Molecular Modeling of Benzothiazepine Binding in the L-type Calcium Channel
Bibliographic record
Abstract
Benz(othi)azepine (BTZ) derivatives constitute one of three major classes of L-type Ca(2+) channel ligands. Despite intensive experimental studies, no three-dimensional model of BTZ binding is available. Here we have built KvAP- and KcsA-based models of the Ca(v)1.2 pore domain in the open and closed states and used multiple Monte Carlo minimizations to dock representative ligands. In our open channel model, key functional groups of BTZs interact with BTZ-sensing residues, which were identified in previous mutational experiments. The bulky tricyclic moiety occupies interface between domains III and IV, while the ammonium group protrudes into the inner pore, where it is stabilized by nucleophilic C-ends of the pore helices. In the closed channel model, contacts with several ligand-sensing residues in the inner helices are lost, which weakens ligand-channel interactions. An important feature of the ligand-binding mode in both open and closed channels is an interaction between the BTZ carbonyl group and a Ca(2+) ion chelated by the selectivity filter glutamates in domains III and IV. In the absence of Ca(2+), the tricyclic BTZ moiety remains in the domain interface, while the ammonium group directly interacts with a glutamate residue in the selectivity filter. Our model suggests that the Ca(2+) potentiation involves a direct electrostatic interaction between aCa(2+) ion and the ligand rather than an allosteric mechanism. Energy profiles indicate that BTZs can reach the binding site from the domain interface, whereas access through the open activation gate is unlikely, because reorientation of the bulky molecule in the pore is hindered.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".