Cryo-electron microscopy reveals sequential binding and activation of Ryanodine Receptors by statin triplets
Bibliographic record
Abstract
Statins are the most prescribed class of drugs and inhibit a key enzyme in the cholesterol biosynthesis pathway. Many patients have reported mild to severe muscle related symptoms and a subset are at risk for rhabdomyolysis. Sequence variants in RyR1, the skeletal muscle Ryanodine Receptor, correlate with intolerance to statins, but whether RyR1 can bind statins directly has remained unclear. Here we report cryo-EM structures of RyR1 in the absence and presence of atorvastatin, firmly establishing RyR1 as an unintended off-target. Our results show an unusual binding mode whereby three atorvastatin molecules bind together in a cleft formed by the pseudo-voltage sensing domain, making extensive interactions with each other and with RyR1. Atorvastatin activates RyR1 in a sequential way, whereby one statin per subunit can bind to the transmembrane region of a closed RyR1, with small structural perturbations that prime the channel for opening. Binding of two additional statins per subunit is associated with a widening of the pseudo-voltage sensing domain that triggers opening of the pore. Comparison with atorvastatin binding to HMG-CoA reductase, its intended target, offers clues on how to modify the statin to reduce RyR1 binding, while leaving binding to HMG-CoA reductase unperturbed. Statins lower blood plasma cholesterol but can cause muscle-related issues including life-threatening rhabdomyolysis. Here the authors show that atorvastatin binds as triplets to the skeletal muscle Ryanodine Receptor transmembrane region, triggering opening of this calcium release channel.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".