Intracellularly Actuated Quantum Dot–Peptide–Doxorubicin Nanobioconjugates for Controlled Drug Delivery via the Endocytic Pathway
Bibliographic record
Abstract
Nanoparticle (NP)-mediated drug delivery (NMDD) has emerged as a novel method to overcome the limitations of traditional systemic delivery of therapeutics, including the controlled release of the NP-associated drug cargo. Currently, our most advanced understanding of how to control NP-associated cargos is in the context of soft nanoparticles (e.g., liposomes), but less is known about controlling the release of cargos from the surface of hard NPs (e.g., gold NPs). Here we employ a semiconductor quantum dot (QD) as a prototypical hard NP platform and use intracellularly triggered actuation to achieve spatiotemporal control of drug release and modulation of drug efficacy. Conjugated to the QD are two peptides: (1) a cell-penetrating peptide (CPP) that facilitates uptake of the conjugate into the endocytic pathway and (2) a display peptide conjugated to doxorubicin (DOX) via three different linkages (ester, disulfide, and hydrazone) that are responsive to enzymatic cleavage, reducing conditions, and low pH, respectively. Formation of the QD-[peptide-DOX]-CPP complex is driven by self-assembly that allows control over both the ratio of each peptide species conjugated to the QD and the eventual drug dose delivered to cells. Förster resonance energy transfer assays confirmed successful assembly of the QD-peptide complexes and functionality of the linkages. Confocal microscopy was employed to visualize residence of the QD-[peptide-DOX]-CPP complexes in the endocytic pathway, and distinct differences in DOX localization were noted for the ester linkage, which showed clear signs of nuclear delivery versus the hydrazone, disulfide, and amide control. Finally, delivery of the QD-[peptide-DOX]-CPP conjugate resulted in cytotoxicity for the ester linkage that was comparable to free DOX. Attachment of DOX via the hydrazone linkage facilitated intermediary toxicity, while the disulfide and amide control linkages showed minimal toxicity. Our data demonstrate the utility of hard NP-peptide bioconjugates to function as multifunctional scaffolds for simultaneous control over cellular drug uptake and toxicity and the vital role played by the nature of the chemical linkage that appends the drug to the NP carrier.
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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) | 0.000 | 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".