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Enhancing the Drug-Like Profile of a Potent Peptide PACE4 Inhibitor by the Formation of a Host–Guest Inclusion Complex with β-Cyclodextrin

2023· article· en· W4385684544 on OpenAlexafffund
Pauline Navals, Anna Kwiatkowska, Nawel Mekdad, Frédéric Couture, Roxane Desjardins, Robert Day, Yves L. Dory

Bibliographic record

VenueMolecular Pharmaceutics · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicChemical Synthesis and Analysis
Canadian institutionsUniversité de Sherbrooke
FundersCanadian Institutes of Health Research
KeywordsPeptidomimeticDrugCyclodextrinChemistryIn vitroPeptideDrug repositioningPotencyEnzymeProstate cancerPharmacologyBiochemistryCombinatorial chemistryMedicineCancerInternal medicine

Abstract

fetched live from OpenAlex

The enzyme PACE4 has been validated as a promising therapeutic target to expand the range of prostate cancer (PCa) treatments. In recent years, we have developed a potent peptidomimetic inhibitor, namely, compound C23 (Ac-(DLeu)LLLRVK-4-amidinobenzylamide). Like many peptides, C23 suffers from an unfavorable drug-like profile which, despite our efforts, has not yet benefited from the usual SAR studies. Hence, we turned our attention toward a novel formulation strategy, i.e., the use of cyclodextrins (CDs). CDs can benefit compounds through the formation of "host-guest" complexes, shielding the guest from degradation and enhancing biological survival. In this study, a series of βCD-C23 complexes have been generated and their properties evaluated, including potency toward the enzyme in vitro, a cell-based proliferation assay, and stability in plasma. As a result, a new βCD-formulated lead compound has been identified, which, in addition to being more soluble and more potent, also showed an improved stability profile.

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 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 score0.027
Threshold uncertainty score0.357

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 head0.014
GPT teacher head0.272
Teacher spread0.258 · 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

Citations3
Published2023
Admission routes2
Has abstractyes

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