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Identification of Novel Indazole-based Inhibitors of Fibroblast GrowthFactor Receptor 1 (FGFR1)

2021· article· en· W3190850226 on OpenAlexaff
Galyna P. Volynets, Vasyl Vdovin, С. С. Лукашов, O. V. Borovykov, Iryna Borysenko, Andrii Gryshchenko, Volodymyr G. Bdzhola, A. P. Iatsyshyna, Л. Л. Лукаш, Yaroslav V. Bilokin, S. M. Yarmoluk

Bibliographic record

VenueCurrent Enzyme Inhibition · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicFibroblast Growth Factor Research
Canadian institutionsOntario Tobacco Research Unit
FundersNational Academy of Sciences of Ukraine
KeywordsFibroblast growth factor receptor 1IndazoleFibroblast growth factor receptorChemistryDocking (animal)IC50Virtual screeningAutoDockKinaseCancer researchIDH1PharmacologyBiochemistryFibroblast growth factorReceptorIn vitroBiologyDrug discoveryMedicineGeneStereochemistry

Abstract

fetched live from OpenAlex

Background: Overactivity of fibroblast growth factor receptor 1 (FGFR1) is associated with various tumors, particularly breast cancer, prostate cancer, non-small-cell lung carcinoma, myeloproliferative diseases, which makes this protein kinase a promising therapeutic target for anticancer therapy. Objective: The main aim of this study is to identify novel FGFR1 inhibitors. Method: In order to find FGFR1 inhibitors, virtual screening experiments were performed using AutoDock software. Best-scored compounds were tested in vitro using P32 radioactive kinase assay. Results: Small-molecular inhibitors of protein kinase FGFR1 were identified among indazole derivatives. The most active compound [3-(3,4-dichloro-phenyl)-1H-indazol-5-yl]-(2,3-dihydro-1Hcyclopenta[ b]quinolin-9-yl)-amine (1) inhibits FGFR1 with IC50 value of 100 nM. According to molecular docking results, this compound interacts simultaneously with adenine- and phosphate-binding regions of protein kinase FGFR1. The structure-activity relationships have been investigated and binding mode has been predicted. Conclusion: Compound 1 can be used for further structural optimization and biological research.

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 score0.009
Threshold uncertainty score0.854

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 head0.023
GPT teacher head0.288
Teacher spread0.265 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

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