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pHAST (pH-Driven Aptamer Switch for Thrombin) Catch-and-Release of Target Protein

2016· article· en· W2344877955 on OpenAlexafffund
Erin M. McConnell, R. Bolzon, Paulette Mezin, Grant Frahm, Michael Johnston, Maria C. DeRosa

Bibliographic record

VenueBioconjugate Chemistry · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsHealth CanadaCarleton University
FundersNatural Sciences and Engineering Research Council of CanadaCarleton University
KeywordsAptamerChemistryFörster resonance energy transferThrombinBiosensorBiophysicsProtonationG-quadruplexConformational changeFluorescenceDNACombinatorial chemistryBiochemistryIonMolecular biologyOrganic chemistry

Abstract

fetched live from OpenAlex

A pH-driven DNA nanomachine based on the human α-thrombin binding aptamer was designed for the specific catch-and-release of human α-thrombin at neutral and acidic pH, respectively. In neutral conditions, the thrombin aptamer component of the nanomachine is exposed and exists in the G-quadruplex conformation required to bind to the target protein. At slightly acidic pH, the polyadenine tail of the nanomachine becomes partially protonated and A+(anti)•G(syn) mispairing results in a conformational change, causing the target protein to be released. Förster resonance energy transfer (FRET) was used to monitor conformational switching over multiple pH cycles. Electrophoretic mobility shift assay (EMSA) and fluorescence anisotropy were used to show pH dependent protein binding and release by the nanomachine. This approach could be applied generally to existing G-rich aptamers to develop novel biosensors, theranostics, and nanoswitches.

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 score0.011
Threshold uncertainty score0.665

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 head0.009
GPT teacher head0.252
Teacher spread0.243 · 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

Citations24
Published2016
Admission routes2
Has abstractyes

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