Pedro Valencia

Batch reactor performance for the enzymatic synthesis of cephalexin: influence of catalyst enzyme loading and particle size

A mathematical model is presented for the kinetically controlled synthesis of cephalexin that describes the heterogeneous reaction-diffusion process involved in a batch reactor with glyoxyl-agarose immobilized penicillin acylase. The model is based on equations considering reaction and diffusion components. Reaction kinetics was considered according to the mechanism proposed by Schroën, while diffusion of the reacting species was described according to Ficks law. Intrinsic kinetic and diffusion parameters were experimentally determined in independent experiments. It was found that from the four kinetic constants, the one corresponding to the acyl-enzyme complex hydrolysis step had the greatest value, as previously reported by other authors. The effective diffusion coefficients of all substances were about 5×10(-10)m(2)/s, being 10% lower than free diffusion coefficients and therefore agreed with the highly porous structure of glyoxyl-agarose particles. Simulations made from the reaction-diffusion model equations were used to evaluate and analyze the impact of internal diffusional restrictions in function of catalyst enzyme loading and particle size. Increasing internal diffusional restrictions decreases the Cex synthesis/hydrolysis ratio, the conversion yield and the specific productivity. A nonlinear relationship between catalyst enzyme loading and specific productivity of Cex was obtained with the implication that an increase in catalyst enzyme loading will not increase the volumetric productivity by the same magnitude as it occurs with the free enzyme. Optimization of catalyst and reactor design should be done considering catalyst enzyme loading and particle size as the most important variables. The approach presented can be extended to other processes catalyzed by immobilized enzymes.

Kinetic Parameter Determination for Enzyme Hydrolysis of Fish Protein Residue Using D-optimal Design

The objective of this work was to compare the quality of parameter estimation from experiments with protein hydrolysis of fish muscle carried out following a traditional versus D-optimal design of experiments. Traditional design was done from hydrolysis experiments using the rapid titration method, from which a large number of data points was obtained and made available for parameter estimation. D-optimal design is recommended under conditions when it would not be possible to use rapid titration with analytical tools. Such conditions would make it necessary to reduce the number of samples that would need to be taken as well as the error and variance in the estimated parameters needed for the kinetic model. Results have shown that D-optimal and traditional designs of experiments obtained accurate and reliable estimates of kinetic model parameters, with a great difference in the number of data points between both types of design: 18 points in traditional and 3 points in D-optimal design. Nevertheless, a few number of observations in D-optimal design impacted negatively the confidence interval because of a low degree of freedom. Confidence intervals ranging from 7.8% to 87% of the parameters values were obtained with D-optimal design method in contrast with traditional design where confidence intervals ranged from 6.2% to 15% of the parameters values. It is estimated that combining the advantages of both types of design will result in an optimal experimental design in terms of reliability, accuracy, and costs saving of analysis. This would be done by determining the number of observations required to achieve an appropriate confidence interval (about six or more experimental points) and, then, a selection of the best experimental points of a curve of hydrolysis by D-optimal design.

Technical Feasibility of Glucose Oxidase as a Prefermentation Treatment for Lowering the Alcoholic Degree of Red Wine

In the present work, the use of the glucose oxidase/catalase enzymatic system was evaluated as an alternative to decrease glucose concentration and eventually produce a reduced-alcohol wine. The effects of glucose oxidase, catalase, and aeration on glucose concentration were evaluated after 24 and 48 hr of treatment of 27°Brix Carmenere must. The results showed that the effect of aeration and glucose oxidase was not significant compared with the effect produced by glucose oxidase itself. In addition, the use of catalase combined with glucose oxidase provided the best result, decreasing the glucose concentration by 51 and 78% after 24 and 48 hr, respectively, when 200 U/mL of both enzymes was used. The alcoholic degree obtained after three and five days under this treatment and subsequent fermentations were 15% (v/v) ± 0.8 and 14% (v/v) ± 0.8, respectively. A major drawback of this treatment was the color change of Carmenere must because H2O2 was produced during the glucose oxidase treatment, despite the presence of catalase. The technical feasibility of using this prefermentative process led to a divided conclusion; obtaining a lower alcoholic degree using the glucose oxidase/catalase system was possible, but if the goal is the industrial application of this technique, the color change should be investigated further. An evaluation of the glucose oxidase/catalase ratio was projected to show an improvement of the H2O2 elimination and, subsequently, decrease the effect on color change.

Calculation of statistic estimates of kinetic parameters from substrate uncompetitive inhibition equation using the median method

We provide initial rate data from enzymatic reaction experiments and tis processing to estimate the kinetic parameters from the substrate uncompetitive inhibition equation using the median method published by Eisenthal and Cornish-Bowden (Cornish-Bowden and Eisenthal, 1974; Eisenthal and Cornish-Bowden, 1974). The method was denominated the direct linear plot and consists in the calculation of the median from a dataset of kinetic parameters Vmax and Km from the Michaelis–Menten equation. In this opportunity we present the procedure to applicate the direct linear plot to the substrate uncompetitive inhibition equation; a three-parameter equation. The median method is characterized for its robustness and its insensibility to outlier. The calculations are presented in an Excel datasheet and a computational algorithm was developed in the free software Python. The kinetic parameters of the substrate uncompetitive inhibition equation Vmax, Km and Ks were calculated using three experimental points from the dataset formed by 13 experimental points. All the 286 combinations were calculated. The dataset of kinetic parameters resulting from this combinatorial was used to calculate the median which corresponds to the statistic estimator of the real kinetic parameters. A comparative statistical analyses between the median method and the least squares was published in Valencia et al. [3].