Polyoligopeptides functionalized zinc(II)porphyrins: Step towards artificial hemes
Bibliographic record
Abstract
Two new zinc(II)porphyrin oligopeptide conjugates (zinc(II)-5,10,15,20-bis[4-(peptide)- phenyl]porphyrin (5) and -tetrakis[3,5-di(peptide)phenyl]porphyrin (9; peptide = -CH2(CO)Gly-Phe-Ala-CNH2) were prepared using the click chemistry with azides and ethynyl-containing precursors. The spectroscopic signature (S0→S1 and transient T1→Tn absorption, excitation and emission spectra) are typical for zinc(II)porphyrin and shows no perturbation upon anchoring the oligopeptides, whereas some small decreases in the photophysical parameters (𝜏F and ΦF), and larger decrease in T1 lifetimes are noted, which are attributable to the known "loose bolt" effect. The structure for 9 in solution was addressed qualitatively using computer modeling and the comparison of the bimolecular fluorescence quenching rate constants between 5 and 9 using C60 as a photooxidative agent. While 5 exhibits a totally accessible zinc(II)porphyrin unit for a C60 approach, 9 shows a slower quenching rate constant meaning some steric hindrance must be present.
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 | 0.000 | 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 | 0.000 |
| 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".