Enhanced production of alkane hydroxylase from Penicillium chrysogenum SNP5 (MTCC13144) through feed-forward neural network and genetic algorithm.

ABSTRACT: Alkane hydroxylase (AlkB), a membrane-bound enzyme has high industrial demand; however, its economical production remains challenging due to its intrinsic nature and co-factor dependency. In the current study, various critical process parameters for optimum production of AlkB have been optimized through feed forward neural network (FFNN) and genetic algorithm (GA) models using Penicillium chrysogenum SNP5 (MTCC13144). AlkB specific activity under preliminary un-optimized conditions i.e., 1% hexadecane, 7.4 pH, 11 days incubation time, 28 °C incubation temperature and 1 ml of inoculum size was 100 U/mg. 'One variable at a time' (OVAT) strategy was used to identify optimum physicochemical parameters and then its output data was fed to develop a model of FFNN with '6-12-1' topology. Outputs o

SUBMITTER: Das S 

PROVIDER: S-EPMC8894539 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature