Quadratic Finite Element Method for 1D Deterministic Transport
Bibliographic record
Abstract
PACE4, one of the seven members of the proprotein convertase family, plays an important role in the progression of prostate cancer. Therefore, its inhibition has become an attractive target to develop new therapies against this disease. Recently, we have developed a highly potent and selective PACE4 inhibitor, known as the multi-Leu peptide with the following sequence Ac-LLLLRVKR-NH<sub>2</sub>. Herein, with the aim of improving the stability profile of this inhibitor for potential in vivo application, we investigated the impact of different cyclization strategies. The inhibitory activity of new peptides was tested and compared to their linear counterparts. The potent analogues were further selected for stability evaluation. Our results showed that the cyclization involving a C-terminal carboxylic acid (head-to-tail or side chain-to-tail) led to compounds with significantly diminished inhibitory potency towards PACE4, indicating that an appropriate balance between rigidity and flexibility of the structure is necessary to allow the optimal binding with the enzyme. On the other hand, the modification within a multi-Leu core in combination with the incorporation of a C-terminal 4-amidinobenzylamide (Amba) residue yielded potent cyclic analogues. The best compound derived from this group, (&)[Mpa]LLLC(&)RVK[Amba] (where & indicates cyclization, Mpa - 3-mercaptopropionic acid), exhibited promising overall profile comprising of potent inhibitory effect against PACE4 and prostate cancer cell lines as well as improved stability. We believe that this cyclic framework could be further used to design even more potent and stable PACE4 inhibitors.
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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".