Bioengineered Peptides Based on α1-PDX Structure as Inhibitors of Furin: Design, Synthesis and Comparative Efficacy
Bibliographic record
Abstract
Furin is a Ca 2+ -dependent serine protease which cleaves proprotein substrates at the Arg-Xaa-(Lys/Arg)-Arg site to generate biologically active proteins. Furin’s critical role in many cellular events associated with health disorders such as HIV, SARS, anthrax, and influenza as well as cancer has made inhibitors of this enzyme as therapeutic targets. To this date, the most potent inhibitor of furin is the bioengineered serpin (serine protease inhibitors) protein namely α1-PDX. It was already demonstrated that the reactive site loop (RSL) of all serpins are prime interactive domains responsible for their protease inhibitory function. Therefore, the objective of the present study was to develop small peptides with the RSL structure of serpin α1-PDX, as inhibitors of furin activity. Fifteen peptides were designed from reactive site loop structure of α1-PDX (sequences 367-394) with different mutations in this site, and were synthesized using a solid-phase peptide synthesizer, and characterized by MALDI-tof mass spectrometry and amino acid analysis. The inhibitory effects of the designed peptides against furin activity were evaluated by spectroflourometry using QVEGF-C [Abz-QVHSIIRRsSLP-Y(NO2)-A-CONH2, Abz = 2-amino benzoic acid and Y(NO2) = 3-nitro tyrosine] as substrate. The results showed that all of the designed peptides inhibit furin activity with different efficacies in a time and concentration dependent pattern. Peptides containing His or straight alkyl side chain amino acids in positions P2, P3, P6 and P8 have higher efficacy for blocking furin activity in comparison with peptides containing Arg or Lys in that position. The study further revealed that the peptides inactivate furin in a slow tight binding pattern. Our study provides an alternate strategy for development of efficient peptide-based inhibitors of proprotein convertases such as furin.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".