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 approximately 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.

The development of a green-by-design, two-step, three-enzyme process for the synthesis of a key intermediate in the manufacture of atorvastatin, the active ingredient of the cholesterol lowering drug Lipitor R , is described. The first step involves the biocatalytic reduction of ethyl-4-chloroacetoacetate using a ketoreductase (KRED) in combination with glucose and a NADP-dependent glucose dehydrogenase (GDH) for cofactor regeneration. The (S) ethyl-4-chloro-3-hydroxybutyrate product is obtained in 96% isolated yield and >99.5% e.e. In the second step, a halohydrin dehalogenase (HHDH) is employed to catalyse the replacement of the chloro substituent with cyano by reaction with HCN at neutral pH and ambient temperature. The natural enzymes were highly selective but exhibited productivities that were insufficient for large scale application. Consequently, in vitro enzyme evolution using gene shuffling technologies was employed to optimise their performance according to predefined criteria and process parameters. In the case of the HHDH reaction, this afforded a 2500-fold improvement in the volumetric productivity per biocatalyst loading. This enabled the economical and environmentally attractive production of the key hydroxynitrile intermediate. The overall process has an E factor (kg waste per kg product) of 5.8 when process water is not included, and 18 if included.

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