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Record W4292764235 · doi:10.1101/2022.08.22.504810

Identification of a cardiac glycoside exhibiting favorable brain bioavailability and potency for reducing levels of the cellular prion protein

2022· preprint· en· W4292764235 on OpenAlexafffund
Shehab Eid, Thomas Zerbes, Declan Williams, Xinzhu Wang, Chris Sackmann, Sammy Meier, Nickolai O. Dulin, Pavel Nagorny, Gerold Schmitt‐Ulms

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2022
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPrion Diseases and Protein Misfolding
Canadian institutionsCanada Research ChairsDiscovery CentreUniversity of Toronto
FundersKrembil Foundation
KeywordsBioavailabilityPharmacologyChemistryIn silicoBlood–brain barrierBiochemistryBiologyNeuroscienceCentral nervous system

Abstract

fetched live from OpenAlex

ABSTRACT Several strands of investigation have established that a reduction in the levels of the cellular prion protein (PrP C ) is a promising avenue for the treatment of prion diseases. We recently described an indirect approach for reducing PrP C levels that targets Na,K-ATPases (NKAs) with cardiac glycosides (CGs), causing cells to respond with the degradation of these pumps and nearby molecules, including PrP C . Because the therapeutic window of widely used CGs is narrow and their brain bioavailability is low, we set out to identify a CG with improved pharmacological properties for this indication. Starting with the CG known as oleandrin, we combined in silico modeling of CG binding poses within human NKA folds, CG structure-activity relationship (SAR) data, and predicted blood-brain barrier (BBB) penetrance scores to identify CG derivatives with improved characteristics. Focusing on C4’-dehydro-oleandrin as a chemically accessible shortlisted CG derivative, we show that it reaches four times higher levels in the brain than in the heart one day after subcutaneous administration, exhibits promising pharmacological properties, and suppresses steady-state PrP C levels by 84% in immortalized human cells that have been differentiated to acquire neural or astrocytic characteristics. Finally, we validate that the mechanism of action of this approach for reducing cell surface PrP C levels requires C4’-dehydro-oleandrin to engage with its cognate binding pocket within the NKA α subunit. The improved brain bioavailability of C4’-dehydro-oleandrin, combined with its relatively low toxicity, make this compound an attractive lead for brain CG indications and recommends its further exploration for the treatment of prion diseases. AUTHOR SUMMARY Prion diseases are fatal neurodegenerative diseases for which there is no effective treatment. An abundance of data indicates that reducing the levels of a specific protein, termed the cellular prion protein (PrP C ), would not only be safe but would delay disease onset and extend prion disease survival. This project builds on our recent discovery that PrP C binds to NKAs, specific cellular transport proteins that use energy to electrify cellular membranes by pumping charged potassium and sodium metals in and out of cells. We showed that targeting NKAs with their natural inhibitors, cardiac glycosides (CGs), causes brain cells to internalize and degrade NKAs, and that PrP C , on account of residing next to NKAs, gets co-degraded. Natural CGs act primarily on the heart. Here, we used computational modeling to identify a CG, termed KDC203, that is predicted to have favorable characteristics for brain applications. We show that KDC203 reduces PrP C levels by 84% in immortalized human brain-like cells grown in the dish. Moreover, we show that KDC203 exhibits relatively low toxicity, predominantly targets the brain when subcutaneously injected into mice, and has other promising pharmacological characteristics that recommend it for further evaluation for the treatment of prion diseases.

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)0.000
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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.011
GPT teacher head0.226
Teacher spread0.215 · 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

Citations2
Published2022
Admission routes2
Has abstractyes

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