Biocatalysts by evolution

Proteins evolve by iterative cycles of mutation, selection and amplification. Analogous evolutionary strategies are being profitably exploited in the laboratory to generate and optimize biocatalysts for diverse biotechnological applications. In this review, we summarize recent efforts to improve this process by creating more effective protein libraries and more efficient screening/selection schemes. Targeted mutagenesis using simplified amino acid alphabets, statistical analyses of sequence-function-stability relationships, and neutral mutational drift have emerged as powerful tools for generating useful molecular diversity, while new techniques for controlling selection stringency and microfluidic methods for screening large populations of molecules promise to facilitate exploration of sequence space. Enzyme engineers interested in creating novel biocatalysts for abiological reactions are sure to profit from these advances.