Journal of Cellular Biochemistry

Computationally focusing the directed evolution of proteins

Authors

  • Christopher A. Voigt,

    Corresponding author
    1. Biochemistry and Molecular Biophysics, California Institute of Technology, Pasadena, California
    • Biochemistry and Molecular Biophysics, California Institute of Technology, Mail code 210-41, Pasadena, CA, 91125.
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  • Stephen L. Mayo,

    1. Howard Hughes Medical Institute and Division of Biology, California Institute of Technology, Pasadena, California
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  • Frances H. Arnold,

    1. Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California
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  • Zhen-Gang Wang

    1. Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California
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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. J. Cell. Biochem. Suppl. 37: 58–63, 2001. © 2002 Wiley-Liss, Inc.

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