G protein–coupled receptor modulation with pepducins: moving closer to the clinic
Bibliographic record
Abstract
At the 2nd Pepducin Science Symposium held in Cambridge, Massachusetts, on November 4-5, 2010, investigators working in G protein-coupled receptor (GPCR) research convened to discuss progress since last year's inaugural conference. This year's symposium focused on increasing knowledge of the structure and function of this ubiquitous superfamily of membrane receptors and their potential modulation for disease treatment. Presentations also focused on how GPCR mechanisms might be exploited to treat diseases with pepducins, novel synthetic lipopeptide pharmacophores that modulate heptahelical GPCR activity. While the multiple roles of GPCRs in physiological and pathophysiological processes offer significant opportunities for novel drug development, the global nature of their activity challenges drug-specific and validated target identification. This year's conference highlighted advances in understanding of GPCR agonist and antagonist ligand-binding motifs, their ligand-independent functions, structure-activity relationships (SARs), and evolving unique methods to probe GPCR structure and function. Study results summarized at the meeting also provided evidence for evolving views of how signaling mechanisms work through these receptors.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".