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Record W4362466334 · doi:10.31665/jfb.2023.18341

Biomolecular interactions and inhibition kinetics of human soluble epoxide hydrolase by tetrapeptide YMSV

2023· article· en· W4362466334 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Food Bioactives · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEicosanoids and Hypertension Pharmacology
Canadian institutionsUniversity of Ottawa
FundersUniversity of Ottawa
KeywordsEpoxide hydrolase 2TetrapeptideChemistryIC50StereochemistryPeptideHydrogen bondDocking (animal)KineticsCircular dichroismEnzymeBiochemistryIn vitroMoleculeOrganic chemistry

Abstract

fetched live from OpenAlex

Soluble epoxide hydrolase (sEH) contributes to the pathophysiology of neurodegenerative diseases by decreasing the epoxyeicosatrienoic acids/dihydroeicosatrienoic acids ratio and influencing the anti-inflammatory system. Thus, sEH inhibition reduces systemic inflammation, particularly in the brain. This study investigated sEH inhibition by a tetrapeptide, YMSV, and its mechanism of action. Enzyme inhibition kinetics demonstrated that YMSV is a mixed-competitive inhibitor of sEH, with a half-maximal inhibitory concentration (IC<sub>50</sub>) of 179.5 ± 0.92 µM. Secondary structural analysis of sEH by circular dichroism showed that YMSV decreased the α-helices by 7.7% and increased the β-sheets and random coils by 11.4% and 22%, respectively. Molecular docking simulation indicated that YMSV formed a hydrogen bond with the Asp333 residue of the hydrolase pocket of sEH in addition to the binding of non-active site residues. The findings provide new insights into the mechanism of sEH inhibition by YMSV and its potential as a peptide-based anti-depressant nutraceutical.

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.

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 score0.002
Threshold uncertainty score0.377

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 head0.016
GPT teacher head0.291
Teacher spread0.275 · 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