IN SILICO ANALYSIS OF PROTEIN-PROTEIN INTERACTION NETWORK OF HUTCHINSON GILFORD PROGERIA SYNDROME

Life Science - Bioinformatics

Abstract

HGPS is a rare genetic disorder, caused by mutations in genes, encoding proteins of the nuclear lamina. Analysis of protein interaction network in the cell would be the key to understand how complex processes, lead to diseases. Protein-protein interaction network (PPIN) analysis provides the possibility to quantify the hub proteins in large networks as well as their interacting partners. A comprehensive genes/proteins dataset related to HGPS is created by analysing public proteomic data and text mining of scientific literature. From this dataset the associated PPI network is acquired to understand the relationships between topology and functionality of the PPI network. The extended network of seed proteins network consisted of 128 nodes connected via 376 edges (Fusion) and 127 nodes connected via 377 edges (Coexpression), targeted for analysis. The backbone network derived from giant network with high BC proteins presents a clear and visual overview which shows closely related proteins of HGPS and the crosstalk between them. Proteins with high BC and large degree have been identified as backbone network of disease. LMNA with highest BC and CC located in the centre of the network. Finally, the robustness of central proteins and accuracy of backbone are validated by 127 test networks. Based on the network topological parameters such as degree, closeness centrality, betweenness centrality we conclude that integrated PPIN is centred on LMNA. Although finding of other interacting partners are strongly represented as novel drug targets for HGPS.