GraphPad Curve Fitting Guide

Equation: Mixed-model inhibition

Equation: Mixed-model inhibition

Previous topic Next topic No expanding text in this topic  

Equation: Mixed-model inhibition

Previous topic Next topic JavaScript is required for expanding text JavaScript is required for the print function Mail us feedback on this topic!  

Introduction

The mixed model is a general equation that includes competitive, uncompetitive and noncompetitive inhibition as special cases. The model has one more parameter than the others, and this parameter tells you about the mechanism of inhibition.

Step by step

Create an XY data table. Enter substrate concentration into the X column, and enzyme activity into the Y columns. Each data set (Y column) represents data collected in the presence of a different concentration of inhibitor, starting at zero. Enter these concentrations into the column titles. Be sure to enter concentrations, not logarithms of concentration.

After entering data, click Analyze, choose nonlinear regression, choose the panel of enzyme kinetics equations, and choose Mixed model enzyme inhibition.

Model

VmaxApp=Vmax/(1+I/(Alpha*Ki))

KmApp=Km*(1+I/Ki)/(1+I/(Alpha*Ki))

Y=VmaxApp*X/(KmApp + X)

 

The parameter I is the concentration of inhibitor, a value you enter into each column title. This is constrained to equal a data set constant.

The parameters Alpha, Vmax, Km and Ki are shared, so Prism fits one best-fit value for the entire set of data.

Interpreting the parameters

Vmax is the maximum enzyme velocity without inhibitor, expressed in the same units as Y.

Km is the Michaelis-Menten constant, expressed in the same units as X. It describes the interaction of substrate and enzyme in the absence of inhibitor.

Ki is the inhibition constant, expressed in the same units as I, which you entered into the column titles.

Alpha determines mechanism. Its value determines the degree to which the binding of inhibitor changes the affinity of the enzyme for substrate. Its value is always greater than zero. When Alpha=1, the inhibitor does not alter binding of substrate to the enzyme, and the mixed-model is identical to noncompetitive inhibition. When alpha is very large, binding of inhibitor prevents binding of the substrate and the mixed-model becomes identical to competitive inhibition. When Alpha is very small (but greater than zero), binding of the inhibitor enhances substrate binding to the enzyme, and the mixed model becomes nearly identical to an uncompetitive model.

Reference                                                                         

Equation 3.2 in: RA Copeland, Evaluation of Enzyme Inhibitors in Drug Discovery, Wiley 2005. IBSN:0471686964.RA Copeland, Evaluation of Enzyme Inhibitors in Drug Discovery, Wiley 2005. IBSN:0471686964.