Barley Serine Proteinase Inhibitor 2-Derived Cyclic Peptides as Potent and Selective Inhibitors of Convertases PC1/3 and Furin
Bibliographic record
Abstract
Proprotein convertases (PCs) are serine proteases containing a subtilisin-like catalytic domain that are involved in the conversion of hormone precursors into their active form. This study aims at designing small cyclic peptides that would specifically inhibit two members of this family of enzymes, namely, the neuroendocrine PC1/3 and the ubiquitously expressed furin. We studied peptide sequences related to the 18-residue loop identified as the active site of the 83 amino acid barley serine protease inhibitor 2 (BSPI-2). Peptides incorporating mutations at various positions in the sequence were synthesized on solid phase and purified by HPLC. Cyclization was achieved by the introduction of a disulfide bridge between the two Cys residues located at both the N- and C-terminal extremities. Peptides VIIA and VIIB incorporating P4Arg, P2Lys, P1Arg, and P2'Lys were the most potent inhibitors with K(i) around 4 microM for furin and around 0.5 microM for PC1/3. Whereas peptide VIIB behaved as a competitive inhibitor of furin, peptide VIIA acted as a noncompetitive one. However, all peptides were eventually cleaved after variable incubation times by PC1/3 or furin. To avoid this problem, we incorporated at the identified cleavage site a nonscissile aminomethylene bond (psi[CH(2)-NH]). Those pseudopeptides, in particular peptide VIID, were shown not to be cleaved and to inhibit potently furin. Conversely, they were not able to inhibit PC1/3 at all. Those results show the validity of this approach in designing new effective PC inhibitors showing a certain level of discrimination between PC1/3 and furin.
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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) | 0.001 | 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".