Isolation and computational investigation of class ۳ L- asparaginase form a native Glutamicibacter. SP.

L- asparaginases are important therapeutic drugs. Type II asparaginases are still used to treatchildhood leukemia. Although these enzymes have been successfully used in treatment, they areassociated with many side effects [۱], so much research directed to find alternative enzymes. The soilsamples were collected from agricultural fields near Saveh, Markazi province. After screening onphenol red agar, the best isolate identified by molecular and biochemical methods as Glutamicibactersp. The specific primers that cover the full length of the asparaginase gene were designed based oncomplete genomes of the nearest type strains. After amplification and sequencing, the translated aminoacid sequence aligned with ۲۸ full-length sequences of type I and II from class ۱ and class ۳ Lasparaginasesthrough the MAFFT algorithm and curated by the BMGE method on the online serverNGPhylogeny (http://www.NGPhylogeny.fr). The phylogenetic tree was created using the maximumlikelihood method based on the Le Gascuel model by Mega-۷ software [۲]. The phylogenetic tree showsthe clustering of new isolate L-asparaginase with newly found Rhizobium etli class ۳ asparaginases oftype IV and V. Bootstrap values ensure that their relationship is strong. The three-dimensional structureof the enzyme was predicted by the ColabFold v۱.۵.۵ server [۳]. The structure of asparagin wasconstructed by ChemDraw v.۱۷.۳ and optimized using MM۲ calculation available in ChemBio۳D ۱۷.۳[۴]. Autodock Vina via the Chimera platform was used for docking. The binding energy for the mostfavorable structure based on docking score are -۴.۶, -۴.۴, and -۴.۴ Kcal/mol for new asparaginase,ReAV, and ReAIV, respectively. The new isolated L- asparaginase from Glutamicicbacter seems apromising target for new drug development. However, future in-vivo and in-vitro studies are essentialto illustrate more about this target.

کلیدواژه ها:

L-asparaginase ، Acute lymphoblastic leukemia ، Phylogenetic analysis ، MolecularDocking