Recombinant l-glutaminase obtained from Geobacillus thermodenitrificans DSM-465: characterization and in silico elucidation of conserved structural domains

从嗜热脱氮地芽孢杆菌 DSM-465 获得的重组 l-谷氨酰胺酶:保守结构域的表征和计算机模拟阐明

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作者:Luqman Shah, Muhammad Shahid Nadeem, Jalaluddin Azam Khan, Mustafa A Zeyadi, Mazin A Zamzami, Kaleemuddin Mohammed

Abstract

Glutaminase (GLS) is an enzyme essential for amino acid metabolism; in particular, it acts as a catalyst in glutaminolysis, a reaction exploited by the malignant cells to meet the nutrient requirements for their accelerated growth and proliferation. Via regulating the initial reaction of the glutaminolysis pathway, glutaminase offers an intriguing target for the development of anticancer drugs. In the present study, we produced a recombinant glutaminase from Geobacillus thermodenitrificans DSM-465 in E. coli. The enzyme was purified to electrophoretic homogeneity, with 40% recovery and 22.36 fold purity. It exhibited a molecular weight of 33 kDa, with an optimum pH and temperature of 9 and 70 °C, respectively. The K M value of the purified enzyme was 104 μM for l-glutamine. A 3D model was built for the enzyme using Swiss-Model and subjected to molecular docking with the substrate and potential inhibitors. Moreover, the subject enzyme was compared with the human kidney type GLS-K by ConSurf and TM-align servers for evolutionary conserved residues and structural domains. Despite having less than 40% amino acid identity, the superimposed monomers of both enzymes exhibited ∼94% structural identity. With a positional difference, the active site residues Ser65, Asn117, Glu162, Asn169, Tyr193, Tyr245, and Val263 found in the bacterial enzyme were also conserved in the human GLS-K. Molecular docking results have shown that CB-839 is the best inhibitor for GLS-GT and UPGL00004 is the best inhibitor for GLS-K, as designated by the binding free energy changes, i.e. ΔG -388.7 kJ mol-1 and ΔG -375 kJ mol-1, respectively. Moreover, six potential inhibitory molecules were ranked according to their binding free energy change values for both enzymes. The information can be used for the in vivo anticancer studies.

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