Structurally distributed surface sites tune allosteric regulation

  1. James W McCormick
  2. Marielle AX Russo
  3. Samuel Thompson
  4. Aubrie Blevins
  5. Kimberly A Reynolds  Is a corresponding author
  1. University of Texas Southwestern Medical Center, United States
  2. Stanford University, United States

Abstract

Our ability to rationally optimize allosteric regulation is limited by incomplete knowledge of the mutations that tune allostery. Are these mutations few or abundant, structurally localized or distributed? To examine this, we conducted saturation mutagenesis of a synthetic allosteric switch in which Dihydrofolate reductase (DHFR) is regulated by a blue-light sensitive LOV2 domain. Using a high-throughput assay wherein DHFR catalytic activity is coupled to E. coli growth, we assessed the impact of 1548 viable DHFR single mutations on allostery. Despite most mutations being deleterious to activity, fewer than 5% of mutations had a statistically significant influence on allostery. Most allostery disrupting mutations were proximal to the LOV2 insertion site. In contrast, allostery enhancing mutations were structurally distributed and enriched on the protein surface. Combining several allostery enhancing mutations yielded near-additive improvements to dynamic range. Our results indicate a path towards optimizing allosteric function through variation at surface sites.

Data availability

Sequencing data (resulting from amplicon sequencing) have been deposited in the NCBI SRA under BioProject: PRJNA706683All analysis codes have been made available as a series of python 3 Jupyter Notebooks on github: https://github.com/reynoldsk/allostery-in-dhfr

The following data sets were generated

Article and author information

Author details

  1. James W McCormick

    The Green Center for Systems Biology and Department of Biophysics, University of Texas Southwestern Medical Center, Dallas, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7573-2300
  2. Marielle AX Russo

    The Green Center for Systems Biology and Department of Biophysics, University of Texas Southwestern Medical Center, Dallas, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Samuel Thompson

    Department of Bioengineering, Stanford University, Stanford, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Aubrie Blevins

    The Green Center for Systems Biology, University of Texas Southwestern Medical Center, Dallas, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Kimberly A Reynolds

    The Green Center for Systems Biology and Department of Biophysics, University of Texas Southwestern Medical Center, Dallas, United States
    For correspondence
    kimberly.reynolds@utsouthwestern.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4805-0317

Funding

National Science Foundation (CAREER Award,1942354)

  • Kimberly A Reynolds

Gordon and Betty Moore Foundation (Data Driven Discovery Initiative,GBMF4557)

  • Kimberly A Reynolds

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

© 2021, McCormick et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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https://doi.org/10.7554/eLife.68346

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