The use of evolutionary patterns in protein annotation.
With genomic data skyrocketing, their biological interpretation remains a serious challenge. Diverse computational methods address this problem by pointing to the existence of recurrent patterns among sequence, structure, and function. These patterns emerge naturally from evolutionary variation, natural selection, and divergence--the defining features of biological systems--and they identify molecular events and shapes that underlie specificity of function and allosteric communication. Here we review these methods, and the patterns they identify in case studies and in proteome-wide applications, to infer and rationally redesign function.
Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA.
Angela D
AD
Wilkins
Benjamin J
BJ
Bachman
Serkan
S
Erdin
Olivier
O
Lichtarge
D019295:Computational Biology / Q000379:methods; D019143:Evolution, Molecular; D023281:Genomics; D058977:Molecular Sequence Annotation; D011506:Proteins / Q000737:chemistry* / Q000145:classification
D011506:Proteins