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Record W2021528703 · doi:10.1021/ac060108i

Plug−Plug Kinetic Capillary Electrophoresis:  Method for Direct Determination of Rate Constants of Complex Formation and Dissociation

2006· article· en· W2021528703 on OpenAlexaff
Victor Okhonin, Alexander P. Petrov, Maxim V. Berezovski, Sergey N. Krylov

Bibliographic record

VenueAnalytical Chemistry · 2006
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Capillary Electrophoresis Applications
Canadian institutionsYork University
Fundersnot available
KeywordsElectropherogramChemistryCapillary electrophoresisElectrophoresisSpark plugDissociation (chemistry)Dissociation constantChromatographyReaction rate constantAnalytical Chemistry (journal)Computational chemistryThermodynamicsKineticsPhysical chemistryClassical mechanicsBiochemistry

Abstract

fetched live from OpenAlex

We present a method for direct determination of rate constants of complex formation, k(on), and dissociation, k(off). The method is termed plug-plug kinetic capillary electrophoresis (ppKCE). To explain the concept of the method, we consider the formation of a noncovalent complex C between molecules A and B; A is assumed to migrate slower in electrophoresis than B. In ppKCE, a short plug of A is injected into a capillary, followed by a short plug of B. When a high voltage is applied, the electrophoretic zone of B moves through that of A, allowing for the formation of C. When the zones of A and B are separated, C starts dissociating. The features of the resulting electropherogram are defined by both binding and dissociation. We developed a unique mathematical approach that allows finding k(on) and k(off) from a single electropherogram without nonlinear regression analysis. The approach uses algebraic functions with the only input parameters from electropherograms being areas and migration times of electrophoretic peaks. In this work, we explain theoretical bases of ppKCE and prove the principle of the method by finding k(on) and k(off) for a protein-ligand complex. The unique capability of the method to directly determine both k(on) and k(off) along with its simplicity make ppKCE highly attractive to a broad community of molecular scientists.

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 score0.194
Threshold uncertainty score0.478

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 head0.008
GPT teacher head0.235
Teacher spread0.228 · 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

Citations52
Published2006
Admission routes1
Has abstractyes

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