In silico identification and characterization of antineoplastic asparaginase enzyme from endophytic bacteria

It is generally accepted that L-asparagine is an important amino acid required for the fast growth of cells. Cancerous cells receive this amino acid from extracellular sources. The depletion of L-asparagine from its surrounding environments by asparaginase enzyme can be used as a therapeutic strategy in cancer patients. This therapeutic enzyme is produced commercially mainly from bacteria such as Escherichia coli and Erwinia chrysanthemi. The side effects of such drugs have persuaded scientists to find new enzyme sources. In this study, in silico approach was applied to investigate L-asparaginase producing endophytic bacteria that produce more compatible enzymes within the body. Protein-protein basic local alignment search tool with E. coli and E. chrysanthemi asparaginase enzyme sequences against 262 endophytic bacteria were performed. The results with identity more than 35%, coverage more than 80%, and E-value less than 10^-4 were selected. Then, some of bioinformatics tools were used to characterize them. A total of nine sequences consisting of seven known and two hypothetical proteins were identified in six bacterial species. The results showed that some of the asparaginase enzymes produced by endophytic bacteria possess more suitable immunological indices compared with asparaginase enzymes of E. coli and E. chrysanthemi. Herbaspirillum rubrisubalbicans was predicted to produce a nonallergen and nonantigen asparaginase enzyme. The number of antigenic determinants was predicted to be lower in asparaginase enzymes produced by Bacillus amyloliquefaciens, H. rubrisubalbicans, and H. seropedicae. Moreover, the number of high-scored B-cell epitopes was lower in enzyme sequences related to the mentioned bacteria and Paenibacillus polymyxa. The number of discontinuous epitopes and the number of T-cell epitopes were lower in B. amyloliquefaciens produced enzymes. Therefore, the therapeutic use of these enzymes is possible.