MétaCan
Menu
Back to cohort
Record W2937941911 · doi:10.31635/ccschem.019.20180012

Harvesting Mechanical Work From Folding-Based Protein Engines: From Single-Molecule Mechanochemical Cycles to Macroscopic Devices

2019· article· en· W2937941911 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCCS Chemistry · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicForce Microscopy Techniques and Applications
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for Innovation
KeywordsFolding (DSP implementation)Work (physics)Protein foldingNanotechnologyCoupling (piping)MechanochemistryMoleculeMaterials scienceMechanical energyActuatorProtein engineeringBiophysicsMolecular machineChemical physicsChemistryMechanical engineeringPhysicsEngineeringBiologyElectrical engineeringBiochemistryThermodynamics

Abstract

fetched live from OpenAlex

Mechanochemical coupling cycles underlie the work-generation mechanisms of biological systems and are realized by highly regulated conformational changes of the protein machineries. However, it has been challenging to utilize protein conformational changes to do mechanical work at the macroscopic level in biomaterials, and it remains elusive to construct macroscopic mechanochemical devices based on molecular-level mechanochemical coupling systems. Here, the authors demonstrate that protein folding can be utilized to realize protein’s mechanochemical cycles at both single-molecule and macroscopic levels. Our results demonstrate, for the first time, the successful harnessing of mechanical work generated by protein folding in a macroscopic protein hydrogel device, and the work generated by protein folding compares favorably with the energy output of molecular motors. Our work bridges a gap between single-molecule and macroscopic levels, and paves the way to utilizing proteins as building blocks to design protein-based artificial muscles and soft actuators.

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.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score1.000

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)0.0010.000

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 head0.008
GPT teacher head0.241
Teacher spread0.233 · 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