Mutant recombinant serpins as highly specific inhibitors of human kallikrein 14
Bibliographic record
Abstract
The reactive center loop (RCL) of serpins plays an essential role in the inhibition mechanism acting as a substrate for their target proteases. Changes within the RCL sequence modulate the specificity and reactivity of the serpin molecule. Recently, we reported the construction of alpha1-antichymotrypsin (ACT) variants with high specificity towards human kallikrein 2 (hK2) [Cloutier SM, Kündig C, Felber LM, Fattah OM, Chagas JR, Gygi CM, Jichlinski P, Leisinger HJ & Deperthes D (2004) Eur J Biochem271, 607-613] by changing amino acids surrounding the scissile bond of the RCL and obtained specific inhibitors towards hK2. Based on this approach, we developed highly specific recombinant inhibitors of human kallikrein 14 (hK14), a protease correlated with increased aggressiveness of prostate and breast cancers. In addition to the RCL permutation with hK14 phage display-selected substrates E8 (LQRAI) and G9 (TVDYA) [Felber LM, Borgoño CA, Cloutier SM, Kündig C, Kishi T, Chagas JR, Jichlinski P, Gygi CM, Leisinger HJ, Diamandis EP & Deperthes D (2005) Biol Chem386, 291-298], we studied the importance of the scaffold, serpins alpha1-antitrypsin (AAT) or ACT, to confer inhibitory specificity. All four resulting serpin variants ACT(E8), ACT(G9), AAT(E8) and AAT(G9) showed hK14 inhibitory activity and were able to form covalent complex with hK14. ACT inhibitors formed more stable complexes with hK14 than AAT variants. Whereas E8-based inhibitors demonstrated a rather relaxed specificity reacting with various proteases with trypsin-like activity including several human kallikreins, the two serpins variants containing the G9 sequence showed a very high selectivity for hK14. Such specific inhibitors might prove useful to elucidate the biological role of hK14 and/or its implication in cancer.
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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".