Mutations and Variations in Health and Disease: Protein Interaction Networks and 3D Structure Information Event

Abstract: In the last years Systems Biology has provided frameworks to integrate high-throughput biological and clinical data, providing significant insights into some of the fundamental roles of genes and proteins in maintaining a functional cellular state. However, it is still challenging to employ quantitative methods to identify important disease-related relationships between proteins harbouring mutations in their structural domains. We recently developed a method called "short-loop network motif profiling" to understand functionality embedded in protein-protein interaction networks (PPIN). The method can be used to design targeted experiments to detect functional phenotypes of proteins in short loops.

We show that a) short loop network motifs associating proteins with common variants are significantly fewer than loops containing pathogenic variants. b) By generating disease-specific networks like genes involved in different Leukemia sub-types, identify pairs of homologous short loops; for example, kinases (FLT3 and KIT) harbouring pathogenic mutations found in patients with Acute Myeloid Leukemia and localised in identical positions in the 3D-structure. c) We observe clear differences in the distribution of mutation types in different 3D-structure regions, with complementary patterns distinguishing between pathogenic and common variants, suggesting that these properties can be used as input for predictions tools. More generally, we show that 3D PPIN analysis can also help biologists to effectively search for possible targets for disease treatment.