RT Journal Article SR Electronic T1 Selection on network dynamics drives differential rates of protein domain evolution JF bioRxiv FD Cold Spring Harbor Laboratory SP 026658 DO 10.1101/026658 A1 Brian K. Mannakee A1 Ryan N. Gutenkunst YR 2015 UL http://biorxiv.org/content/early/2015/09/11/026658.abstract AB The long-held principle that functionally important proteins evolve slowly has recently been challenged by studies in mice and yeast showing that the severity of a protein knockout only weakly predicts that protein’s rate of evolution. However, the relevance of these studies to evolutionary changes within proteins is unknown, because amino acid substitutions, unlike knockouts, often only slightly perturb protein activity. To quantify the phenotypic effect of small biochemical per-turbations, we developed an approach to use computational systems biology models to measure the influence of individual reaction rate constants on network dynamics. We show that this dynamical influence is predictive of protein domain evolutionary rate in vertebrates and yeast, even after controlling for expression level and breadth, network topology, and knockout effect. Thus, our results not only demonstrate the importance of protein domain function in determining evolutionary rate, but also the power of systems biology modeling to uncover unanticipated evolutionary forces.