Iterative saturation mutagenesis (ISM) is a new and efficient method for the directed evolution of functional enzymes. It reduces the necessary molecular biological work and the screening effort drastically. It is based on a Cartesian view of the protein structure, performing iterative cycles of saturation mutagenesis at rationally chosen sites in an enzyme, a given site being composed of one, two or three amino acid positions. The basis for choosing these sites depends on the nature of the catalytic property to be improved, e.g., enantioselectivity, substrate acceptance or thermostability. In the case of thermostability, sites showing highest B-factors (available from X-ray data) are chosen. The pronounced increase in thermostability of the lipase from Bacillus subtilis (Lip A) as a result of applying ISM is illustrated here.

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Our previous contribution to increasing the efficiency of directed evolution is iterative saturation mutagenesis (ISM) as a systematic means of generating focused libraries for the control of substrate acceptance, enantioselectivity, or thermostability of enzymes. We have now introduced a crucial element to knowledge-guided targeted mutagenesis in general that helps to solve the numbers problem in directed evolution. We show that the choice of the amino acid (aa) alphabet, as specified by the utilized codon degeneracy, provides the experimenter with a powerful tool in designing "smarter" randomized libraries that require considerably less screening effort. A systematic comparison of two different codon degeneracies was made by examining the relative quality of the identically sized enzyme libraries in relation to the degree of oversampling required in the screening process. The specific example in our case study concerns the conventional NNK codon degeneracy (32 codons/20 aa) versus NDT (12 codons/12 aa). The model reaction is the hydrolytic kinetic resolution of a chiral trans-disubstituted epoxide, catalyzed by the epoxide hydrolase from Aspergillus niger. The NDT library proves to be of much higher quality, as measured by the dramatically higher frequency of positive variants and by the magnitude of catalyst improvement (enhanced rate and enantioselectivity). We provide a statistical analysis that constitutes a useful guide for the optimal design and generation of "smarter" focused libraries. This type of approach accelerates the process of laboratory evolution considerably and can be expected to be broadly applicable when engineering functional proteins in general.

Enzymes as catalysts in synthetic organic chemistry gained importance in the latter half of the 20th century, but nevertheless suffered from two major limitations. First, many enzymes were not accessible in large enough quantities for practical applications. The advent of recombinant DNA technology changed this dramatically in the late 1970s. Second, many enzymes showed a narrow substrate scope, often poor stereo- and/or regioselectivity and/or insufficient stability under operating conditions. With the development of directed evolution beginning in the 1990s and continuing to the present day, all of these problems can be addressed and generally solved. The present Perspective focuses on these and other developments which have popularized enzymes as part of the toolkit of synthetic organic chemists and biotechnologists. Included is a discussion of the scope and limitation of cascade reactions using enzyme mixtures in vitro and of metabolic engineering of pathways in cells as factories for the production of simple compounds such as biofuels and complex natural products. Future trends and problems are also highlighted, as is the discussion concerning biocatalysis versus nonbiological catalysis in synthetic organic chemistry. This Perspective does not constitute a comprehensive review, and therefore the author apologizes to those researchers whose work is not specifically treated here.