Turnover numbers ( k cat values) quantitatively represent the activity of enzymes, which are mostly measured in vitro. While a few studies have reported in vivo catalytic rates ( k app values) in bacteria, a large-scale estimation of k app in eukaryotes is lacking. Here, we estimated k app of the yeast Saccharomyces cerevisiae under diverse conditions. By comparing the maximum k app across conditions with in vitro k cat we found a weak correlation in log scale of R 2 = 0.28, which is lower than for Escherichia coli ( R 2 = 0.62). The weak correlation is caused by the fact that many in vitro k cat values were measured for enzymes obtained through heterologous expression. Removal of these enzymes improved the correlation to R 2 = 0.41 but still not as good as for E. coli , suggesting considerable deviations between in vitro and in vivo enzyme activities in yeast. By parameterizing an enzyme-constrained metabolic model with our k app dataset we observed better performance than the default model with in vitro k cat in predicting proteomics data, demonstrating the strength of using the dataset generated here.
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Chen et al. (2021) studied this question.
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