Inference of functional regions in proteins by quantification of evolutionary constraints.
Likelihood estimates of local rates of evolution within proteins reveal that selective constraints on structure and function are quantitatively stable over billions of years of divergence. The stability of constraints produces an intramolecular clock that gives each protein a characteristic pattern of evolutionary rates along its sequence. This pattern allows the identification of constrained regions and, because the rate of evolution is a quantitative measure of the strength of the constraint, of their functional importance. We show that results from such analyses, which require only sequence alignments, are consistent with experimental and mutational data. The methodology has significant predictive power and may be used to guide structure--function studies for any protein represented by a modest number of homologs in sequence databases.
Simon
Alexander L
AL
Program in Cancer Biology and Department of Pathology, Stanford University Medical School, Stanford, CA 94305-5324, USA.
Stone
Eric A
EA
Sidow
Arend
A
D000818:Animals; D001665:Binding Sites; D019143:Evolution, Molecular; D017434:Protein Structure, Tertiary; D011506:Proteins / Q000737:chemistry / Q000145:classification / Q000502:physiology*; D016415:Sequence Alignment; D013329:Structure-Activity Relationship
D011506:Proteins