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Computationally designed libraries of fluorescent proteins evaluated by preservation and diversity of function

  1. Thomas P. Treynor * , † ,
  2. Christina L. Vizcarra ‡ ,
  3. Daniel Nedelcu *, and
  4. Stephen L. Mayo * , † , §
  1. Divisions of *Biology and Chemistry and
  2. ‡Chemical Engineering and
  3. †Howard Hughes Medical Institute, California Institute of Technology, 1200 East California Boulevard, Pasadena, CA 91125

  1. Contributed by Stephen L. Mayo, October 31, 2006 (received for review August 11, 2006)

Abstract

To determine which of seven library design algorithms best introduces new protein function without destroying it altogether, seven combinatorial libraries of green fluorescent protein variants were designed and synthesized. Each was evaluated by distributions of emission intensity and color compiled from measurements made in vivo. Additional comparisons were made with a library constructed by error-prone PCR. Among the designed libraries, fluorescent function was preserved for the greatest fraction of samples in a library designed by using a structure-based computational method developed and described here. A trend was observed toward greater diversity of color in designed libraries that better preserved fluorescence. Contrary to trends observed among libraries constructed by error-prone PCR, preservation of function was observed to increase with a library's average mutation level among the four libraries designed with structure-based computational methods.

Footnotes

  • §To whom correspondence should be addressed. E-mail: steve{at}mayo.caltech.edu

  • Author contributions: T.P.T. and S.L.M. designed research; T.P.T., C.L.V., and D.N. performed research; T.P.T. contributed new reagents/analytic tools; T.P.T. and C.L.V. analyzed data; and T.P.T. wrote the paper.

  • The authors declare no conflict of interest.

  • This article contains supporting information online at www.pnas.org/cgi/content/full/0609647103/DC1.

  • Abbreviations:
    DBIS,
    diversity benefit applied to interacting sets;
    epPCR,
    error-prone PCR;
    MSA,
    multiple sequence alignment;
    SCMF,
    self-consistent mean-field;
    SE,
    site entropy.

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