engleski

Choosing the most appropriate design of experiment for enzymatic research

Design of Experiment (DOE) is one of the most efficient tools that enables improving the efficiency of experimentation, reducing costs and obtaining many relevant information on the desired system [1]. In addition, it allows gaining knowledge on investigated parameters and their interaction with minimal number of experiments [2]. In order to investigate which design of experiment is the most suitable for investigation and optimization of the enzyme efficiency, in this work we have compared several different designs (General, Two level fractorial, Box Behnken, and D-optimal designs) for the optimization of model enzyme sample (Pectinase). During the optimization we have varied temperature (in ranges from 20 to 50 ºC), pH (in ranges from 3 to 7) and the volume of the enzyme (in ranges from 20 to 80 μL) in the system in order to estimate their individual and mutual effects on the enzymatic efficiency. The function of the optimization was “reducing sugars” function which was measured with the 3, 5-dinitrosalicylic acid (DNSA) assay procedure after 24 hours as the amount of galacturonic acid. The highest concentration of liberated galacturonic acid was reached at 45°C on a thermo-shaker with 80 μL of enzyme solution in citrate buffer pH 4. This experimental optimum was compared to data obtained after calculation with different designs of experiment, and a very good agreement between those data was achieved. Moreover, our results have shown that D-optimal design was the most suitable design for enzymatic research. In contrast, Box Behnken design was suitable only for preliminary testing of desired system and predicting the optimal working area. Therefore we showed that DOE is the methodology that enables comprehensive analysis of complex systems with highly efficiency, reduced costs and increased value of the quality of the obtained information.

design of experiment ; optimization ; ensymatic research

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