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Recombinant Nepenthesin II for Hydrogen/Deuterium Exchange Mass Spectrometry

2015· article· en· W278490554 on OpenAlexafffund
Meng‐Lin Yang, Morgan Hoeppner, Martial Rey, Alan Kádek, Petr Man, David C. Schriemer

Bibliographic record

VenueAnalytical Chemistry · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and Biological Electrophysiology Studies
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsEuropean Regional Development FundCanada Foundation for InnovationAlberta Innovates - Health Solutions
KeywordsChemistryCleavage (geology)ProteasesHydrogen–deuterium exchangeMass spectrometryRecombinant DNAEnzymeDeuteriumChromatographyBiochemistry

Abstract

fetched live from OpenAlex

The pitcher secretions of the Nepenthes genus of carnivorous plants contain a proteolytic activity that is very useful for hydrogen/deuterium exchange mass spectrometry (HX-MS). Our efforts to reconstitute pitcher fluid activity using recombinant nepenthesin I (one of two known aspartic proteases in the fluid) revealed a partial cleavage profile and reduced enzymatic stability in certain HX-MS applications. We produced and characterized recombinant nepenthesin II to determine if it complemented nepenthesin I in HX-MS applications. Nepenthesin II shares many properties with nepenthesin I, such as fast digestion at reduced temperature and pH, and broad cleavage specificity, but in addition, it cleaves C-terminal to tryptophan. Neither enzyme reproduces the C-terminal proline cleavage we observed in the natural extract. Nepenthesin II is considerably more resistant to chemical denaturants and reducing agents than nepenthesin I, and it possesses a stability profile that is similar to that of pepsin. Higher stability combined with the slightly broader cleavage specificity makes nepenthesin II a useful alternative to pepsin and a more complete replacement for pitcher fluid in HX-MS applications.

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 score0.354
Threshold uncertainty score0.283

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 head0.043
GPT teacher head0.236
Teacher spread0.193 · 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

Citations77
Published2015
Admission routes2
Has abstractyes

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