Improving catalytic function by ProSAR-driven enzyme evolution

Fox, Richard J; Davis, S Christopher; Mundorff, Emily C; Newman, Lisa M; Gavrilovic, Vesna; Ma, Steven K; Chung, Loleta M; Ching, Charlene; Tam, Sarena; Muley, Sheela; Grate, John; Gruber, John; Whitman, John C; Sheldon, Roger A; Huisman, Gjalt W
March 2007
Nature Biotechnology;Mar2007, Vol. 25 Issue 3, p338
Academic Journal
We describe a directed evolution approach that should find broad application in generating enzymes that meet predefined process-design criteria. It augments recombination-based directed evolution by incorporating a strategy for statistical analysis of protein sequence activity relationships (ProSAR). This combination facilitates mutation-oriented enzyme optimization by permitting the capture of additional information contained in the sequence-activity data. The method thus enables identification of beneficial mutations even in variants with reduced function. We use this hybrid approach to evolve a bacterial halohydrin dehalogenase that improves the volumetric productivity of a cyanation process ~4,000-fold. This improvement was required to meet the practical design criteria for a commercially relevant biocatalytic process involved in the synthesis of a cholesterol-lowering drug, atorvastatin (Lipitor), and was obtained by variants that had at least 35 mutations.


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