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  • Title: An ensemble of theta class glutathione transferases with novel catalytic properties generated by stochastic recombination of fragments of two mammalian enzymes.
    Author: Broo K, Larsson AK, Jemth P, Mannervik B.
    Journal: J Mol Biol; 2002 Apr 19; 318(1):59-70. PubMed ID: 12054768.
    Abstract:
    The correlation between sequence diversity and enzymatic function was studied in a library of Theta class glutathione transferases (GSTs) obtained by stochastic recombination of fragments of cDNA encoding human GST T1-1 and rat GST T2-2. In all, 94 randomly picked clones were characterized with respect to sequence, expression level, and catalytic activity in the conjugation reactions between glutathione and six alternative electrophilic substrates. Out of these six different compounds, dichloromethane is a selective substrate for human GST T1-1, whereas 1-menaphthyl sulfate and 1-chloro-2,4-dinitrobenzene are substrates for rat GST T2-2. The other three substances serve as substrates for both enzymes. Through this broad characterization, we have identified enzyme variants that have acquired novel activity profiles that differ substantially from those of the original GSTs. In addition, the expression levels of many clones were improved in comparison to the parental enzyme. A library of mutants can thus display a distribution of properties from which highly divergent evolutionary pathways may emerge, resembling natural evolutionary processes. From the GST library, a clone was identified that, by the point mutation N49D in the rat GST T2-2 sequence, has a 1700% increased activity with 1-menaphthyl sulfate and a 60% decreased activity with 4-nitrophenethyl bromide. Through the N49D mutation, the ratio of these activities has thus been altered 40-fold. An extensive characterization of a population of stochastically mutated enzymes can accordingly be used to find variants with novel substrate-activity profiles and altered catalytic properties. Recursive recombination of selected sequences displaying optimized properties is a strategy for the engineering of proteins for medical and biochemical applications. Such sequential design is combinatorial protein chemistry based on remodeling of existing structural scaffolds and has similarities to evolutionary processes in nature.
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