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Record W4410329670 · doi:10.26434/chemrxiv-2025-xwnb7

Green Fluorescent Protein SELEX: Immobilization Chemistry and His-tag Epitope Bias

2025· preprint· en· W4410329670 on OpenAlexafffund
Stefen Stangherlin, Tyler Malloch, Anthony J. Clarke, Juewen Liu

Bibliographic record

VenueChemRxiv · 2025
Typepreprint
Languageen
FieldChemistry
TopicClick Chemistry and Applications
Canadian institutionsWilfrid Laurier UniversityUniversity of GuelphUniversity of Waterloo
FundersGlobal Water FuturesNatural Sciences and Engineering Research Council of CanadaUniversity of WaterlooCanada Foundation for Innovation
KeywordsSystematic evolution of ligands by exponential enrichmentEpitopeChemistryFluorescenceComputational biologyCombinatorial chemistryBiochemistryBiologyAntibodyGeneticsPhysicsGene

Abstract

fetched live from OpenAlex

Despite numerous DNA aptamers for proteins have been reported, a model system allowing the use of cost-effective proteins, unmodified DNA and convenient homogeneous assays is still lacking, which has in turn limited not only fundamental studies of aptamers but also translation to practical applications. Herein, three separate green fluorescent protein (GFP) selections were carried out using both non-tagged and His-tagged GFP immobilized on either NHS-resin or Co2+ affinity resin. Only the GFP/NHS system resulted in aptamers consistently bind to unmodified GFP, whereas the His-tagged GFP yielded aptamers biased towards the His-tag epitope. Sequence alignment and fluorescence polarization assays indicate many previously published aptamers bound to the His-tagged instead of the intended protein. This work not only obtained a model aptamer for proteins but also revealed critical information on bias towards His-tags during aptamer selections.

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 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 score0.030
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.024
GPT teacher head0.261
Teacher spread0.237 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

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