Using design of experiment to optimize enzyme activity assays

Abstract

This laboratory exercise teaches students the application of design of experiments (DOE) for optimizing a trypsin activity assay using the artificial substrate Nα-benzoyl-l-arginine-p-nitroanilide (BAPNA). The response surface modeling (RSM) approach is exploited to design and evaluate the combined effects of relevant factors on the inhibition of trypsin by the competitive inhibitor benzamidine. RSM matrices and statistics are generated using commercial software. Experimental data are compared with Michaelis–Menten theory. The predicted values are in good agreement with the experimental data. The comprehensive analysis of data provides deep insight into the relationship between substrate, inhibitor concentration, and assay sensitivity in the context of high-throughput drug screening. Data analysis reveals also unexpected but explainable interactions between the substrate and the pH value in the applied enzyme activity assay. The combined design, performance, and analysis of practical experiments demonstrates that DOE is an excellent tool to explore the relationship between several parameters affecting the enzyme activity and to optimize functional enzyme activity assays in a variety of applications.