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  • Title: Computational design of glutamate dehydrogenase in Bacillus subtilis natto.
    Author: Chen LL, Wang JL, Hu Y, Qian BJ, Yao XM, Wang JF, Zhang JH.
    Journal: J Mol Model; 2013 Apr; 19(4):1919-27. PubMed ID: 23338837.
    Abstract:
    Bacillus subtilis natto is widely used in industry to produce natto, a traditional and popular Japanese soybean food. However, during its secondary fermentation, high amounts of ammonia are released to give a negative influence on the flavor of natto. Glutamate dehydrogenase (GDH) is a key enzyme for the ammonia produced and released, because it catalyzes the oxidative deamination of glutamate to alpha-ketoglutarate using NAD(+) or NADP(+) as co-factor during carbon and nitrogen metabolism processes. To solve this problem, we employed multiple computational methods model and re-design GDH from Bacillus subtilis natto. Firstly, a structure model of GDH with cofactor NADP(+) was constructed by threading and ab initio modeling. Then the substrate glutamate were flexibly docked into the structure model to form the substrate-binding mode. According to the structural analysis of the substrate-binding mode, Lys80, Lys116, Arg196, Thr200, and Ser351 in the active site were found could form a significant hydrogen bonding network with the substrate, which was thought to play a crucial role in the substrate recognition and position. Thus, these residues were then mutated into other amino acids, and the substrate binding affinities for each mutant were calculated. Finally, three single mutants (K80A, K116Q, and S351A) were found to have significant decrease in the substrate binding affinities, which was further supported by our biochemical experiments.
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