60 YEARS OF POMC: From the prohormone theory to pro-opiomelanocortin and to proprotein convertases (PCSK1 to PCSK9)
Bibliographic record
Abstract
Pro-opiomelanocortin (POMC), is a polyprotein expressed in the pituitary and the brain where it is proteolytically processed into peptide hormones and neuropeptides with distinct biological activities. It is the prototype of multipotent prohormones. The prohormone theory was first suggested in 1967 when Chrétien and Li discovered γ-lipotropin and observed that (i) it was part of β-lipotropin (β-LPH), a larger polypeptide characterized 2 years earlier and (ii) its C-terminus was β-melanocyte-stimulating hormone (β-MSH). This discovery led them to propose that the lipotropins might be related biosynthetically to the biologically active β-MSH in a precursor to end product relationship. The theory was widely confirmed in subsequent years. As we celebrate the 50th anniversary of the sequencing of β-LPH, we reflect over the lessons learned from the sequencing of those proteins; we explain their extension to the larger POMC precursor; we examine how the theory of precursor endoproteolysis they inspired became relevant for vast fields in biology; and how it led, after a long and arduous search, to the novel proteolytic enzymes called proprotein convertases. This family of nine enzymes plays multifaceted functions in growth, development, metabolism, endocrine, and brain functions. Their genetics has provided many insights into health and disease. Their therapeutic targeting is foreseeable in the near future. Thus, what started five decades ago as a theory based on POMC fragments, has opened up novel and productive avenues of biological and medical research, including, for our own current interest, a highly intriguing hypocholesterolemic Gln152His PCSK9 mutation in French-Canadian families.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".