ABSTRACT
This chapter summarizes research activities by the Maranas group (https://fenske.che.psu.edu/faculty/cmaranas/) toward modeling the statistics of combinatorial DNA libraries generated through directed evolution methods. Directed evolution methods utilize the process of natural selection to combinatorially evolve enzymes, proteins, or even entire metabolic pathways with improved properties. These methods typically begin with the infusion of diversity into a small set of parental nucleotide sequences through DNA recombination and/or mutagenesis. The resulting combinatorial DNA library is then subjected to a high-throughput selection or screening procedure, and the most improved variants are isolated for another round of recombination or mutagenesis. The cycles of recombination/mutagenesis, screening, and isolation continue until a protein or enzyme with the desired level of improvement is found. In the last few years, remarkable success stories of directed evolution have been reported (1-3), ranging from manifold improvements in enzyme activity and thermostability (4), enhanced bioreme-diation (5-8), and design of vaccines (9-11), to viral vectors for gene delivery (12, 13).
