Assay Characteristics

A sound assay, regardless of the level of sophistication required, will have (1) linear dependence on enzyme concentration, (2) adequate consideration of pH and temperature effects, (3) appropriate accuracy, (4) adequate sensitivity, and (5) speed and ease of performance. Unfortunately, many assays emphasize the last factor at the expense of the other four.

Enzyme Linearity. Enzyme linearity is paramount. A curved plot of assay response versus amount of enzyme used indicates that some chemical, physical, and/or en-zymological factors have been overlooked. In fixed-time assays the formation of product is often not strictly linear with time because of substrate depletion or product inhibition and this nonlinearity is more pronounced at higher enzyme concentrations. Occasionally the chemical reaction used to quantitate the amount of product formed is not stoichiometric, leading to a nonlinear plot of, for example, spectrophotometric absorbance versus enzyme amount. Numerous nonlinear assays found in the literature indicate an incomplete understanding of the system being used for the assay.

Many assays are linear over a limited range of activity. These may be used (particularly if they meet the requirement for ease of use) if care is taken to ensure that measurements are made only within the linear range.

Temperature, pH. Elevated temperatures and extremes of pH contribute to enzyme denaturation during the assay. Temperature optimum curves are always due to this phenomenon, and activity decreases at high or low pH also may be due to enzyme instability. The pH also may affect enzyme catalytic activity, influencing the ionization state of the active site and possibly the substrate (2-4). A sound assay will take these factors into account.

Accuracy, Sensitivity. The required levels of accuracy (more properly, precision) and sensitivity should be carefully considered. Measurements of a-amylase activity may have a coefficient of variation of 2% or of 10%, depending on whether the assay is a replicated colorimetric one using a modified substrate (5) or a viscometric one using gelatinized ground grain (6). For standardizing a purified amylase for use in bread production, the former would be appropriate, while for identifying bins of wheat that has been subjected to sprouting, the latter method is quite adequate. Likewise, assays at almost any level of sensitivity may be constructed. Using a fluorescent substrate, pico-molar concentrations of trypsin may be assayed (7), while in monitoring the production of microbial protease a simple protein-based assay (8) will do the job, although it is some five orders of magnitude less sensitive.

Convenience. Speed and ease of performance should be the last factors considered. These are important in many industrial contexts, but a fast, easy, inadequate assay will only result in the rapid generation of much useless data. After linearity, precision, enzyme stability, and sensitivity are established, then steps may be taken to increase output.

Initial Rates. Most assays measure the rate of formation of product from substrate, that is, d[P]/dt. This measurement may be of the initial rate, d[P] /dt, at the initiation of the reaction, or of the amount of product formed during a fixed time of incubation of substrate with enzyme. Fixed-time assays are convenient, in that a large number of samples may be run simultaneously. Unfortunately, they are also more prone to complications leading to the nonlinearity mentioned above. Accurate initial rate measurements are not contaminated by effects such as substrate depletion, product inhibition, or enzyme denaturation. However, they are not always easy to obtain. A relatively simple method of finding the initial rate is the following. Set up the assay system, take samples at various times t, and measure product concentration [P] at each time. Usually there is a slight downward curve of the plot of [P] versus t (Fig. 1) that makes the determination of the tangent (d[P]/dt) at zero time difficult. Using a simple program (Basic, or even most spreadsheet programs today are capable of this), fit the data points with a least squares quadratic curve:

The first derivative gives the desired initial rate with reasonable accuracy:

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