Viral Complexity: Amino acid co-evolution in viral genomes as a possible metric

Abstract

Viruses are simultaneously simple and complex. Simple because they have barely around ten types of proteins compared to tens of thousands of proteins in bacteria. Complex because amino acid mutation rates are very high, challenging host immune system and drugs. In this work we use the co-evolution of amino acids and the network characteristics that arise out of it to describe the complexity hidden in the multitude of variations in a viral genome. Using large-scale genomic data, the complexity in several viruses was compared. Interestingly, the co-evolutionary relations were primarily intra-protein in avian influenza and inter-protein in HIV-1. The network degree distributions showed two universality classes: a power-law with exponent -1 in HIV-1 and avian-influenza, random co-evolutionary behavior in human flu and dengue, suggesting the co-evolution as one way to statistically classify the complexity in viruses. The observed correlation between the network densities and the strengths on virus Richter scale raises interesting questions on whether it is possible to define the complexity of viruses using their evolutionary networks.