Improvement of trypanocidal metabolites production by Aspergillus fumigatus using neural networks.
An optimization procedure using artificial neural networks was developed to determine the optimal combination of parameters, such as medium culture, initial pH, temperature and time of fermentation for maximal trypanocidal metabolites production by Aspergillus fumigatus. A data set of 81 experiments was carried out and an artificial neural network was trained to identify the optimal conditions for this process. Good correlation was obtained between the experimental and predicted values of lysis of the trypomastigote forms of Trypanosoma cruzi (r2 = 0.9990). The simulations of fermentation performance were undertaken on combinations of input variables and the highest level of activity against T. cruzi was obtained from the chloroform extract of the modified Jackson medium culture, initial pH of 6.0, incubated at 40 degrees C for 144 h. It displayed lysis of 95% of the trypomastigote forms of T. cruzi and the red blood cells remained normal.
Jacometti Cardoso Furtado
Niege Araçari
NA
Faculdade de Ciências Farmacêuticas de Ribeirão Preto, Universidade de São Paulo, CEP 14040-903, Ribeirão Preto, SP, Brazil.
Teixeira Duarte
Marta Cristina
MC
de Albuquerque
Sérgio
S
Mello
Cesar
C
Kenupp Bastos
Jairo
J
D000818:Animals; D001232:Aspergillus fumigatus / Q000254:growth & development* / Q000378:metabolism*; D001709:Biotechnology / Q000379:methods; D003470:Culture Media; D005285:Fermentation; D006863:Hydrogen-Ion Concentration; D008954:Models, Biological; D016571:Neural Networks, Computer; D021261:Parasitic Sensitivity Tests; D013696:Temperature; D014344:Trypanocidal Agents / Q000378:metabolism* / Q000494:pharmacology; D014349:Trypanosoma cruzi / Q000187:drug effects*
D003470:Culture Media; D014344:Trypanocidal Agents