Searching sequence space to engineer proteins: exponential ensemble mutagenesis.

Abstract

We describe an efficient method for generating combinatorial libraries with a high percentage of unique and functional mutants. Combinatorial libraries have been successfully used in the past to express ensembles of mutant proteins in which all possible amino acids are encoded at a few positions in the sequence. However, as more positions are mutagenized the proportion of functional mutants is expected to decrease exponentially. Small groups of residues were randomized in parallel to identify, at each altered position, amino acids which lead to functional proteins. By using optimized nucleotide mixtures deduced from the sequences selected from the random libraries, we have simultaneously altered 16 sites in a model pigment binding protein: approximately one percent of the observed mutants were functional. Mathematical formalization and extrapolation of our experimental data suggests that a 10(7)-fold increase in the throughput of functional mutants has been obtained relative to the expected frequency from a random combinatorial library. Exponential ensemble mutagenesis should be advantageous in cases where many residues must be changed simultaneously to achieve a specific engineering goal, as in the combinatorial mutagenesis of phage displayed antibodies. With the enhanced functional mutant frequencies obtained by this method, entire proteins could be mutagenized combinatorially.