Novel approaches for the identification of modulators of receptor tyrosine phosphatase sigma
Bibliographic record
Abstract
Leukocyte common antigen-related receptor protein tyrosine phosphatases (LAR-RPTPs) are type II A receptor tyrosine phosphatases which have been shown to have considerable effects on a variety of neural activities including axonal outgrowth, neural regeneration and synapse plasticity. Ligands, novel downstream adaptor, and effector proteins have been recently identified to interact with LAR-RPTPs. This association is essential for LAR-RPTPs mediated signalling. The potential therapeutic benefits for selective inhibitors of RPTPs in the treatment of CNS injury, neurodegenerative disease and memory improvement has generated recent attention. Notwithstanding, a comprehensive investigation of the regulation and signalling network controlled by RPTPs (specifically RPTPσ) is lacking.To improve our understanding how RPTPσ functions at different molecular levels, we have developed a novel cell-based system, the split luciferase RPTPσ assay. The assay is specifically designed to analyse RPTPσ activity in live cells as well as permit the screening of its relevant ligands, small molecule inhibitors and therapeutic antibodies all selected towards inhibiting RPTPσ function. Using this system, we have successfully validated known ligands such as chondroitin sulfate proteoglycans (CSPGs) and haparan sulfate proteoglycans (HSPGs) which actively control RPTPσ activity from the extracellular milieu surrounding neurons. Further, in collaboration with Dr. P. Gunning at the University of Toronto, dimeric compounds specifically targeting RPTPσ have also been shown to inhibit RPTPσ activity in vitro and in vivo. Several antibodies against the ectodomain of RPTPσ have been generated and their specificity validated with different experimental approaches. Our results further demonstrated the therapeutic potential of these RPTPσ antibodies in the treatment of spinal cord injuries and neurodegenerative diseases.In an effort to decipher the molecular mechanisms of RPTPσ functions, several interacting proteins and potential substrates have been identified by using the modified yeast-two-hybrid system. In particular, we demonstrated that p250GAP is an associate protein and a physiological relevant substrate of RPTPσ. Our results showed that the increased activity of p250GAP following RPTPσ-mediated dephosphoryaltion further attenuated Rac activity and promoted the inhibition of axonal growth.In addition to the vital role of RPTPσ in the regulation of neural activity, recent studies on RPTPσ have shown its potential activity in regulating tumorigenesis. Our results indicated that RPTPσ hinders cell growth and migration, both in vitro and in vivo. Further, we investigated the molecular mechanisms beyond the anti-tumor effects of RPTPσ. Our data demonstrated that loss of RPTPσ led to an increase in autophagy accompanied by an elevation of mitochondrial activities. These results lend support to the notion that RPTPσ suppresses cell growth and migration through its negative regulation on autophagy. In conclusion, our results have made a substantial contribution to the current understanding of the role of RPTPσ in cell growth and migration. Furthermore, the data collected in this thesis has demonstrated the importance of RPTPσ as a novel therapeutic target in a variety of human diseases.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".