FRET Quenching of Photosensitizer Singlet Oxygen Generation
Bibliographic record
Abstract
The development of activatable photodynamic therapy (PDT) has demonstrated a utility for effective photosensitizer quenchers. However, little is known quantitatively about Forster resonance energy transfer (FRET) quenching of photosensitizers, even though these quenchers are versatile and readily available. To characterize FRET deactivation of singlet oxygen generation, we attached various quenchers to the photosensitizer pyropheophorbide-alpha (Pyro) using a lysine linker. The linker did not induce major changes in the properties of the photosensitizer. Absorbance and emission wavelength maxima of the quenched constructs remained constant, suggesting that quenching by ground-state complex formation was minimal. All quenchers sharing moderate spectral overlap with the fluorescence emission of Pyro (J > or = 5.1 x 10(13) M(-1) cm(-1) nm4) quenched over 90% of the singlet oxygen, and quenchers with weaker spectral overlap displayed minimal quenching. A self-quenched double Pyro construct exhibited intermediate quenching. Consistent with a FRET deactivation mechanism, extension of the linker to a 10 residue polyproline peptide resulted in only the quenchers with spectral overlap almost 2 orders of magnitude higher (J > or = 3.7 x 10(15) M(-1) cm(-1) nm4) maintaining high quenching efficiency. Overall, there was good correlation (0.98) between fluorescence quenching and singlet oxygen quenching, implying that fluorescence intensity can be a convenient indicator for the singlet oxygen production status of activatable photosensitizers. Uniform singlet oxygen luminescence lifetimes of the compounds, along with minimal triplet state transient absorption were consistent with quenchers primarily deactivating the photosensitizer excited singlet state. In vitro, cells treated with well-quenched constructs demonstrated greatly reduced PDT induced toxicity, indicating that FRET-based quenchers can provide a level of quenching useful for future biological applications. The presented findings show that FRET-based quenchers can potently decrease singlet oxygen production and therefore be used to facilitate the rational design of activatable photosensitizers.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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".