Deciphering biological evolution exploiting the topology of Protein Locality Graph

Abstract

The conventional sequence comparison-based evolutionary studies ignore other evolutionary constraints like interaction among proteins, functions of proteins and genes etc. A lot of speculations exist in literature regarding the presence of species divergence at the level of the Protein Interaction Networks. Additionally, it has been conjectured that the intra-module connections stay conserved whereas the inter-module connections change during evolution. The most important components of the biological networks are the functional modules which are more conserved among the evolutionary closer species. Here, we demonstrate an alternative method to decipher biological evolution by exploiting the topology of a spatially localized Protein Interaction Network called Protein Locality Graph (PLG). Our lossless graph compression from PLG to a power graph called Protein Cluster Interaction Network (PCIN) results in a 90% size reduction and aids in improving computational time. Further, we exploit the topology of PCIN and demonstrate our capability of deriving the correct species tree by focusing on the cross-talk between the protein modules exclusively. Our results provide new evidence that traces of evolution are not only present at the level of the Protein-Protein Interactions, but are also very much present at the level of the inter-module interactions.