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Record W2790532659 · doi:10.1039/c8an00099a

A simple and sensitive detection of small molecule–protein interactions based on terminal protection-mediated exponential strand displacement amplification

2018· article· en· W2790532659 on OpenAlexaff
Chang Yeol Lee, Hyo Yong Kim, Soeun Kim, Ki Soo Park, Hyun Gyu Park

Bibliographic record

VenueThe Analyst · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsKootenay Association for Science & Technology
FundersMinistry of Science, ICT and Future Planning
KeywordsDNAExonucleaseChemistryBiotinFluorescenceExonuclease IIIBiophysicsSmall moleculeCombinatorial chemistryMolecular biologyBiological systemBiochemistryPhysicsBiologyDNA polymerase

Abstract

fetched live from OpenAlex

We herein describe a simple and sensitive strategy to detect a small molecule-protein interaction based on terminal protection-mediated exponential strand displacement amplification (eSDA). In principle, the small molecule linked to a DNA probe protects the DNA probe against the exonuclease I-catalyzed degradation after its binding to the corresponding target protein. The protected DNA probe then serves as a template to promote eSDA. Consequently, a large number of duplexes are produced, which leads to a high fluorescence from a double-stranded DNA specific fluorescent dye, SYBR Green I. As a model system to prove this sensing strategy, the interaction between biotin and streptavidin (SA), which is known to be the strongest among the non-covalent biological interactions, was selected and its analytical performance was thoroughly investigated. As a result, SA was sensitively detected with the limit of detection of 16 pM. In addition, the practical applicability of this method was successfully demonstrated by reliably determining the SA in human serum.

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 score0.189
Threshold uncertainty score0.306

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 head0.012
GPT teacher head0.265
Teacher spread0.254 · 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

Citations16
Published2018
Admission routes1
Has abstractyes

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