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Record W4390192937 · doi:10.1002/alz.076479

Efforts toward discovering inhibitors of the SYK SH2–FCER1γ interaction as potential Alzheimer’s disease chemical probes and therapeutics

2023· article· en· W4390192937 on OpenAlexaff
Arunima Sikdar, Frances M. Bashore, V.L. Katis, W.J. Bradshaw, Karolina A. Rygiel, Yuhong Du, Dongxue Wang, Brian Hardy, Dmitri Kireev, Kenneth H. Pearce, Haian Fu, Stephen V. Frye, Alison D. Axtman

Bibliographic record

VenueAlzheimer s & Dementia · 2023
Typearticle
Languageen
FieldMedicine
TopicCholinesterase and Neurodegenerative Diseases
Canadian institutionsStructural Genomics Consortium
Fundersnot available
KeywordsSykDrug discoveryComputational biologyChemistryCancer researchPharmacologyBiochemistryBiologyTyrosine kinaseReceptor

Abstract

fetched live from OpenAlex

Abstract Background Spleen associated tyrosine kinase (SYK) plays a potential role in several neurodegenerative conditions. To date, a few pharmacological inhibitors have been developed, targeting the ATP‐binding kinase domain, and some of these inhibitors have been reported to show beneficial effects on the pathophysiology of Alzheimer’s (PMC: 9179326).In 2015, the Accelerating Medicines Partnership: Alzheimer’s Disease (AMP‐AD) Knowledge Portal analyzed and identified SYK and the FC gamma receptor (FCεR1γ) as targets for Alzheimer’s Disease (AD), through multidimensional human “omic” (genomic, epigenomic, RNAseq, and proteomic) data (PMID: 26853544). Thus, the interaction between FCER1G p‐ITAM and SYK tandem SH2 domain was selected for further target validation and small molecule hit discovery efforts through the portfolio of novel targets to treat the Alzheimer’s disease via the Target Enablement to Accelerate Therapy Development for Alzheimer’s Disease (TREAT‐AD) program were initiated. As part of the TREAT‐AD effort, we aim to provide experimental validation of a SYK–FCεR1γ interaction inhibitor for AD and begin drug discovery campaigns to identify novel inhibitors of this interaction, with the goal of developing an in vivo chemical probe. Method Using purified SYK tandem‐SH2 (tSH2) domain protein, a time‐resolved fluorescence energy transfer (TR‐FRET) based assay platform was developed with a fluoroprobe‐labeled phospho‐ITAM peptide of FCεR1γ. This assay was miniaturized for ultra‐high‐throughput screening (uHTS) of 100K compounds in parallel with a DNA encoded library (DEL) screening approach (Ref: X‐Chem). The hits from these screening methods were evaluated in secondary assays in an attempt to validate the initial hits. Result We have previous crystallography data of the SYK tSH2 domains bound to phospho‐ITAM peptides and have established a TR‐FRET based assay to discover and characterize inhibitors of the interaction between the FCεR1γ peptide and SYK tSH2 domains. Several thio‐uric acids hit compounds have been identified from uHTS. Most of them demonstrate potency in the TR‐FRET based assay of <10 µM. Although, orthogonal experimental validation is still under process. Conclusion Through the TREAT‐AD program, we have explored the SYK–FCεR1γ interaction and demonstrated novel screening strategies, which can be further exploited to generate novel inhibitors of this interaction.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.042
GPT teacher head0.313
Teacher spread0.271 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2023
Admission routes1
Has abstractyes

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