Drug specificity and affinity are encoded in the probability of cryptic pocket opening in myosin motor domains
- Washington University in St. Louis, United States
- University of Pennsylvania, United States
- 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).
Article and author information
Author details
Michael J Greenberg
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.
Reviewing Editor
- Donald Hamelberg, Georgia State University, United States
Version history
- Preprint posted: September 5, 2022 (view preprint)
- Received: September 21, 2022
- Accepted: January 23, 2023
- Accepted Manuscript published: January 27, 2023 (version 1)
- Version of Record published: March 8, 2023 (version 2)
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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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
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