Use of the F test for determining the degree of enzyme-kinetic and ligand-binding data. A Monte Carlo simulation study
- 1 April 1983
- journal article
- research article
- Published by Portland Press Ltd. in Biochemical Journal
- Vol. 211 (1), 23-34
- https://doi.org/10.1042/bj2110023
Abstract
1. Initial-rate data were simulated for 13 representative enzyme mechanisms with the use of several distributions of rate constants in order to locate conditions leading to v([S]) curves in physiological ranges of substrate concentration. 2. In all, 420 sets of such v([S]) curves were generated with the use of several choices of substrate concentration range (two, three or four orders of magnitude), number of experimental points (10, 15 or 20), error on v (5-10%) and standard deviation on v (5-9%) in order to simulate experimental results in a number of possible ways. 3. Curve-fitting was carried out to rational functions of degree 1:1, 2:2, …, 5:5 until there was no statistically significant decrease in the sum of weighted squared residuals as judged by the F test at 95% and 99% confidence levels. 4. It was checked whether the non-linear regression program had located a good minimum in the sum of squares by also fitting the data with the correct values of parameters as starting estimates. 5. A similar procedure was adopted with 110 sets of binding data simulated for 11 models, and the F test was used to see if fractional-saturation data generated by a binding polynomial of order n could be adequately fitted by one of order m, m less than n. 6. From the 530 simulations the F test was successful in fixing the correct degree with a probability of 0.62 at the 95% confidence level, but this fell with increase in degree as follows: 1:1 (0.98), 2:2 (0.71), 3:3 (0.43) and 4:4 (0.34), the first numbers being the degree of the rate equation and those in parentheses referring to the 95% confidence level. 7. It made little difference whether the 95% or the 99% confidence level was consulted, as there were very few borderline cases. 8. The chance of detecting deviations from Michaelis-Menten kinetics, i.e. terms of at least second-order in a rate equation of degree n:n, n greater than 1, was estimated to be about 0.8. 9. The probability of the F test leading to a spurious result due to error in the data was found to be about 0.04. 10. The probability with which 4:4 mechanisms can lead to v([S]) plots with no, one, two or three turning points was computed, and it was established that there is a small but finite chance that the increase in degree that occurs in some mechanisms when ES in equilibrium EP interconversions are explicitly allowed for can be detected by the F test.This publication has 29 references indexed in Scilit:
- The probability of obtaining complex kinetic curves for enzyme mechanisms with cubic terms in the pseudo-steady state rate equationsJournal of Theoretical Biology, 1982
- Some mathematical results concerning hessians of binding polynomials and co-operativity coefficientsJournal of Theoretical Biology, 1980
- The structure of steady-state enzyme kinetic equations: A graph-theoretical algorithm for obtaining conditions for reduction in degree by common-factor cancellationJournal of Theoretical Biology, 1979
- Fitting kinetic data for two independent saturable terms by multifit ii, a general purpose curve fitting program in fortran ivJournal of Theoretical Biology, 1978
- Factorability of the Hessian of the binding polynomial. The central issues concerning statistical ratios between binding constants, hill plot slope and positive and negative co-operativityJournal of Theoretical Biology, 1978
- The determination of positive and negative co-operativity with allosteric enzymes and the interpretation of sigmoid curves and non-linear double reciprocal plots for the MWC and KNF modelsJournal of Theoretical Biology, 1978
- The reduction in degree of allosteric and other complex rate equations using sylvester's dialytic method of eliminationJournal of Theoretical Biology, 1977
- Does any enzyme follow the Michaelis—Menten equation?Molecular and Cellular Biochemistry, 1977
- Use of multivariate non-linear regression analysis in fitting enzyme kinetic models: An empirical study of the inhibition of aspartate aminotransferase by dicarboxylic acid substrate analoguesJournal of Theoretical Biology, 1969
- On the nature of allosteric transitions: A plausible modelJournal of Molecular Biology, 1965