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Record W2748408164 · doi:10.1002/anie.201706162

On the Role of Chirality in Guiding the Self‐Assembly of Peptides

2017· article· en· W2748408164 on OpenAlexafffund
Shibaji Basak, Ishwar Singh, Annaleizle Ferranco, Jebreil Syed, Heinz‐Bernhard Kraatz

Bibliographic record

VenueAngewandte Chemie International Edition · 2017
Typearticle
Languageen
FieldMaterials Science
TopicSupramolecular Self-Assembly in Materials
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHomochiralityChemistryTripeptideSelf-assemblyChirality (physics)PeptideIntermolecular forceStereochemistryMoleculeEnantiomerOrganic chemistryChiral symmetryBiochemistry

Abstract

fetched live from OpenAlex

Homochirality in peptides is crucial in sustaining "like-like" intermolecular interactions that allow the formation of assemblies and aggregates and is ultimately responsible for the resulting material properties. With the help of a series of stereoisomers of the tripeptide F-F-L, we demonstrate the critical role that peptide stereochemistry plays in the self-assembly of peptides, guided by molecular recognition, and for self-sorting. Homochiral self-assemblies are thermally and mechanically more robust compared to heterochiral self-assemblies. Morphological studies of the multicomponent peptide systems showed that aggregates formed from homochiral peptides possessed a uniform nano-fibrous structure, whereas heterochiral systems resulted in self-sorted systems with a heterogeneous morphology. In essence, homochiral peptides form the stronger aggregates, which may be one of reasons why homochirality is preferred in living systems.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.012
Threshold uncertainty score0.262

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.000
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 head0.024
GPT teacher head0.282
Teacher spread0.257 · 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

Citations72
Published2017
Admission routes2
Has abstractyes

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