title: Mean protein evolutionary distance: a method for comparative protein evolution and its application.
abstract: Proteins are under tight evolutionary constraints, so if a protein changes it can only do so in ways that do not compromise its function. In addition, the proteins in an organism evolve at different rates. Leveraging the history of patristic distance methods, a new method for analysing comparative protein evolution, called Mean Protein Evolutionary Distance (MeaPED), measures differential resistance to evolutionary pressure across viral proteomes and is thereby able to point to the proteins' roles. Different species' proteomes can also be compared because the results, consistent across virus subtypes, concisely reflect the very different lifestyles of the viruses. The MeaPED method is here applied to influenza A virus, hepatitis C virus, human immunodeficiency virus (HIV), dengue virus, rotavirus A, polyomavirus BK and measles, which span the positive and negative single-stranded, doubled-stranded and reverse transcribing RNA viruses, and double-stranded DNA viruses. From this analysis, host interaction proteins including hemagglutinin (influenza), and viroporins agnoprotein (polyomavirus), p7 (hepatitis C) and VPU (HIV) emerge as evolutionary hot-spots. By contrast, RNA-directed RNA polymerase proteins including L (measles), PB1/PB2 (influenza) and VP1 (rotavirus), and internal serine proteases such as NS3 (dengue and hepatitis C virus) emerge as evolutionary cold-spots. The hot spot influenza hemagglutinin protein is contrasted with the related cold spot H protein from measles. It is proposed that evolutionary cold-spot proteins can become significant targets for second-line anti-viral therapeutics, in cases where front-line vaccines are not available or have become ineffective due to mutations in the hot-spot, generally more antigenically exposed proteins. The MeaPED package is available from www.pam1.bcs.uwa.edu.au/~michaelw/ftp/src/meaped.tar.gz.
authors.affiliation: School of Chemistry and Biochemistry, University of Western Australia, Crawley, Western Australia, Australia. Michael.Wise@uwa.edu.au
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Wise
mesh_terms: D000465:Algorithms; D000818:Animals; D019295:Computational Biology / Q000379:methods*; D019143:Evolution, Molecular; D006801:Humans; D010802:Phylogeny; D040901:Proteomics; D013045:Species Specificity; D014764:Viral Proteins / Q000378:metabolism*; D014780:Viruses / Q000235:genetics / Q000378:metabolism
chemical_list: D014764:Viral Proteins