title: Computationally focusing the directed evolution of proteins.
abstract: Directed evolution has proven to be a successful strategy for the modification of enzyme properties. To date, the preferred experimental procedure has been to apply mutations or crossovers randomly throughout the gene. With the emergence of powerful computational methods, it has become possible to develop focused combinatorial searches, guided by computer algorithms. Here, we describe several computational methods that have emerged to aid the optimization of mutant libraries, the targeting of specific residues for mutagenesis, and the design of recombination experiments.
authors.affiliation: Biochemistry and Molecular Biophysics, California Institute of Technology, Pasadena, California 91125, USA.
authors.forename: C A
authors.initials: CA
authors.lastname: Voigt
authors.forename: S L
authors.initials: SL
authors.lastname: Mayo
authors.forename: F H
authors.initials: FH
authors.lastname: Arnold
authors.forename: Z G
authors.initials: ZG
authors.lastname: Wang
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D004247:DNA; D019020:Directed Molecular Evolution / Q000379:methods*; D016296:Mutagenesis; D011506:Proteins / Q000235:genetics*; D011995:Recombination, Genetic
chemical_list: D011506:Proteins; D004247:DNA