title: Accounting for epistatic interactions improves the functional analysis of protein structures.
abstract: BACKGROUND
  The constraints under which sequence, structure and function coevolve are not fully understood. Bringing this mutual relationship to light can reveal the molecular basis of binding, catalysis and allostery, thereby identifying function and rationally guiding protein redesign. Underlying these relationships are the epistatic interactions that occur when the consequences of a mutation to a protein are determined by the genetic background in which it occurs. Based on prior data, we hypothesize that epistatic forces operate most strongly between residues nearby in the structure, resulting in smooth evolutionary importance across the structure.
  
  
  RESULTS
  We find that when residue scores of evolutionary importance are distributed smoothly between nearby residues, functional site prediction accuracy improves. Accordingly, we designed a novel measure of evolutionary importance that focuses on the interaction between pairs of structurally neighboring residues. This measure that we term pair-interaction Evolutionary Trace yields greater functional site overlap and better structure-based proteome-wide functional predictions.
  
  
  CONCLUSIONS
  Our data show that the structural smoothness of evolutionary importance is a fundamental feature of the coevolution of sequence, structure and function. Mutations operate on individual residues, but selective pressure depends in part on the extent to which a mutation perturbs interactions with neighboring residues. In practice, this principle led us to redefine the importance of a residue in terms of the importance of its epistatic interactions with neighbors, yielding better annotation of functional residues, motivating experimental validation of a novel functional site in LexA and refining protein function prediction.
  
  
  BACKGROUND
  lichtarge@bcm.edu.
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Department of Molecular and Human Genetics, CIBR Center for Computational and Integrative Biomedical Research and Program in Structural and Computational Biology & Molecular Biophysics, Baylor College of Medicine, Houston, TX 77030 and Center for Human Genetic Research, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA.
authors.forename: Angela D
authors.initials: AD
authors.lastname: Wilkins
authors.forename: Eric
authors.initials: E
authors.lastname: Venner
authors.forename: David C
authors.initials: DC
authors.lastname: Marciano
authors.forename: Serkan
authors.initials: S
authors.lastname: Erdin
authors.forename: Benu
authors.initials: B
authors.lastname: Atri
authors.forename: Rhonald C
authors.initials: RC
authors.lastname: Lua
authors.forename: Olivier
authors.initials: O
authors.lastname: Lichtarge
mesh_terms: D000465:Algorithms; D001426:Bacterial Proteins / Q000737:chemistry; D004843:Epistasis, Genetic; D019143:Evolution, Molecular; D058977:Molecular Sequence Annotation; D009154:Mutation; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry / Q000235:genetics; D020543:Proteome / Q000737:chemistry; D020539:Sequence Analysis, Protein / Q000379:methods*; D012697:Serine Endopeptidases / Q000737:chemistry; D000099160:LexA Repressor Protein
chemical_list: D001426:Bacterial Proteins; D011506:Proteins; D020543:Proteome; D012697:Serine Endopeptidases; D000099160:LexA Repressor Protein
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