Thermodynamic Characterization of the Interaction between a Peptide–Drug Complex and Serum Proteins
Bibliographic record
Abstract
The interaction between a peptide-based drug delivery system and two serum proteins, bovine serum albumin (BSA) and immunoglobulin G (IgG), is investigated using fluorescence quenching and calorimetric techniques. An ionic-complementary self/co-assembling peptide, EAR8-II, is employed to encapsulate the hydrophobic anticancer drug pirarubicin (THP) and stabilize it in protein environments. Self/co-assembling properties of the peptide-drug complex (EAR8-II-THP) are shown to be different while interacting with serum proteins compared with the properties of the isolated complex. The results from thermodynamic studies suggest that the drug delivery system has a strong binding affinity (K(SV) 1689 M(-1)), exothermic and enthalpy-driven interaction, with BSA and a relatively weak affinity with IgG (K(SV) 295.2 M(-1)). In the presence of salt ions, the enthalpy and binding affinity remain unchanged, implying other interactions such as hydrogen bonding and Van der Waals interactions are present that are not affected by reduced polarity. This work forms the basis for further studies of EAR8-II-THP complexes in the presence of important proteins and for further evaluation of the complexes' immune response and anticancer activity.
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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 | 0.001 |
| 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".