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Record W2322543929 · doi:10.1021/jm301661h

Discovery of Piperazin-1-ylpyridazine-Based Potent and Selective Stearoyl-CoA Desaturase-1 Inhibitors for the Treatment of Obesity and Metabolic Syndrome

2012· article· en· W2322543929 on OpenAlexaff
Zaihui Zhang, Shaoyi Sun, Kodumuru Vishnumurthy, Duanjie Hou, Shifeng Liu, Nagasree Chakka, Serguei Sviridov, Sultan Chowdhury, David G. McLaren, Leslie G. Ratkay, Kuldip Khakh, Xing Cheng, Heinz W. Gschwend, Rajender K. Kamboj, Jianmin Fu, Michael D. Winther

Bibliographic record

VenueJournal of Medicinal Chemistry · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPeroxisome Proliferator-Activated Receptors
Canadian institutionsXenon Pharmaceuticals (Canada)
Fundersnot available
KeywordsChemistryStearoyl-CoA DesaturaseTolerabilityMetabolic syndromeIC50In vivoBioavailabilityPharmacologyBiochemistryIn vitroInternal medicineObesityGeneAdverse effectBiologyMedicineGene expressionBiotechnology

Abstract

fetched live from OpenAlex

Stearoyl-CoA desaturase-1 (SCD1) catalyzes de novo synthesis of monounsaturated fatty acids from saturated fatty acids. Studies have demonstrated that rodents lacking a functional SCD1 gene have an improved metabolic profile, including reduced weight gain, lower triglycerides, and improved insulin response. In this study, we discovered a series of piperazinylpyridazine-based highly potent, selective, and orally bioavailable compounds. Particularly, compound 49 (XEN103) was highly active in vitro (mSCD1 IC(50) = 14 nM and HepG2 IC(50) = 12 nM) and efficacious in vivo (ED(50) = 0.8 mg/kg). It also demonstrated striking reduction of weight gain in a rodent model. Our findings with small-molecule SCD1 inhibitors confirm the importance of this target in metabolic regulation, describe novel models for assessing SCD1 inhibitors for efficacy and tolerability and demonstrate an opportunity to develop a novel therapy for metabolic disease.

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 score0.020
Threshold uncertainty score0.449

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 head0.008
GPT teacher head0.242
Teacher spread0.234 · 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

Citations29
Published2012
Admission routes1
Has abstractyes

Explore more

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