Massachusetts Institute of Technology, Department of Chemistry, Cambridge 02139.
We have developed a generally applicable experimental procedure to find functional
proteins that are many mutational steps from wild type. Optimization algorithms, which are
typically used to search for solutions to certain combinatorial problems, have been
adapted to the problem of searching the 'sequence space' of proteins. Many of the steps
normally performed by a digital computer are embodied in this new molecular genetics
technique, termed recursive ensemble mutagenesis (REM). REM uses information gained from
previous iterations of combinatorial cassette mutagenesis (CCM) to search sequence space
more efficiently. We have used REM to simultaneously mutate six amino acid residues in a
model protein. As compared to conventional CCM, one iteration of REM yielded a 30-fold
increase in the frequency of 'positive' mutants. Since a multiplicative factor of similar
magnitude is expected for the mutagenesis of additional sets of six residues, performing
REM on 18 sites is expected to yield an exponential (30,000-fold) increase in the
throughput of positive mutants as compared to random [NN(G,C)]18 mutagenesis.