Prodrug delivery of novel PTP1B inhibitors to enhance insulin signalling
Bibliographic record
Abstract
A growing percentage of the population is resistant to two key hormones - insulin and leptin - as a result of increased obesity, often leading to significant health consequences such as type 2 diabetes. Protein tyrosine phosphatase 1B (PTP1B) is a key negative regulator of signalling by both of these hormones, so that inhibitors of this enzyme may provide promise for correcting endocrine abnormalities in both diabetes and obesity. As with other tyrosine phosphatases, identification of viable drug candidates targeting PTP1B has been elusive because of the nature of its active site. Beginning with novel phosphotyrosine mimetics, we have designed some of the most potent PTP1B inhibitors. However, their highly acidic structures limit intrinsic permeability and pharmacokinetics. Ester prodrugs of these inhibitors improve their drug-like properties with the goal of delivering these nanomolar inhibitors to the cytoplasm of cells within target tissues. In addition to identifying prodrugs that is able to deliver active drugs into cells to inhibit PTP1B and increase insulin signalling, these compounds were further modified to gain a variety of cleavage properties for targeting activity in vivo. One such prodrug candidate improved insulin sensitivity in ob/ob mice, with lowered fasting blood glucose levels seen in the context of lowered fasting insulin levels following 4 days of intraperitoneal dosing. The results presented in this study highlight the potential for design of orally active drug candidates targeting PTP1B, while also delineating the considerable challenges remaining.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".