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Record W2902340796 · doi:10.1039/c8ra08515c

Protein-induced fluorescence enhancement for a simple and universal detection of protein/small molecule interactions

2018· article· en· W2902340796 on OpenAlexaff
Hansol Kim, Chang Yeol Lee, Jayeon Song, Junhyeok Yoon, Ki Soo Park, Hyun Gyu Park

Bibliographic record

VenueRSC Advances · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBiotin and Related Studies
Canadian institutionsKootenay Association for Science & Technology
FundersMinistry of Science, ICT and Future PlanningNational Research Foundation
KeywordsFluorescenceBiotinStreptavidinChemistryBiophysicsSmall moleculeFolate receptorTarget proteinBiotinylationProtein–protein interactionBiological systemBiochemistryBiologyPhysics

Abstract

fetched live from OpenAlex

We herein describe a novel and efficient method for the detection of protein/small molecule (SM) interactions, which relies on the protein-induced fluorescence enhancement (PIFE). In this method, a duplex probe is designed to position Cy3 and SM at the optimal distance to maximize the effect of PIFE, which is utilized as the key component. In the presence of target proteins that bind to SM, the Cy3 is guided close to the target proteins, which significantly enhances the fluorescence signal through a process of PIFE. With this approach, we successfully analyzed a model target protein, streptavidin (STV) that interacts with biotin (BTN) in less than 10 min without any washing steps. In addition, the practical applicability of this method was demonstrated by reliably determining STV in human serum. Finally, the universal applicability of this method was demonstrated by monitoring the interaction between folate and folate receptors.

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 score0.280

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 head0.011
GPT teacher head0.264
Teacher spread0.253 · 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

Citations13
Published2018
Admission routes1
Has abstractyes

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