A further consideration is required when studying multi-substrate enzymes, since the saturation level of the unlabeled substrate can often influence the observed KIE for the labeled one ( Cook, 1991, Cook and Cleland, 2007 and Kohen and Limbach, 2006). Each of these factors are critical when determining if the measured KIE reflects an observed value, whether an intrinsic KIE has been assessed, which step along the catalytic cycle the KIE may reflect, and for comparing the results from enzymes obtained from different sources or their mutants. Finally, the raw data used to calculate isotope effects

U0126 purchase should always be presented either in the main text or in the supplementary information to allow for a critical review of the conclusions by the reader, and to enable their use in an alternative analysis or for comparison to new data collected in the future. Conclusions are often drawn from trends in the KIEs observed with either pH, temperature, or upon

site-directed mutation of the enzyme. Figures or tables showing the parameters and their standard deviation or standard errors obtained from overall fits of isotope effect data to the relevant equations are often the most effective and meaningful MLN0128 way of reporting results. While it is typically appropriate to exclude the raw data from the main text the results should be presented as supplemental information whenever possible. A critical yet often neglected component of reports on KIEs is a clear description of how error analysis was performed. Like any experimental measurement there is a certain level of uncertainty regarding precision and accuracy when measuring a KIE for an enzymatic reaction. Even in the simple example of the common non-competitive method, which involves separate rate measurements of both the

light and heavy isotopes, each rate has to be measured by several repeats under the same conditions, the errors from each measurement (whether from continuous or other assays) should be propagated when calculating the average value for each set of conditions. Then, the errors associated with each rate need to be propagated and reported in the ratio of rates Alanine-glyoxylate transaminase between light and heavy isotopologues, i.e., the KIE. While the competitive method reduces the error propagation by directly comparing both the light and heavy isotopes to measure a KIE rather than rates, it also involves multiple measurements to assess the confidence in the measured value. The errors associated with each measurement must also be propagated when averaging the KIE. Furthermore, since KIEs are typically more meaningful when reported for kinetic parameters rather than a single rate, special attention must be paid as to how the raw data are fit to calculate the effects of isotopic substitution.