Prioritising candidate genes for further experimental characterisation is a
non-trivial challenge in drug discovery and biomedical research in general. An
integrated approach that combines results from multiple data types is best
suited for optimal target selection. We developed TargetMine, a data warehouse
for efficient target prioritisation. TargetMine utilises the InterMine
framework, with new data models such as protein-DNA interactions integrated in a
novel way. It enables complicated searches that are difficult to perform with
existing tools and it also offers integration of custom annotations and in-house
experimental data. We proposed an objective protocol for target prioritisation
using TargetMine and set up a benchmarking procedure to evaluate its
performance. The results show that the protocol can identify known
disease-associated genes with high precision and coverage. A demonstration
version of TargetMine is available at http://targetmine.nibio.go.jp/.
Background: Serine proteases are one of the largest groups of proteolytic enzymes found across all kingdoms of life and are associated with several essential physiological pathways. The availability of Arabidopsis thaliana and rice (Oryza sativa) genome sequences has permitted the identification and comparison of the repertoire of serine protease-like proteins in the two plant species.
Hepatitis C virus (HCV) is a major cause of chronic liver disease worldwide. Here we attempt to further our understanding of the biological context of protein interactions in HCV pathogenesis, by investigating interactions between HCV proteins Core and NS4B and human host proteins. Using the yeast two-hybrid (Y2H) membrane protein system, eleven human host proteins interacting with Core and 45 interacting with NS4B were identified, most of which are novel. These interactions were used to infer overall protein interaction maps linking the viral proteins with components of the host cellular networks. Core and NS4B proteins contribute to highly compact interaction networks that may enable the virus to respond rapidly to host physiological responses to HCV infection. Analysis of the interaction networks highlighted enriched biological pathways likely influenced in HCV infection. Inspection of individual interactions offered further insights into the possible mechanisms that permit HCV to evade the host immune response and appropriate host metabolic machinery. Follow-up cellular assays with cell lines infected with HCV genotype 1b and 2a strains validated Core interacting proteins ENO1 and SLC25A5 and host protein PXN as novel regulators of HCV replication and viral production. ENO1 siRNA knockdown was found to inhibit HCV replication in both the HCV genotypes and viral RNA release in genotype 2a. PXN siRNA inhibition was observed to inhibit replication specifically in genotype 1b but not in genotype 2a, while SLC25A5 siRNA facilitated a minor increase in the viral RNA release in genotype 2a. Thus, our analysis can provide potential targets for more effective anti-HCV therapeutic intervention.
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