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Record W3202531487 · doi:10.3390/molecules26195911

Synthesis and Evaluation of Novel 1,2,6-Thiadiazinone Kinase Inhibitors as Potent Inhibitors of Solid Tumors

2021· article· en· W3202531487 on OpenAlexfundno aff
Andreas S. Kalogirou, Michael P. East, Tuomo Laitinen, Chad Torrice, Kaitlyn Maffuid, David H. Drewry, Panayiotis A. Koutentis, Gary L. Johnson, Daniel J. Crona, Christopher R. M. Asquith

Bibliographic record

VenueMolecules · 2021
Typearticle
Languageen
FieldChemistry
TopicQuinazolinone synthesis and applications
Canadian institutionsnot available
FundersDivision of ChemistryUniversity of North Carolina at Chapel HillNational Institutes of HealthCommon FundBiocenter FinlandMinistero dello Sviluppo EconomicoGenome CanadaFundação de Amparo à Pesquisa do Estado de São PauloUniversity of CyprusOntario Ministry of Economic Development and InnovationEuropean Federation of Pharmaceutical Industries and AssociationsWellcome TrustNovartis PharmaChina Scholarship CouncilNational Institute of Diabetes and Digestive and Kidney DiseasesA.G. Leventis FoundationResearch Promotion FoundationPfizerNational Science Foundation
KeywordsProstate cancerCancer researchKinaseCell cultureFibroblastChemistryMedicineCancerInternal medicineBiologyBiochemistry

Abstract

fetched live from OpenAlex

A focused series of substituted 4H-1,2,6-thiadiazin-4-ones was designed and synthesized to probe the anti-cancer properties of this scaffold. Insights from previous kinase inhibitor programs were used to carefully select several different substitution patterns. Compounds were tested on bladder, prostate, pancreatic, breast, chordoma, and lung cancer cell lines with an additional skin fibroblast cell line as a toxicity control. This resulted in the identification of several low single digit micro molar compounds with promising therapeutic windows, particularly for bladder and prostate cancer. A number of key structural features of the 4H-1,2,6-thiadiazin-4-one scaffold are discussed that show promising scope for future improvement.

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)0.001
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 score0.021
Threshold uncertainty score0.680

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.021
GPT teacher head0.275
Teacher spread0.254 · 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

Citations5
Published2021
Admission routes1
Has abstractyes

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