Paurush Praveen, Erfan Younesi and Martin Hofmann-Apitius
Modeling inter-species molecular cross-talks in three host- parasite, systems by expansion of their sparse information space

TL;DR
This study models cross-species protein interactions in parasitic diseases to uncover shared mechanisms and identify new drug targets, combining databases, text mining, and predictive methods.
Contribution
It introduces an integrated approach to expand protein interaction networks in parasitic diseases, revealing new pathways and potential drug targets.
Findings
Shared molecular mechanisms in host invasion and immune modulation
Identification of new potential drug targets for malaria and sleeping sickness
Expanded protein interaction maps with novel pathways
Abstract
The emergence of cross species interactions at protein level is a part of molecular mechanisms that lead to parasitic diseases. Comprehensive modelling can capture such interactions and could be useful to understand their pathophysiology and assist in identifying novel drug targets. Using combination of databases, text minig and predictive methods, we expanded the sparse information space of protein-protein interactions in three parasitic diseases namely, malaria, sleeping sickness and cattle east coast fever. These network models revealed significant similarities in molecular mechanisms underlaying host's invasion, immuno-modulation and energy metabolism. The models also suggested new possible pathways in the inter-species protein interaction maps. Enrichment of these maps with drug-target informations showed a plethora of drug space to be explored and led to proposal of two new…
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Taxonomy
TopicsMachine Learning in Bioinformatics · Computational Drug Discovery Methods · Genetics, Bioinformatics, and Biomedical Research
