Characterization of the SMTNL1‐tropomyosin binding interface using hydrogen‐deuterium exchange mass spectrometry
Bibliographic record
Abstract
The smoothelin‐like 1 protein (SMTNL1) modulates muscle contractile activity, particularly in exercise adaptation. SMTNL1 bears sequence similarity to smoothelin, a smooth muscle differentiation marker, particularly in its calponin homology (CH) domain. The interaction of SMTNL1 with tropomyosin (TM) is dependent on the CH domain and some portion of a central, unfolded region (aa 197–342) of SMTNL1. These data are based on pull‐down studies with SMTNL1 truncations, and reinforced by isothermal titration calorimetry experiments. We hypothesize that independent sections of the SMTNL1 protein cooperate to form a functional TM binding surface. We will elucidate the specific surfaces of SMTNL1 involved in TM binding using hydrogen‐deuterium exchange mass spectroscopy (HXMS). To this end, we have mapped pepsin‐derived mass fragments covering 94% of the SMTNL1‐CH domain, and 83% of a functional TM‐binding truncate (SMTNL1‐∆N, aa 196–459). These maps will be compared with deuterated SMTNL1 samples, and with SMTNL1 samples deuterated while bound to TM. The deuterium incorporated is calculated for each SMTNL1 peptide to reveal the interaction interface. The objectives will address the molecular and structural elements of the SMTNL1‐TM interaction and provide a framework for the physiological role of SMTNL1 in vascular smooth muscle biology. The research was supported by HSFC and CIHR.
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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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".