Synthetic Peptides as Therapeutic Agents: Lessons Learned From Evolutionary Ancient Peptides and Their Transit Across Blood-Brain Barriers
Bibliographic record
Abstract
Peptides play a major role in the transmission of information to and from the central nervous system. However, because of their structural complexity, the development of pharmacological peptide-based therapeutics has been challenged by the lack of understanding of endogenous peptide evolution. The teneurin C-terminal associated peptides (TCAP) possess many of the required attributes of a practical peptide therapeutic. TCAPs, associated with the teneurin transmembrane proteins that bind to the latrophilins, members of the Adhesion family of G-protein-coupled receptors (GPCR). Together, this ligand-receptor unit plays an integral role in synaptogenesis, neurological development, and maintenance, and is present in most metazoans. TCAP has structural similarity to corticotropin-releasing factor (CRF), and related peptides, such as calcitonin and the secretin-based peptides and inhibits the (CRF)-associated stress response. Latrophilins are structurally related to the secretin family of GPCRs. TCAP is a soluble peptide that crosses the blood-brain barrier and regulates glucose transport into the brain. We posit that TCAP represents a phylogenetically older peptide system that evolved before the origin of the CRF-calcitonin-secretin clade of peptides and plays a fundamental role in the regulation of cell-to-cell energy homeostasis. Moreover, it may act as a phylogenetically older peptide system that evolved as a natural antagonist to the CRF-mediated stress response. Thus, TCAP's actions on the CNS may provide new insights into the development of peptide therapeutics for the treatment of CNS disorders.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| 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".