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Record W4388783415 · doi:10.1002/trc2.12429

SHIP1 therapeutic target enablement: Identification and evaluation of inhibitors for the treatment of late‐onset Alzheimer's disease

2023· article· en· W4388783415 on OpenAlexfundno aff
Cynthia D. Jesudason, Emily R. Mason, Shaoyou Chu, Adrian L. Oblak, June Javens‐Wolfe, Mustapha Moussaif, Greg Durst, Philip A. Hipskind, Daniel E. Beck, Jiajun Dong, Ovini Amarasinghe, Zhong‐Yin Zhang, Adam Hamdani, Kratika Singhal, Andrew D. Mesecar, Sarah Souza, Marlene Jacobson, Jerry Di Salvo, Disha Soni, Murugesh Kandasamy, Andrea R. Masters, Sara K. Quinney, Suzanne Doolen, Hasi Huhe, Stacey J. Sukoff Rizzo, Bruce T. Lamb, Alan D. Palkowitz, Timothy I. Richardson

Bibliographic record

VenueAlzheimer s & Dementia Translational Research & Clinical Interventions · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPI3K/AKT/mTOR signaling in cancer
Canadian institutionsnot available
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institute on AgingNational Cancer InstituteNational Institutes of HealthSchool of Medicine, Indiana UniversityPurdue UniversityPartenariat Canadien Contre Le CancerUniversity of Pittsburgh
KeywordsDiseaseIdentification (biology)MedicineOncologyInternal medicineBiology

Abstract

fetched live from OpenAlex

INTRODUCTION: , it is a negative regulator of microglia function. Validated inhibitors are needed to evaluate SHIP1 as a potential therapeutic target. METHODS: We identified inhibitors and screened the enzymatic domain of SHIP1. A protein construct containing two domains was used to evaluate enzyme inhibitor potency and selectivity versus SHIP2. Inhibitors were tested against a construct containing all ordered domains of the human and mouse proteins. A cellular thermal shift assay (CETSA) provided evidence of target engagement in cells. Phospho-AKT levels provided further evidence of on-target pharmacology. A high-content imaging assay was used to study the pharmacology of SHIP1 inhibition while monitoring cell health. Physicochemical and absorption, distribution, metabolism, and excretion (ADME) properties were evaluated to select a compound suitable for in vivo studies. RESULTS: SHIP1 inhibitors displayed a remarkable array of activities and cellular pharmacology. Inhibitory potency was dependent on the protein construct used to assess enzymatic activity. Some inhibitors failed to engage the target in cells. Inhibitors that were active in the CETSA consistently destabilized the protein and reduced pAKT levels. Many SHIP1 inhibitors were cytotoxic either at high concentration due to cell stress or they potently induced cell death depending on the compound and cell type. One compound activated microglia, inducing phagocytosis at concentrations that did not result in significant cell death. A pharmacokinetic study demonstrated brain exposures in mice upon oral administration. DISCUSSION: 3-((2,4-Dichlorobenzyl)oxy)-5-(1-(piperidin-4-yl)-1H-pyrazol-4-yl) pyridine activated primary mouse microglia and demonstrated exposures in mouse brain upon oral dosing. Although this compound is our recommended chemical probe for investigating the pharmacology of SHIP1 inhibition at this time, further optimization is required for clinical studies. Highlights: Cellular thermal shift assay (CETSA) and signaling (pAKT) assays were developed to provide evidence of src homology 2 (SH2) domain-contaning inositol phosphatase 1 (SHIP1) target engagement and on-target activity in cellular assays.A phenotypic high-content imaging assay with simultaneous measures of phagocytosis, cell number, and nuclear intensity was developed to explore cellular pharmacology and monitor cell health.SHIP1 inhibitors demonstrate a wide range of activity and cellular pharmacology, and many reported inhibitors are cytotoxic.The chemical probe 3-((2,4-dichlorobenzyl)oxy)-5-(1-(piperidin-4-yl)-1H-pyrazol-4-yl) pyridine is recommended to explore SHIP1 pharmacology.

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)0.006
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.623
Threshold uncertainty score0.468

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
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 head0.386
GPT teacher head0.528
Teacher spread0.143 · 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 designObservational
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

Citations12
Published2023
Admission routes1
Has abstractyes

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