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Record W4210517447 · doi:10.1016/j.bmcl.2022.128588

Development of dihydropyrrolopyridinone-based PKN2/PRK2 chemical tools to enable drug discovery

2022· article· en· W4210517447 on OpenAlexfundno aff
Fiona L. Scott, Jéssica E. Takarada, Mihaela Ficu, Lewis E. Pennicott, Tristan Reuillon, Rafael M. Couñago, Katlin B. Massirer, Jonathan M. Elkins, Simon E. Ward

Bibliographic record

VenueBioorganic & Medicinal Chemistry Letters · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Kinase Regulation and GTPase Signaling
Canadian institutionsnot available
FundersGenentechConselho Nacional de Desenvolvimento Científico e TecnológicoUniversity of SussexWellcome TrustCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorOntario Genomics InstituteEuropean Federation of Pharmaceutical Industries and AssociationsMerck KGaAOntario GenomicsFundação de Amparo à Pesquisa do Estado de São PauloGenome CanadaMcGill UniversityUniversidade Estadual de CampinasBayerPfizerBristol-Myers Squibb
KeywordsKinomeEffectorChemistryDrug discoveryKinaseMembrane permeabilityComputational biologyBiochemistryBiologyMembrane

Abstract

fetched live from OpenAlex

The Protein Kinase N proteins (PKN1, PKN2 and PKN3) are Rho GTPase effectors. They are involved in several biological processes such as cytoskeleton organization, cell mobility, adhesion, and cell cycle. Recently PKNs have been reported as essential for survival in several tumor cell lines, including prostate and breast cancer. Here, we report the development of dihydropyrrolopyridinone-based inhibitors for PKN2 and its closest homologue, PKN1, and their associated structure–activity relationship (SAR). Our studies identified a range of molecules with high potency exemplified by compound 8 with Ki = 8 nM for PKN2 and 14x selectivity over PKN1. Membrane permeability and target engagement for PKN2 were assessed by a NanoBRET cellular assay. Importantly, good selectivity across the wider human kinome and other kinase family members was achieved. These compounds provide strong starting points for lead optimization to PKN1/2 development compounds.

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 categoriesMeta-epidemiology (narrow)
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 score0.031
Threshold uncertainty score1.000

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 head0.012
GPT teacher head0.222
Teacher spread0.210 · 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.

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

Citations6
Published2022
Admission routes1
Has abstractyes

Explore more

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