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Record W2770821468 · doi:10.1080/08927022.2017.1405158

Emergence of order in self-assembly of the intrinsically disordered biomineralisation peptide n16N

2017· article· en· W2770821468 on OpenAlexfundno aff
Gil O. Rutter, A. H. Brown, David Quigley, Tiffany R. Walsh, Michael P. Allen

Bibliographic record

VenueMolecular Simulation · 2017
Typearticle
Languageen
FieldMaterials Science
TopicCalcium Carbonate Crystallization and Inhibition
Canadian institutionsnot available
FundersAir Force Office of Scientific ResearchUniversity of WarwickEngineering and Physical Sciences Research CouncilVeskiRyerson University
KeywordsPeptideAragonitePinctada fucataMonomerChemistryChemical physicsCrystallographySequence (biology)Calcium carbonateBiophysicsMaterials sciencePearl oysterPolymerBiologyBiochemistryPearl

Abstract

fetched live from OpenAlex

We present the results of an aggregation study on the intrinsically disordered biomineralisation peptide n16N, which selects the aragonite polymorph of calcium carbonate and is expected to have aggregation-dependent structure and function. The peptide is a sub-sequence of the in vivo protein n16, with putative framework and polymorph selection roles in the nacre layer of pearl oyster (Pinctada fucata). Employing the intermediate-resolution coarse-grained protein model PLUM*, which has previously been validated with respect to n16N, we simulate assemblies of these peptide units for system sizes inaccessible to atomistic models. We use extensive conformational sampling to show that the configurational ensemble explored by n16N aggregates contains a significant proportion of ordered -structure, within which arrangement of monomers is consistent with a previous hypothesis on functionally distinct subdomains of n16N. We also study an n16N mutant which fails to aggregate in experimental studies and obtain very similar behaviour, the consequences of which are discussed.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

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 head0.013
GPT teacher head0.271
Teacher spread0.258 · 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 designSimulation or modeling
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

Citations4
Published2017
Admission routes1
Has abstractyes

Explore more

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