Development of Clinically Viable Non-Muscle Myosin II Small Molecule Inhibitors with Broad Therapeutic Potential
Bibliographic record
Abstract
ABSTRACT Non-muscle myosin II (NMII), a molecular motor that regulates critical processes such as cytokinesis and neuronal synaptic plasticity, has substantial therapeutic potential. However, translating this potential to in vivo use has been hampered by the lack of selective tools. The most prototypical non-selective inhibitor, blebbistatin inactivates both NMII and cardiac myosin II (CMII), a key regulator of heart function. Using rational drug design, we developed a series of NMII inhibitors that improve tolerability by selectively targeting NMII over CMII, including MT-228, which has excellent properties such as high brain penetration and efficacy in preclinical models of stimulant use disorder, which has no current FDA-approved therapies. The structure of MT-228 bound to myosin II provides insight into its 17-fold selectivity for NMII over CMII. MT-228’s broad therapeutic window opens the door to new disease treatments and provides valuable tools for the scientific community, along with promising leads for future medication development. Highlights Research suggests numerous indications, from axon regeneration and cancer, would benefit from a small molecule inhibitor of non-muscle myosin II, a molecular motor that regulates the actin cytoskeleton. Current chemical probe options are very limited and lack sufficient safety for in vivo studies, which we show is primarily due to potent inhibition of cardiac myosin II. Rational design that focused on improving target selectivity over the pan-myosin II inhibitor, blebbistatin, led to the identification of MT-228, a small molecule inhibitor with a wide therapeutic window. High-resolution structure of MT-228 bound to myosin II reveals that selectivity results from a different positioning compared to blebbistatin and an important sequence difference between cardiac and non-muscle myosin II in the inhibitor binding pocket. A single administration of MT-228 shows long-lasting efficacy in animal models of stimulant use disorder, a current unmet and rapidly escalating need with no FDA-approved treatments.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".