Structural Determinants for Activity of Glucagon-like Peptide-2
Bibliographic record
Abstract
Glucagon-like peptide-2 (GLP-2) is a 33 amino acid gastrointestinal hormone that regulates epithelial growth in the intestine. Dipeptidylpeptidase IV cleaves GLP-2 at the position 2 alanine, resulting in the inactivation of peptide activity. To understand the structural basis for GLP-2 action, we studied receptor binding and activation for 56 GLP-2 analogues with either position 2 substitutions or alanine replacements along the length of the peptide. The majority of position 2 substitutions exhibited normal to enhanced GLP-2 receptor (GLP-2R) binding; in contrast, position 2 substitutions were less well tolerated in studies of receptor activation as only Gly, Ile, Pro, alpha-aminobutyric acid, D-Ala, or nor-Val substitutions exhibited enhanced GLP-2R activation. In contrast, alanine replacement at positions 5,6,17, 20, 22, 23, 25, 26, 30, and 31 led to diminished GLP-2R binding. Position 2 substitutions containing Asp, Leu, Lys, Met, Phe, Trp, and Tyr, and Ala substitutions at positions 12 and 21 exhibited normal to enhanced GLP-2R binding but greater than 75% reduction in receptor activation. D-Ala(2), Pro(2) and Gly(2), Ala(16) exhibited significantly lower EC(50)s for receptor activation than the parent peptide (p < 0.01-0.001). Circular dichroism analysis indicated that the enhanced activity of these GLP-2 analogues was independent of the alpha-helical content of the peptide. These results indicate that single amino acid substitutions within GLP-2 can confer structural changes to the ligand-receptor interface, allowing the identification of residues important for GLP-2R binding and receptor activation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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".