Synthesis and Use of the Bifunctional Sulfenic Acid Probe BCN‐E‐BCN for <i>In Vitro</i> and Cell‐Based Assays of Protein Oxidation
Bibliographic record
Abstract
The reversible oxidation of cysteine thiol groups to sulfenic acid by reactive oxygen species (ROS) such as hydrogen peroxide can impact protein function, activity, and localization. As a consequence, ROS have profound effects on cell functions including proliferation, differentiation, and survival. Furthermore, there are clear associations between the effects of ROS on cells and the etiology of several diseases including cancer and neurodegeneration. In spite of the importance of cysteine sulfenylation as a validated post-translational modification, its labile nature impedes efficient and reproducible detection of proteins with cysteine sulfenic acid residues. To overcome this challenge, we developed a novel cell-permeable bifunctional reagent, consisting of two linked bicyclo[6.1.0]nonyne (BCN) moieties coupled with a short ethylenediamine-derived linker (BCN-E-BCN) that enables the detection of sulfenylated proteins in vitro and in intact cells. The two symmetrical BCN groups allow protein sulfenic acids to be selectively tagged with a BCN at one end while allowing for copper-free click chemistry with azide-tagged reagents of the opposite BCN. In this protocol, the synthesis of BCN-E-BCN and its use to detect cysteine sulfenic acids will be detailed. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Copper-mediated cyclopropanation of 1,5-cyclooctadiene Basic Protocol 2: Synthesis of endo- and exo-bicyclononyne Basic Protocol 3: Synthesis of endo-BCN-E-BCN Basic Protocol 4: BCN-E-BCN treatment of wild-type and cysteine-deficient mutant recombinant cofilin protein Basic Protocol 5: BCN-E-BCN labeling in live cells Basic Protocol 6: Western blotting and visualization of BCN-E-BCN-labeled samples.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".