The Binding of W7, an Inhibitor of Striated Muscle Contraction, to Cardiac Troponin C
Bibliographic record
Abstract
W7 is a well-characterized calmodulin antagonist. It decreases the maximal tension and rate of ATP hydrolysis in cardiac muscle fibers. Cardiac troponin C (cTnC) has been previously implicated as the mechanistically significant target for W7 in the myofilament. Two-dimensional NMR spectra ({1H,15N}- and {1H,13C}-HSQCs) were used to monitor the Ca2+-dependent binding of W7 to cTnC. Titration of cTnC x 3Ca2+ with W7 indicated binding to both domains of the protein. We examined the binding of W7 to the separated domains of cTnC to simplify the spectral analysis. In the titration of the C-terminal domain (cCTnC x 2Ca2+), the spectral peaks originating from a subset of residues changed nonuniformly, and could not be well-described as single-site binding. A global fit of the cCTnC x 2Ca2+ titration data to a two-site, sequential binding model (47 residues simultaneously fit) yielded a dissociation constant (Kd1) of 0.85-0.91 mM for the singly bound state, with the second dissociation constant fit to 3.40-3.65 mM (> or = 4 x Kd1). The titration data for the N-terminal domain (cNTnC x Ca2+) was globally fit to single-site binding model with a Kd of 0.15-0.30 mM (41 residues fit). The data are consistent with W7 binding to each domain's major hydrophobic pocket, coordinating side chains responsible for liganding cTnI. When in muscle fibers, W7 may compete with cTnI for target sites on cTnC.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".