Hierarchical Organization of Ferrocene–Peptides
Bibliographic record
Abstract
Hierarchical self-assembly of disubstituted ferrocene (Fc)-peptide conjugates that possess Gly-Val-Phe and Gly-Val-Phe-Phe peptide substituents leads to the formation of nano- and micro-sized assemblies. Hydrogen-bonding and hydrophobic interactions provide directionality to the assembly patterns. The self-assembling behavior of these compounds was studied in solution by using (1)H NMR and circular dichroism (CD) spectroscopies. In the solid state, attenuated total reflectance (ATR) FTIR spectroscopy, single-crystal X-ray diffraction (XRD), powder X-ray diffraction (PXRD), and scanning electron microscopy (SEM) methods were used. Spontaneous self-assembly of Fc-peptides through intra- and intermolecular hydrogen-bonding interactions induces supramolecular assemblies, which further associate and give rise to fibers, large fibrous crystals, and twisted ropes. In the case of Fc[CO-Gly-Val-Phe-OMe](2) (1), molecules initially interact to form pleated sheets that undergo association into long fibers that form bundles and rectangular crystalline cuboids. Molecular offsets and defects, such as screw dislocations and solvent effects that occur during crystal growth, induce the formation of helical arrangements, ultimately leading to large twisted ropes. By contrast, the Fc-tetrapeptide conjugate Fc[CO-Gly-Val-Phe-Phe-OMe](2) (2) forms a network of nanofibers at the supramolecular level, presumably due to the additional hydrogen-bonding and hydrophobic interactions that stem from the additional Phe residues.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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) | 0.004 | 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 teacher head, 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".