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Record W1968231808 · doi:10.1021/ac0355348

Mechanistic Studies on Enzymatic Reactions by Electrospray Ionization MS Using a Capillary Mixer with Adjustable Reaction Chamber Volume for Time-Resolved Measurements

2004· article· en· W1968231808 on OpenAlexafffund
Derek J. Wilson, Lars Konermann

Bibliographic record

VenueAnalytical Chemistry · 2004
Typearticle
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsChemistryReaction rate constantMass spectrometryElectrospray ionizationAnalytical Chemistry (journal)ElectrosprayIonizationSubstrate (aquarium)Capillary electrophoresisSteady state (chemistry)KineticsChromatographyPhysical chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Mass spectrometry (MS)-based techniques have enormous potential for kinetic studies on enzyme-catalyzed processes. In particular, the use of electrospray ionization (ESI) MS for steady-state measurements is well established. However, there are very few reports of MS-based studies in the pre-steady-state regime, because it is difficult to achieve the time resolution required for this type of experiment. We have recently developed a capillary mixer with adjustable reaction chamber volume for kinetic studies by ESI-MS with millisecond time resolution (Wilson, D. J.; Konermann, L. Anal. Chem. 2003, 75, 6408-6414). Data can be acquired in kinetic mode, where the concentrations of selected reactive species are monitored as a function of time, or in spectral mode, where entire mass spectra are obtained for selected reaction times. Here, we describe the application of this technique to study the kinetics of enzyme reactions. The hydrolysis of p-nitrophenyl acetate by chymotrypsin was chosen as a simple chromophoric model system. On-line addition of a "makeup solvent" immediately prior to ionization allowed the pre-steady-state accumulation of acetylated chymotrypsin to be monitored. The rate constant for acetylation, as well as the dissociation constant of the enzyme-substrate complex obtained from these data, is in excellent agreement with results obtained by conventional stopped-flow methods. Bradykinin was chosen to illustrate the performance of the ESI-MS-based method with a nonchromophoric substrate. In this case, the unfavorable rate constant ratio for acylation and deacylation of the enzyme precluded measurements in the pre-steady-state regime. Steady-state experiments were carried out to determine the turnover number and the Michaelis constant for bradykinin. The methodologies used in this work open a wide range of possibilities for future ESI-MS-based kinetic assays in enzymology.

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)
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 score0.161
Threshold uncertainty score1.000

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)0.0010.000

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 head0.032
GPT teacher head0.288
Teacher spread0.256 · 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

Citations52
Published2004
Admission routes2
Has abstractyes

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