Library analysis of SCHEMA-guided protein recombination

Authors

  • Michelle M. Meyer,

    1. Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California 91125, USA
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    • These authors contributed equally to this work.

  • Jonathan J. Silberg,

    1. Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California 91125, USA
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    • These authors contributed equally to this work.

  • Christopher A. Voigt,

    1. Department of Bioengineering, University of California, Berkeley, California 94720, USA
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  • Jeffrey B. Endelman,

    1. Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California 91125, USA
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  • Stephen L. Mayo,

    1. Howard Hughes Medical Institute and Division of Biology, California Institute of Technology, Pasadena, California 91125, USA
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  • Zhen-Gang Wang,

    1. Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California 91125, USA
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  • Frances H. Arnold

    Corresponding author
    1. Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California 91125, USA
    • Division of Chemistry and Chemical Engineering, California Institute of Technology, mail code 210-41, Pasadena, CA 91125, USA; fax: (626) 568-8743.
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Abstract

The computational algorithm SCHEMA was developed to estimate the disruption caused when amino acid residues that interact in the three-dimensional structure of a protein are inherited from different parents upon recombination. To evaluate how well SCHEMA predicts disruption, we have shuffled the distantly-related β-lactamases PSE-4 and TEM-1 at 13 sites to create a library of 214 (16,384) chimeras and examined which ones retain lactamase function. Sequencing the genes from ampicillin-selected clones revealed that the percentage of functional clones decreased exponentially with increasing calculated disruption (E = the number of residue–residue contacts that are broken upon recombination). We also found that chimeras with low E have a higher probability of maintaining lactamase function than chimeras with the same effective level of mutation but chosen at random from the library. Thus, the simple distance metric used by SCHEMA to identify interactions and compute E allows one to predict which chimera sequences are most likely to retain their function. This approach can be used to evaluate crossover sites for recombination and to create highly mosaic, folded chimeras.

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