Enzyme Assay Optimization

It is very difficult to give specific guidelines for assay development in HTS due to the complexity of variables involved and because one often must balance cost, speed, sensitivity, statistical robustness, automation requirements, and desired mechanisms. The typical parameters to test are shown in Figure 1.3. Schematically, the assay development process can be thought of as a cycle in which several variables can be tested and the parameters that give a better "reading window" can be fixed, allowing further parameters to be tested under the prior fixed conditions. Often, one observes interactions among the various parameters. For example, the optimal detergent concentration may not be the same for every pH and that is why the same fixed parameters must sometimes be retested under newly identified optimal parameters. Furthermore, the type of optimization experiments depends upon the particular technology used.

In its simplest form, building an assay is a matter of adding several reagent solutions to a micro-titer plate (MTP) with a multi-channel pipette, at various incubation times, stopping the reaction if required, and reading the MTP in a plate reader. A typical procedure may involve: (1) adding the enzyme solution to a compound-containing microtiter plate and incubating for 15 min; (2) adding substrates and incubating for 15 to 60 min; (3) adding a stopping reagent such as EDTA (for kinases) or sodium orthovanadate (for phosphatases); (4) adding sensor or detector reagents such as labeled antibodies or coupling enzymes; and (5) measuring in a plate reader. The specific detector reagents, assay reagent volumes, concentrations of reagents, incubation times, buffer conditions, MTP types, and assay stopping reagents are all important parameters that must be tested.


Carrier protein





Assay Component

Example Range

Enzyme conc.

1-50 nM

pH value



0.1-10 uM

Substrate conc.

0.1-10 uM


0.25-3 hours


Mg, Mn (mM)




0.05% NP-40, Tween-20, CHAPS, pluronic


BSA, gelatin, casein, 0.1%


5-20 nM

FIGURE 1.3 Assay optimization cycle and typical test parameters.

A very important part of assay development is making an appropriate choice of substrates. Where possible, it is desirable to choose a physiological substrate, although this is not always practical. For example, with phosphatases, using fluorescent small molecule substrates to obtain good assay robustness presents good advantages. With kinases, it is often possible to perform a substrate screen in which many random peptide sequences are tested to identify good substrates.

Based on the many factors that must be optimized, statistical design of experiment software (e.g., JMP software from SAS) can be employed to determine the minimal number of variables for drawing statistically significant inferences (Rodgers et al., 2003). Furthermore, design of experiment software can be coupled to automated pipettes to rapidly run multi-variable experiments (e.g., SAGIAN from Beckman Instruments). The disadvantage of using purely statistical parameters in assay optimization is that these systems do not take into account the desired physiological or biochemical mechanism of action in determining optimal reagent concentration. For example, the optimal substrate concentration to use in an enzyme assay may not necessarily be the one that gives the best statistics with respect to reproducibility. The optimal salt concentration required for reproducibility may be far different from physiological concentration. Therefore, one must be careful in using these systems in a way that is consistent with the desired mechanism of action of the lead compound.

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