Selection of the Optimal L-asparaginase II Against Acute Lymphoblastic Leukemia: An In Silico Approach

Background L-asparaginase II (asnB), a periplasmic protein commercially extracted from E coli and Erwinia, is often used to treat acute lymphoblastic leukemia. an enzyme that converts L-asparagine aspartic acid ammonia. Cancer cells are dependent on asparagine other sources for growth, when these deprived of by the action enzyme, cancer selectively die. Objective Questions remain as whether asnB Erwinia best asparaginase they have many side effects. asnBs with lowest Michaelis constant (Km; most potent) immunogenicity considered optimal enzymes. In this paper, we attempted development method screen enzymes better than available Methods sequence was search homologous proteins in different bacterial archaeal phyla, maximum likelihood phylogenetic tree constructed. The sequences distant were candidates terms chosen further processing. structures built homology modeling, docked calculate binding energy. Results Streptomyces griseus, venezuelae, collinus found highest energy (–5.3 kcal/mol, –5.2 –5.3 respectively; higher asnBs) predicted Kms, there inverse relationship between Km. Besides predicting asparaginase, technique can also be predict where substrate known structure one homologs solved. Conclusions We devised silico kinetics along being able alternative against