Aplicação da lógica fuzzi na produção de penicilina G Acilase em cultivos de Bacillus megaterium

• Autor(a) principal: Nucci, Edson Romano
• Data de Publicação: 2003
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Repositório Institucional da UFSCAR
• Texto Completo: https://repositorio.ufscar.br/handle/ufscar/4052
• topic: Biotecnologia; Lógica nebulosa; Soft sensoring; Aquisição de banco de dados; Sistema supervisório; Penicilina G Acilase; ENGENHARIAS::ENGENHARIA QUIMICA

Penicillin G acylase (PGA) is an important enzyme for the pharmaceutical industry. This enzyme has industrial use in the hydrolysis of penicillin G to obtain 6-aminocephalosporanic acid (6-APA), essential intermediate for the production of beta-lactam antibiotics. Many microorganisms produce PGA, but Bacillus megaterium is one of the few that excretes the enzyme to the extra cellular medium, facilitating downstream operations. Another recently enzyme application refers to enzymatic synthesis of semi-synthetics antibiotics as amoxilin and amphicilin via green route. This work studied the pH influence on the production of the enzyme. An algorithm based on the Fuzzy logic theory was implemented aiming to determine the maximum enzyme concentration during Bacillus megaterium cultivations. Experiments were carried out in a bioreactor (5 liter working volume) coupled to a data acquisition system using a Programmable Logic Controller and Supervisory System. Experiments carried out under pH control showed a decreasing in enzyme concentration compared to standard experiments. This result could be related to production of proteases by microorganism or enzyme deactivation caused by local acid addition. Two algorithms were implemented. The first was programmed in Fortran and linked as dynamic link library in a Visual Basic program to exchange on-line information with data acquisition system. The second one was implemented in MatLab (Mathworks, 5.2) software. On-line variables as cultivation time, carbon dioxide concentration and time carbon dioxide concentration derivate were used as information to Fuzzy algorithm. Both algorithms were able to accurately identify the time for which the enzyme reached its maximum. The first algorithm was tested in real time in two experiments.