2015
DOI: 10.1098/rspb.2015.2215
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Dynamic sensitivity and nonlinear interactions influence the system-level evolutionary patterns of phototransduction proteins

Abstract: Determining the influence of complex, molecular-system dynamics on the evolution of proteins is hindered by the significant challenge of quantifying the control exerted by the proteins on system output. We have employed a combination of systems biology and molecular evolution analyses in a first attempt to unravel this relationship. We employed a comprehensive mathematical model of mammalian phototransduction to predict the degree of influence that each protein in the system exerts on the high-level dynamic be… Show more

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Cited by 4 publications
(3 citation statements)
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“…Our results are relevant to recent studies suggesting that mechanisms of epistatic interactions between specific amino acids must be understood by studying various orthologues in different species that have adapted to different environments 54 . These findings contribute to the emerging trend that complex non-linear interactions seem to be at the base of phototransduction evolution 55 .…”
Section: Discussionsupporting
confidence: 56%
“…Our results are relevant to recent studies suggesting that mechanisms of epistatic interactions between specific amino acids must be understood by studying various orthologues in different species that have adapted to different environments 54 . These findings contribute to the emerging trend that complex non-linear interactions seem to be at the base of phototransduction evolution 55 .…”
Section: Discussionsupporting
confidence: 56%
“…Our results are relevant to recent studies suggesting that mechanisms of epistatic interactions between specific amino acids must be understood by studying various orthologues in different species that have adapted to different environments (S. Yokoyama et al, 2014). These findings contribute to the emerging trend that complex non-linear interactions seem to be at the base of phototransduction evolution (Invergo, Montanucci, & Bertranpetit, 2015).…”
Section: 24)supporting
confidence: 63%
“…We have shown that incorporating that detail can, for domains within dynamical networks, explain the previous lack of correlation between protein function and evolutionary rate. Dynamical models have previously been used to predict the phenotypic effects of mutations [ 79 ] and to assess the correlation between network sensitivity and protein evolution in phototransduction [ 80 ] and in pyrimidne biosynthesis [ 81 ]. Here we consider many networks to reveal a previously unexplored and general link between dynamical influence and protein domain evolutionary rate within networks.…”
Section: Resultsmentioning
confidence: 99%