustment (MOMA) and regulatory on-off minimization (ROOM), which can describe the behavior of the metabolic networks in case of enzymopathies, are applied to observe the relative changes in the flux distribution of the deficient network. The deficiencies in several enzymes in RBC metabolism are investigated and the flux distributions are compared with the non-deficient FBA distribution to elucidate the metabolic changes in response to enzymopathies. It is found that the metabolism is mostly affected by the glucose-6-phosphate dehydrogenase (G6PDH) and phosphoglycerate kinase (PGK) enzymopathies, whereas the effects of the deficiency in DPGM on the metabolism are negligible. These stoichiometric modeling results are found to be in accordance with the experimental findings in the literature related to metabolic behavior of the human red blood cells, showing that human RBC metabolism can be modeled stoichiometrically.

Systems biology of pathogen-host interaction: networks of protein-protein interaction within pathogens and pathogen-human interactions in the post-genomic era.

Infectious diseases comprise some of the leading causes of death and disability worldwide. Interactions between pathogen and host proteins underlie the process of infection. 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. Complete genome sequences for a number of pathogenic microorganisms, as well as the human host, has led to the revelation of their protein-protein interaction (PPI) networks. In this post-genomic era, pathogen-host interactions (PHIs) operating during infection can also be mapped. Detailed systematic analyses of PPI and PHI data together are required for a complete understanding of pathogenesis of infections. Here we review the striking results recently obtained during the construction and investigation of these networks. Emphasis is placed on studies producing large-scale interaction data by high-throughput experimental techniques.

Infection Strategies of Bacterial and Viral Pathogens through Pathogen-Human Protein-Protein Interactions.

Since ancient times, even in today's modern world, infectious diseases cause lots of people to die. Infectious organisms, pathogens, cause diseases by physical interactions with human proteins. A thorough analysis of these interspecies interactions is required to provide insights about infection strategies of pathogens. Here we analyzed the most comprehensive available pathogen-human protein interaction data including 23,435 interactions, targeting 5,210 human proteins. The data were obtained from the newly developed pathogen-host interaction search tool, PHISTO. This is the first comprehensive attempt to get a comparison between bacterial and viral infections. We investigated human proteins that are targeted by bacteria and viruses to provide an overview of common and special infection strategies used by these pathogen types. We observed that in the human protein interaction network the proteins targeted by pathogens have higher connectivity and betweenness centrality values than those proteins not interacting with pathogens. The preference of interacting with hub and bottleneck proteins is found to be a common infection strategy of all types of pathogens to manipulate essential mechanisms in human. Compared to bacteria, viruses tend to interact with human proteins of much higher connectivity and centrality values in the human network. Gene Ontology enrichment analysis of the human proteins targeted by pathogens indicates crucial clues about the infection mechanisms of bacteria and viruses. As the main infection strategy, bacteria interact with human proteins that function in immune response to disrupt human defense mechanisms. Indispensable viral strategy, on the other hand, is the manipulation of human cellular processes in order to use that transcriptional machinery for their own genetic material transcription. A novel observation about pathogen-human systems is that the human proteins targeted by both pathogens are enriched in the regulation of metabolic processes.