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Record W4223552247 · doi:10.1002/ange.202201895

Programmed Supramolecular Assemblies Using Orthogonal Pairs of Heterodimeric Coiled Coil Peptides

2022· article· en· W4223552247 on OpenAlexfundno aff
Linhai Jiang, Xiaobing Zuo, Jianping Li, Nathaniel J. Traaseth, Kent Kirshenbaum

Bibliographic record

VenueAngewandte Chemie · 2022
Typearticle
Languageen
FieldMaterials Science
TopicSupramolecular Self-Assembly in Materials
Canadian institutionsnot available
FundersDivision of ChemistryYork UniversityNational Institutes of HealthNational Science Foundation
KeywordsCoiled coilSupramolecular chemistryQuadrilateralTopology (electrical circuits)NanotechnologyCovalent bondMaterials scienceChemistryCrystallographyPhysicsMathematicsCombinatoricsBiochemistry

Abstract

fetched live from OpenAlex

Despite recent progress, it remains challenging to program biomacromolecules to assemble into discrete nanostructures with pre-determined sizes and topologies. We report here a novel strategy to address this challenge. By using two orthogonal pairs of heterodimeric coiled coils as the building blocks, we constructed six discrete supramolecular assemblies, each composed of a prescribed number of coiled coil components. Within these assemblies, different coiled coils were connected via end-to-side covalent linkages strategically pre-installed between the non-complementary pairs. The overall topological features of two highly complex assemblies, a "barbell" and a "quadrilateral" form, were characterized experimentally and were in good agreement to the designs. This work expands the design paradigms for peptide-based discrete supramolecular assemblies and will provide a route for de novo fabrication of functional protein materials.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

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 head0.026
GPT teacher head0.264
Teacher spread0.238 · 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 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

Citations1
Published2022
Admission routes1
Has abstractyes

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