Intrinsic structural disorder on proteins is involved in the interactome evolution

Abstract

New mathematical tools help understand cell functions, adaptability, and evolvability to discover hidden variables to predict phenotypes that could be tested in the future in wet labs. Different models have been successfully used to discover the properties of the protein-protein interaction networks or interactomes. I found that in the hyperbolic Popularity-Similarity model, cellular proteins with the highest contents of structural intrinsic disorder cluster together in many different eukaryotic interactomes and this is not the case for the prokaryotic E. coli, where proteins with high degree of intrinsic disorder are scarce. I also found that the normalized theta variable from the Popularity-Similarity model for orthologues proteins correlate to the complexity of the organisms in analysis.