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Record W2953797568 · doi:10.1021/acs.jmedchem.9b00757

Novel Human Aminopeptidase N Inhibitors: Discovery and Optimization of Subsite Binding Interactions

2019· article· en· W2953797568 on OpenAlexaff
Ji Sook Lee, Natalie B. Vinh, Nyssa Drinkwater, Wei Yang, Komagal Kannan Sivaraman, Luke S. Schembri, Michelle Gazdik, Peter M. Grin, Georgina S. Butler, Christopher M. Overall, Susan A. Charman, Sheena McGowan, Peter J. Scammells

Bibliographic record

VenueJournal of Medicinal Chemistry · 2019
Typearticle
Languageen
FieldMedicine
TopicPeptidase Inhibition and Analysis
Canadian institutionsUniversity of British Columbia
FundersNational Health and Medical Research CouncilCooperative Research Centres, Australian Government Department of IndustryMonash University
KeywordsChemistryHydroxamic acidMatrix metalloproteinase inhibitorEnzymeBiochemistryAminopeptidaseIn vitroCytotoxicityPlasmodium falciparumStereochemistryPharmacologyAmino acidBiologyLeucine

Abstract

fetched live from OpenAlex

Aminopeptidase N (APN/CD13) is a zinc-dependent M1 aminopeptidase that contributes to cancer progression by promoting angiogenesis, metastasis, and tumor invasion. We have previously identified hydroxamic acid-containing analogues that are potent inhibitors of the APN homologue from the malarial parasite Plasmodium falciparum M1 aminopeptidase (PfA-M1). Herein, we describe the rationale that underpins the repurposing of PfA-M1 inhibitors as novel APN inhibitors. A series of novel hydroxamic acid analogues were developed using a structure-based design approach and evaluated their inhibition activities against APN. N-(2-(Hydroxyamino)-2-oxo-1-(3′,4′,5′-trifluoro-[1,1′-biphenyl]-4-yl)ethyl)-4-(methylsulfonamido)benzamide (6ad) proved to be an extremely potent inhibitor of APN activity in vitro, selective against other zinc-dependent enzymes such as matrix metalloproteases, and possessed limited cytotoxicity against Ad293 cells and favorable physicochemical and metabolic stability properties. The combined results indicate that compound 6ad may be a useful lead for the development of anticancer agents.

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 score0.022
Threshold uncertainty score0.520

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 head0.013
GPT teacher head0.278
Teacher spread0.265 · 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

Citations24
Published2019
Admission routes1
Has abstractyes

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