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Record W2025213752 · doi:10.1021/nl1024886

Bipartite Design of a Self-Fibrillating Protein Copolymer with Nanopatterned Peptide Display Capabilities

2010· article· en· W2025213752 on OpenAlexaff
Marc Bruning, Laurent Kreplak, Sonja Leopoldseder, Shirley A. Müller, Philippe Ringler, Laurence Duchesne, David G. Fernig, Andreas Engel, Zöhre Ucurum-Fotiadis, Olga Mayans

Bibliographic record

VenueNano Letters · 2010
Typearticle
Languageen
FieldMaterials Science
TopicSupramolecular Self-Assembly in Materials
Canadian institutionsDalhousie University
Fundersnot available
KeywordsTitinNanotechnologyNanofiberMaterials sciencePolymerNanoscopic scaleCopolymerNanoparticleSarcomere

Abstract

fetched live from OpenAlex

The development of biomatrices for technological and biomedical applications employs self-assembled scaffolds built from short peptidic motifs. However, biopolymers composed of protein domains would offer more varied molecular frames to introduce finer and more complex functionalities in bioreactive scaffolds using bottom-up approaches. Yet, the rules governing the three-dimensional organization of protein architectures in nature are complex and poorly understood. As a result, the synthetic fabrication of ordered protein association into polymers poses major challenges to bioengineering. We have now fabricated a self-assembling protein nanofiber with predictable morphologies and amenable to bottom-up customization, where features supporting function and assembly are spatially segregated. The design was inspired by the cross-linking of titin filaments by telethonin in the muscle sarcomere. The resulting fiber is a two-protein system that has nanopatterned peptide display capabilities as shown by the recruitment of functionalized gold nanoparticles at regular intervals of ∼ 5 nm, yielding a semiregular linear array over micrometers. This polymer promises the uncomplicated display of biologically active motifs to selectively bind and organize matter in the fine nanoscale. Further, its conceptual design has high potential for controlled plurifunctionalization.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.040
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.008
GPT teacher head0.218
Teacher spread0.210 · 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

Citations22
Published2010
Admission routes1
Has abstractyes

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