MétaCan
Menu
Back to cohort
Record W2972644283 · doi:10.1002/1873-3468.13602

Crystal structure of peptide‐bound neprilysin reveals key binding interactions

2019· article· en· W2972644283 on OpenAlexfundno aff
Stephen Moss, Vasanta Subramanian, K. Ravi Acharya

Bibliographic record

VenueFEBS Letters · 2019
Typearticle
Languageen
FieldMedicine
TopicPeptidase Inhibition and Analysis
Canadian institutionsnot available
FundersAlzheimer SocietyAlzheimer's SocietyDiamond Light Source
KeywordsNeprilysinEndopeptidaseMetalloproteinaseChemistryPeptideBiochemistryEnzymeProteolysisProtein structureBinding siteHydrolaseBiophysicsBiology

Abstract

fetched live from OpenAlex

Neprilysin (NEP) is a promiscuous zinc metalloprotease with broad substrate specificity and cleaves a remarkable diversity of substrates through endopeptidase action. Two of these - amyloid-β and natriuretic peptides - implicate the enzyme in both Alzheimer's disease and cardiovascular disease, respectively. Here, we report the creation of a catalytically inactive NEP (E584D) to determine the first peptide-bound crystal structure at 2.6 Å resolution. The structure reveals key interactions involved in substrate binding which we have identified to be conserved in other known zinc metalloproteases. In addition, the structure provides evidence for a potential exosite within the central cavity that may play a critical role in substrate positioning. Together, these results contribute to our understanding of the molecular function of NEP.

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 categoriesInsufficient payload (model declined to judge)
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 score0.275
Threshold uncertainty score0.998

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)0.0030.000

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 head0.012
GPT teacher head0.263
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 teacher head, not a consensus.

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

Citations21
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueFEBS LettersSame topicPeptidase Inhibition and AnalysisFrench-language works237,207