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Record W2793255951 · doi:10.1124/jpet.117.247163

Identification and Characterization of Novel Receptor-Interacting Serine/Threonine‐Protein Kinase 2 Inhibitors Using Structural Similarity Analysis

2018· article· en· W2793255951 on OpenAlexafffund
Mohamed Salla, Gaddafi I. Danmaliki, Alaa Zare, Ahmed M. Said, Jack Moore, Vrajesh Pandya, Robin Manaloor, Sunny Fong, Anna R. Blankstein, Spencer B. Gibson, Laura Ramos Garcia, Pascal Meier, Khushwant S. Bhullar, Basil P. Hubbard, Yahya Fiteh, Harissios Vliagoftis, Ing Swie Goping, Dion R. Brocks, Peter H. Hwang, Carlos A. Velázquez-Martínez, Shairaz Baksh

Bibliographic record

VenueJournal of Pharmacology and Experimental Therapeutics · 2018
Typearticle
Languageen
FieldMedicine
TopicCytokine Signaling Pathways and Interactions
Canadian institutionsUniversity of ManitobaWomen and Children’s Health Research InstituteUniversity of Alberta
FundersFondation pour la Recherche MédicaleAlberta InnovatesWomen and Children's Health Research Institute
KeywordsPonatinibInflammationChemistryKinaseCancer researchDocking (animal)PharmacologySignal transductionBiologyCell biologyBiochemistryMedicineImmunology

Abstract

fetched live from OpenAlex

Receptor-interacting protein kinase 2 (RIP2 or RICK, herein referred to as RIPK2) is linked to the pathogen pathway that activates nuclear factor <i>κ</i>-light-chain-enhancer of activated B cells (NF<i>κ</i>B) and autophagic activation. Using molecular modeling (docking) and chemoinformatics analyses, we used the RIPK2/ponatinib crystal structure and searched in chemical databases for small molecules exerting binding interactions similar to those exerted by ponatinib. The identified RIPK2 inhibitors potently inhibited the proliferation of cancer cells by &gt; 70% and also inhibited NF<i>κ</i>B activity. More importantly, in vivo inhibition of intestinal and lung inflammation rodent models suggests effectiveness to resolve inflammation with low toxicity to the animals. Thus, our identified RIPK2 inhibitor may offer possible therapeutic control of inflammation in diseases such as inflammatory bowel disease, asthma, cystic fibrosis, primary sclerosing cholangitis, and pancreatitis.

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 score0.014
Threshold uncertainty score0.370

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 head0.044
GPT teacher head0.378
Teacher spread0.334 · 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

Citations31
Published2018
Admission routes2
Has abstractyes

Explore more

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