Convergent Preparation and Photophysical Characterization of Dimaleimide Dansyl Fluorogens: Elucidation of the Maleimide Fluorescence Quenching Mechanism
Bibliographic record
Abstract
Dimaleimide fluorogens are being developed for application to fluorescent protein labeling. In this method, fluorophores bearing two maleimide quenching groups do not fluoresce until both maleimide groups have undergone thiol addition reactions with the Cys residues of the target protein sequence [J. Am. Chem. Soc. 2005, 127, 559-566]. In this work, a new convergent synthetic route was developed that would allow any fluorophore to be attached via a linker to a dimaleimide moiety in a modular fashion. Series of dimaleimide and dansyl derivatives were thus prepared conveniently and used to elucidate the mechanism of maleimide quenching. Intersystem crossing was ruled out as a potential quenching pathway, based on the absence of a detectable triplet intermediate by laser flash photolysis. Stern-Volmer rate constants were measured with exogenous dimaleimide quenchers and found to be close to the diffusion-controlled limits, consistent with electron transfer being thermodynamically favorable. The thermodynamic feasibility of the photoinduced electron transfer (PET) quenching mechanism was verified by cyclic voltammetry. The redox potentials measured for dansyl and maleimide confirm that electron transfer from the dansyl excited state to a pendant maleimide group is exergonic and is responsible for fluorescence quenching of the fluorogens studied herein. Taking this PET quenching mechanism into account, future fluorogenic protein labeling agents will be designed with spacers of variable length and rigidity to probe the structure-property PET efficiency relationship.
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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) | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".