Proteins with greater influence on network dynamics evolve more slowly but are not more essential
Ryan N. Gutenkunst

TL;DR
This study introduces dynamical influence as a detailed measure of protein importance in biochemical networks, revealing that proteins with higher influence evolve more slowly, independently of their essentiality or expression characteristics.
Contribution
The paper develops a new measure called dynamical influence based on biochemical models, linking it to evolutionary rates and challenging previous assumptions about essentiality.
Findings
Proteins with higher dynamical influence evolve more slowly.
Dynamical influence is not correlated with protein essentiality.
Influence on evolution rate is independent of expression and gene features.
Abstract
A fundamental question for evolutionary biology is why rates of evolution vary dramatically between proteins. Perhaps surprisingly, it is controversial how much a protein's functional importance affects its rate of evolution. In most studies, functional importance has been measured on the coarse scale of protein knock-outs, while evolutionary rate has been measured on the fine scale of amino acid substitutions. Here we introduce dynamical influence, a finer measure of protein functional importance. To measure dynamical influence, we first use detailed biochemical models of particular reaction networks to measure the influence of each reaction rate constant on network dynamics. We then define the dynamical influence of a protein to be the average influence of the rate constants for all reactions it is involved in. Using models of a dozen biochemical systems and sequence data from…
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Taxonomy
TopicsBioinformatics and Genomic Networks · Protein Structure and Dynamics · Evolution and Genetic Dynamics
