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Record W2738161677 · doi:10.1002/cmdc.201700300

Rational Design of a Highly Potent and Selective Peptide Inhibitor of PACE4 by Salt Bridge Interaction with D160 at Position P3

2017· article· en· W2738161677 on OpenAlexafffund
Vahid Dianati, Azar Shamloo, Anna Kwiatkowska, Roxane Desjardins, Armand Soldera, Robert Day, Yves L. Dory

Bibliographic record

VenueChemMedChem · 2017
Typearticle
Languageen
FieldMedicine
TopicPeptidase Inhibition and Analysis
Canadian institutionsUniversité de Sherbrooke
FundersCanadian Cancer Society Research InstitutePublic Health Agency of CanadaProstate Cancer CanadaCancer Research Institute
KeywordsProprotein ConvertasesFurinProteasesSalt bridgeSerineSerine proteaseChemistryResidue (chemistry)StereochemistryBiochemistryProteaseEnzymeMutantLDL receptorGene

Abstract

fetched live from OpenAlex

Abstract PACE4, a member of the proprotein convertases (PCs) family of serine proteases, is a validated target for prostate cancer. Our group has developed a potent and selective PACE4 inhibitor: Ac‐LLLLRVKR‐NH 2 . In seeking for modifications to increase the selectivity of this ligand toward PACE4, we replaced one of its P3 Val methyl groups with a basic group capable of forming a salt bridge with D160 of PACE4. The resulting inhibitor is eight times more potent than the P3 Val parent inhibitor and two times more selective over furin, because the equivalent salt bridge with furin E257 is not optimal. Moreover, the β‐branched nature of the new P3 residue favors the extended β‐sheet conformation usually associated with substrates of proteases. This work provides new insight for better understanding of β‐sheet backbone–backbone interactions between serine proteases and their peptidic ligands.

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 head0.021
GPT teacher head0.272
Teacher spread0.251 · 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

Citations10
Published2017
Admission routes2
Has abstractyes

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