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Record W2604758481 · doi:10.1021/acs.nanolett.7b00814

A DNA Nanodevice That Loads and Releases a Cargo with Hemoglobin-Like Allosteric Control and Cooperativity

2017· article· en· W2604758481 on OpenAlexafffund
Davide Mariottini, Andrea Idili, Alexis Vallée‐Bélisle, Kevin W. Plaxco, Francesco Ricci

Bibliographic record

VenueNano Letters · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsUniversité de Montréal
FundersNatural Sciences and Engineering Research Council of CanadaH2020 European Research CouncilDirectorate-General for Research and InnovationAssociazione Italiana per la Ricerca sul Cancro
KeywordsNanodeviceAllosteric regulationCooperativityBiophysicsChemistryNanotechnologyRational designHemoglobinProtein engineeringDNASynthetic biologyComputational biologyMaterials scienceBiochemistryBiologyEnzyme

Abstract

fetched live from OpenAlex

Here we report the rational design of a synthetic molecular nanodevice that is directly inspired from hemoglobin, a highly evolved protein whose oxygen-carrying activity is finely regulated by a sophisticated network of control mechanisms. Inspired by the impressive performance of hemoglobin we have designed and engineered in vitro a synthetic DNA-based nanodevice containing up to four interacting binding sites that, like hemoglobin, can load and release a cargo over narrow concentration ranges, and whose affinity can be finely controlled via both allosteric effectors and environmental cues like pH and temperature. As the first example of a synthetic DNA nanodevice that undergoes a complex network of nature-inspired control mechanisms, this represents an important step toward the use of similar nanodevices for diagnostic and drug-delivery applications.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.018
Threshold uncertainty score0.559

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)0.0000.000

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 head0.007
GPT teacher head0.233
Teacher spread0.226 · 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

Citations39
Published2017
Admission routes2
Has abstractyes

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