p-hydroxyphenylglycine-methyl-ester and aminopenicillanic-acid

A one-pot, two-step enzymatic synthesis of amoxicillin from penicillin G, using penicillin acylase, is presented. Immobilized penicillin acylase from Kluyvera citrophila was selected as the biocatalyst for its good pH stability and selectivity. Hydrolysis of penicillin G and synthesis of amoxicillin from the 6-aminopenicillanic acid formed and D-p-hydroxyphenylglycine methyl ester were catalyzed in situ by a single enzyme. Zinc ions can react with amoxicillin to form complexes, and the yield of 76.5% was obtained after optimization. In the combined one-pot synthesis process, zinc sulfate was added to remove produced amoxicillin as complex for shifting the equilibrium to the product in the second step. By controlling the conditions in two separated steps, the conversion of the first and second step was 93.8% and 76.2%, respectively. With one-pot continuous procedure, a 71.5% amoxicillin yield using penicillin G was obtained.

Topics: Amoxicillin; Biotechnology; Glycine; Kluyvera; Penicillanic Acid; Penicillin Amidase; Penicillin G; Technology, Pharmaceutical; Zinc

Penicillin G acylase immobilized on glyoxyl-agarose is used to catalyse the reaction between p -hydroxyphenylglycine methyl ester (POHPGME) and 6-aminopenicillanic acid (6-APA). Inhibitory effects affecting the side reactions that occur during the synthesis of amoxicillin have been reported and need to be considered when proposing a kinetic model for the enzymic synthesis. In this work, we present a semi-empirical kinetic model that successively includes different inhibitory effects in the rate equations. The model performance was always compared with experimental data on amoxicillin synthesis. Enzyme load and stirring rate were chosen to prevent diffusional effects. Our results indicate that POHPGME and amoxicillin were competitive inhibitors of the hydrolysis of amoxicillin and POHPGME, respectively. 6-APA was a competitive inhibitor of the hydrolysis of amoxicillin. POHPG was a competitive inhibitor and methanol a non-competitive inhibitor of the hydrolysis of both ester and antibiotic, but the action of methanol was only noticeable at very high concentrations. Adding inhibitory effects to the kinetic model led to a significant increase in the accuracy of the simulations of the overall process of synthesis.

Topics: Amoxicillin; Enzyme Inhibitors; Enzymes, Immobilized; Glycine; Hydrogen-Ion Concentration; Hydrolysis; Kinetics; Methanol; Models, Theoretical; Penicillanic Acid; Penicillin Amidase

A recurrent doubt that occurs to the enzyme-kinetics modeler is, When should I stop adding parameters to my mechanistic model in order to fit a non-conventional behavior? This problem becomes more and more involving when the complexity of the reaction network increases. This work intends to show how the use of artificial neural networks may circumvent the need of including an overwhelming number of parameters in the rate equations obtained through the classical, mechanistic approach. We focus on the synthesis of amoxicillin by the reaction of p-OH-phenylglycine methyl ester and 6-aminopenicillanic acid, catalyzed by penicillin G acylase immobilized on glyoxyl-agarose, at 25 degrees C and pH 6.5. The reaction was carried on a batch reactor. Three kinetic models of this system were compared: a mechanistic, a semi-empiric, and a hybrid-neural network (NN). A semi-empiric, simplified model with a reasonable number of parameters was initially built-up. It was able to portray many typical process conditions. However, it either underestimated or overestimated the rate of synthesis of amoxicillin when substrates' concentrations were low. A more complex, full-scale mechanistic model that could span all operational conditions was intractable for all practical purposes. Finally, a hybrid model, that coupled artificial neural networks (NN) to mass-balance equations was established, that succeeded in representing all situations of interest. Particularly, the NN could predict with accuracy reaction rates for conditions where the semi-empiric model failed, namely, at low substrate concentrations, a situation that would occur, for instance, at the end of a fed-batch industrial process.

Topics: Amoxicillin; Bioreactors; Computer Simulation; Enzymes, Immobilized; Gels; Glycine; Kinetics; Models, Chemical; Neural Networks, Computer; Penicillanic Acid; Penicillin Amidase; Quality Control; Reproducibility of Results; Sensitivity and Specificity; Sepharose