Computer‐Aided Drug Discovery Approach Finds Calcium Sensitizer of Cardiac Troponin
Bibliographic record
Abstract
In the fight against heart failure, therapeutics that have the ability to increase the contractile power of the heart are urgently needed. One possible route of action to improve heart contractile power is increasing the calcium sensitivity of the thin filament. From a pharmaceutical standpoint, calcium sensitizers have the distinct advantage of not altering cardiomyocyte calcium levels and thus have lower potential for side-effects. Small chemical molecules have been shown to bind to the interface between cTnC and the cTnI switch peptide and exhibit calcium-sensitizing properties, possibly by stabilizing cTnC in an open conformation. Building on existing structural data of a known calcium sensitizer bound to cardiac troponin, we combined computational structure-based virtual screening drug discovery methods and solution NMR titration assays to identify a novel calcium sensitizer 4-(4-(2,5-dimethylphenyl)-1-piperazinyl)-3-pyridinamine (NSC147866) which binds to cTnC and the cTnC-cTnI147-163 complex. Its presence increases the affinity of switch peptide to cTnC by approximately a factor of two. This action is comparable to that of known levosimendan analogues.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".