Correlation of Secondary Structures Of Bradykinin B1 Receptor Antagonists with Their Activity
Bibliographic record
Abstract
The secondary structure of a bradykinin B(1)receptor antagonist B-10324 (F5C-Lys-(1)- Lys(0)-Arg(1)-Pro(2)- Hyp(3)-Gly(4)-CpG(5)- Ser(6)-DTic(7)-CpG(8)) was determined by NMR at 800MHz. The conformational data are compared with those obtained previously for two bradykinin B(1) receptor antagonists, namely B-9858 (Lys-(1)- Lys(0)-Arg(1)-Pro(2)- Hyp(3)-Gly(4)-Igl(5)- Ser(6)-DIgl(7)-Oic(8)) and B-10148 (Lys-(1)-Lys(0)-Arg(1)- Pro(2)-Hyp(3)-Gly(4)- Igl(5)-Ser(6)-DF5F(7)- Oic(8)). The abnormal amino acids are: Hyp, trans-4- hydroxyproline; Tic, 1, 2, 3, 4-tetrahydroisoquinoline-3-carboxylic acid; Oic, (2S, 3aS, 7aS)-octahydroindole-2-carboxylic acid; Igl, alpha(2- indanyl)glycine; F5F, 2,3,4,5,6-pentafluorophenylalanine; CpG, alpha- cyclopentylglycine. F5C, pentafluorocinnamoyl, is the N-terminal protecting group and is not involved in the peptide secondary structure. B-10324 contains an N-terminal Pro(2)- CpG(5) distorted type II beta-turn whereas the rest of the peptide is random. A salt bridge is not observed between the carboxylate group at the C-terminal end and the Arg(1) side chain, in contrast to that previously observed for B-9858 and B- 10148. The conformations are correlated with the measured B(1) receptor antagonist activities (J.-F. Larrivée, L. Gera, S. Houle, J. Bouthillier, D. R. Bachvarov, J. M. Stewart and F. Marc au, Br. J. Pharmacol. 131, 885-892 (2000)). The importance of the N-terminal beta-turn is highlighted.
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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 | 0.000 |
| 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 | 0.001 |
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".