title: A phylogenetic mixture model for the identification of functionally divergent protein residues.
abstract: BACKGROUND
  To understand the evolution of molecular function within protein families, it is important to identify those amino acid residues responsible for functional divergence; i.e. those sites in a protein family that affect cofactor, protein or substrate binding preferences; affinity; catalysis; flexibility; or folding. Type I functional divergence (FD) results from changes in conservation (evolutionary rate) at a site between protein subfamilies, whereas type II FD occurs when there has been a shift in preferences for different amino acid chemical properties. A variety of methods have been developed for identifying both site types in protein subfamilies, both from phylogenetic and information-theoretic angles. However, evaluation of the performance of these methods has typically relied upon a handful of reasonably well-characterized biological datasets or analyses of a single biological example. While experimental validation of many truly functionally divergent sites (true positives) can be relatively straightforward, determining that particular sites do not contribute to functional divergence (i.e. false positives and true negatives) is much more difficult, resulting in noisy 'gold standard' examples.
  
  
  RESULTS
  We describe a novel, phylogeny-based functional divergence classifier, FunDi. Unlike previous approaches, FunDi uses a unified mixture model-based approach to detect type I and type II FD. To assess FunDi's overall classification performance relative to other methods, we introduce two methods for simulating functionally divergent datasets. We find that the FunDi method performs better than several other predictors over a wide variety of simulation conditions.
  
  
  BACKGROUND
  http://rogerlab.biochem.dal.ca/Software
  
  
  BACKGROUND
  andrew.roger@dal.ca
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Centre for Comparative Genomics and Evolutionary Bioinformatics, Dalhousie University, Halifax, Canada, B3H 1X5.
authors.forename: Daniel
authors.initials: D
authors.lastname: Gaston
authors.forename: Edward
authors.initials: E
authors.lastname: Susko
authors.forename: Andrew J
authors.initials: AJ
authors.lastname: Roger
mesh_terms: D000596:Amino Acids / Q000235:genetics*; D019143:Evolution, Molecular; D008957:Models, Genetic; D010802:Phylogeny; D011485:Protein Binding / Q000235:genetics*; D011506:Proteins / Q000737:chemistry / Q000235:genetics* / Q000378:metabolism
chemical_list: D000596:Amino Acids; D011506:Proteins