Biogenic and Synthetic Polyamines Bind Cationic Dendrimers
Bibliographic record
Abstract
Biogenic polyamines are essential for cell growth and differentiation, while polyamine analogues exert antitumor activity in multiple experimental model systems, including breast and lung cancer. Dendrimers are widely used for drug delivery in vitro and in vivo. We report the bindings of biogenic polyamines, spermine (spm), and spermidine (spmd), and their synthetic analogues, 3,7,11,15-tetrazaheptadecane.4HCl (BE-333) and 3,7,11,15,19-pentazahenicosane.5HCl (BE-3333) to dendrimers of different compositions, mPEG-PAMAM (G3), mPEG-PAMAM (G4) and PAMAM (G4). FTIR and UV-visible spectroscopic methods as well as molecular modeling were used to analyze polyamine binding mode, the binding constant and the effects of polyamine complexation on dendrimer stability and conformation. Structural analysis showed that polyamines bound dendrimers through both hydrophobic and hydrophilic contacts with overall binding constants of K(spm-mPEG-G3) = 7.6 × 10(4) M(-1), K(spm-mPEG-PAMAM-G4) = 4.6 × 10(4) M(-1), K(spm-PAMAM-G4) = 6.6 × 10(4) M(-1), K(spmd-mPEG-G3) = 1.0 × 10(5) M(-1), K(spmd-mPEG-PAMAM-G4) = 5.5 × 10(4) M(-1), K(spmd-PAMAM-G4) = 9.2 × 10(4) M(-1), K(BE-333-mPEG-G3) = 4.2 × 10(4) M(-1), K(Be-333-mPEG-PAMAM-G4) = 3.2 × 10(4) M(-1), K(BE-333-PAMAM-G4) = 3.6 × 10(4) M(-1), K(BE-3333-mPEG-G3) = 2.2 × 10(4) M(-1), K(Be-3333-mPEG-PAMAM-G4) = 2.4 × 10(4) M(-1), K(BE-3333-PAMAM-G4) = 2.3 × 10(4) M(-1). Biogenic polyamines showed stronger affinity toward dendrimers than those of synthetic polyamines, while weaker interaction was observed as polyamine cationic charges increased. The free binding energies calculated from docking studies were: -3.2 (spermine), -3.5 (spermidine) and -3.03 (BE-3333) kcal/mol, with the following order of binding affinity: spermidine-PAMAM-G-4>spermine-PAMMAM-G4>BE-3333-PAMAM-G4 consistent with spectroscopic data. Our results suggest that dendrimers can act as carrier vehicles for delivering antitumor polyamine analogues to target tissues.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".