Structural Elements of Dwarf Open Reading Frame Required for Activation of the Sarco-Endoplasmic Reticulum Calcium Pump
Bibliographic record
Abstract
Abstract The sarco-endoplasmic reticulum calcium pump (SERCA) is a P-type ATPase that plays a critical role in intracellular calcium signaling. SERCA maintains the calcium gradient between the cytosol and the sarco-endoplasmic reticulum, which is essential for a variety of physiological events including the muscle contraction-relaxation cycle. In cardiac muscle, SERCA is regulated by transmembrane peptides phospholamban (PLN) and dwarf open reading frame (DWORF). These peptides encode the opposing functions of SERCA inhibition by PLN and SERCA activation by DWORF, though the underlying mechanisms remain unclear. Herein, we investigated structural elements of DWORF expected to play a role in SERCA activation. We first measured SERCA activity in the absence and presence of DWORF variants targeting Leu12 and Pro15. These residues were selected based on sequence alignment with PLN. Leu12 and Pro15 of DWORF align with the essential residues Leu31 and Asn34 of PLN, which are required for SERCA inhibition. We found that both residues are required for SERCA activation by DWORF and that substitution of Pro15 (to Ala, Asn, or Leu) resulted in potent inhibition of SERCA. We next investigated the roles of Gly21, Ile23, and Gly25 in SERCA activation and DWORF oligomerization. These residues are part of a common helix interaction motif, GxxxG (Gly21-Trp-Ile-Val-Gly25) found in DWORF, which is unique among the regulins. The data suggest that the GxxxG motif does not play a role in DWORF oligomerization. Instead, this motif appears to interact with SERCA and provides a smooth interface that promotes activation and avoids inhibitory interactions with SERCA.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".