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Record W2783099657 · doi:10.1038/s41467-017-02252-2

Harnessing insulin- and leptin-induced oxidation of PTP1B for therapeutic development

2018· article· en· W2783099657 on OpenAlexfundno aff
Navasona Krishnan, Christopher A. Bonham, Ioana A. Rus, Om Kumar Shrestha, Carla M. Gauss, Aftabul Haque, Ante Tocilj, Leemor Joshua‐Tor, Nicholas K. Tonks

Bibliographic record

VenueNature Communications · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Tyrosine Phosphatases
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaNational Cancer InstituteNational Institutes of HealthCold Spring Harbor LaboratoryNational Institute of General Medical SciencesUniversity of WindsorDon Monti Memorial Research FoundationHoward Hughes Medical Institute
KeywordsProtein tyrosine phosphataseSmall moleculeRegulatorLeptinGlucose homeostasisInsulinDiabetes mellitusChemistryFunction (biology)Signal transductionBiochemistryCell biologyBiologyObesityInsulin resistanceEndocrinology

Abstract

fetched live from OpenAlex

The protein tyrosine phosphatase PTP1B is a major regulator of glucose homeostasis and energy metabolism, and a validated target for therapeutic intervention in diabetes and obesity. Nevertheless, it is a challenging target for inhibitor development. Previously, we generated a recombinant antibody (scFv45) that recognizes selectively the oxidized, inactive conformation of PTP1B. Here, we provide a molecular basis for its interaction with reversibly oxidized PTP1B. Furthermore, we have identified a small molecule inhibitor that mimics the effects of scFv45. Our data provide proof-of-concept that stabilization of PTP1B in an inactive, oxidized conformation by small molecules can promote insulin and leptin signaling. This work illustrates a novel paradigm for inhibiting the signaling function of PTP1B that may be exploited for therapeutic intervention in diabetes and obesity.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.070
Threshold uncertainty score0.268

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.032
GPT teacher head0.326
Teacher spread0.293 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations65
Published2018
Admission routes1
Has abstractyes

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