Drug specificity and affinity are encoded in the probability of cryptic pocket opening in myosin motor domains

  1. Artur Meller
  2. Jeffrey M. Lotthammer
  3. Louis G Smith
  4. Borna Novak
  5. Lindsey A Lee
  6. Catherine C Kuhn
  7. Lina Greenberg
  8. Leslie A Leinwand
  9. Michael J Greenberg
  10. Gregory R Bowman  Is a corresponding author
  1. Washington University in St. Louis, United States
  2. University of Pennsylvania, United States
  3. University of Colorado Boulder, United States

Abstract

The design of compounds that can discriminate between closely related target proteins remains a central challenge in drug discovery. Specific therapeutics targeting the highly conserved myosin motor family are urgently needed as mutations in at least 6 of its members cause numerous diseases. Allosteric modulators, like the myosin-II inhibitor blebbistatin, are a promising means to achieve specificity. However, it remains unclear why blebbistatin inhibits myosin-II motors with different potencies given that it binds at a highly conserved pocket that is always closed in blebbistatin-free experimental structures. We hypothesized that the probability of pocket opening is an important determinant of the potency of compounds like blebbistatin. To test this hypothesis, we used Markov state models (MSMs) built from over 2 milliseconds of aggregate molecular dynamics simulations with explicit solvent. We find that blebbistatin’s binding pocket readily opens in simulations of blebbistatin-sensitive myosin isoforms. Comparing these conformational ensembles reveals that the probability of pocket opening correctly identifies which isoforms are most sensitive to blebbistatin inhibition and that docking against MSMs quantitatively predicts blebbistatin binding affinities (R2=0.82). In a blind prediction for an isoform (Myh7b) whose blebbistatin sensitivity was unknown, we find good agreement between predicted and measured IC50s (0.67 mM vs. 0.36 mM). Therefore, we expect this framework to be useful for the development of novel specific drugs across numerous protein targets.

Data availability

Experimental, pocket volume, docking, and trajectory clustering data have been deposited in OSF under accession code CV6D2. Scripts and notebooks used to generate all figures are available in our GitHub repository (https://github.com/bowman-lab/blebbistatin-specificity).

The following data sets were generated
The following previously published data sets were used

Article and author information

Author details

  1. Artur Meller

    Department of Biochemistry and Molecular Biophysics, Washington University in St. Louis, St Louis, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5504-2684
  2. Jeffrey M. Lotthammer

    Department of Biochemistry and Molecular Biophysics, Washington University in St. Louis, St Louis, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Louis G Smith

    Department of Biochemistry and Biophysics, University of Pennsylvania, Philadelphia, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Borna Novak

    Department of Biochemistry and Molecular Biophysics, Washington University in St. Louis, St. Louis, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Lindsey A Lee

    Department of Molecular, Cellular, and Developmental Biology, University of Colorado Boulder, Boulder, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Catherine C Kuhn

    Department of Biochemistry and Molecular Biophysics, Washington University in St. Louis, St. Louis, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Lina Greenberg

    Department of Biochemistry and Molecular Biophysics, Washington University in St. Louis, St Louis, United States
    Competing interests
    The authors declare that no competing interests exist.
  8. Leslie A Leinwand

    Department of Molecular, Cellular, and Developmental Biology, University of Colorado Boulder, Boulder, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1470-4810
  9. Michael J Greenberg

    Department of Biochemistry and Molecular Biophysics, Washington University in St. Louis, St Louis, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1320-3547
  10. Gregory R Bowman

    Department of Biochemistry and Biophysics, University of Pennsylvania, Philadelphia, United States
    For correspondence
    grbowman@seas.upenn.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2083-4892

Funding

National Institutes of Health (1F30HL162431-01A1)

  • Artur Meller

National Institutes of Health (R01 GM124007)

  • Gregory R Bowman

National Institutes of Health (RF1AG067194)

  • Gregory R Bowman

National Institutes of Health (R01 HL141086)

  • Michael J Greenberg

National Institutes of Health (GM 20909)

  • Leslie A Leinwand

National Science Foundation (DGE2139839)

  • Jeffrey M. Lotthammer

National Science Foundation (MCB-1552471)

  • Gregory R Bowman

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

Copyright

© 2023, Meller 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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  1. Artur Meller
  2. Jeffrey M. Lotthammer
  3. Louis G Smith
  4. Borna Novak
  5. Lindsey A Lee
  6. Catherine C Kuhn
  7. Lina Greenberg
  8. Leslie A Leinwand
  9. Michael J Greenberg
  10. Gregory R Bowman
(2023)
Drug specificity and affinity are encoded in the probability of cryptic pocket opening in myosin motor domains
eLife 12:e83602.
https://doi.org/10.7554/eLife.83602

Share this article

https://doi.org/10.7554/eLife.83602

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