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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 ofk app in eukaryotes is lacking. Here, we estimatedk app of the yeastSaccharomyces cerevisiae under diverse conditions. By comparing the maximumk app across conditions with in vitrok cat we found a weak correlation in log scale ofR 2 = 0.28, which is lower than forEscherichia coli (R 2 = 0.62). The weak correlation is caused by the fact that many in vitrok cat values were measured for enzymes obtained through heterologous expression. Removal of these enzymes improved the correlation toR 2 = 0.41 but still not as good as forE. coli , suggesting considerable deviations between in vitro and in vivo enzyme activities in yeast. By parameterizing an enzyme-constrained metabolic model with ourk app dataset we observed better performance than the default model with in vitrok cat in predicting proteomics data, demonstrating the strength of using the dataset generated here.

In vitro turnover numbers do not reflect in vivo activities of yeast enzymes