Encapsulation of an anticancer drug Isatin inside a host nano-vehicle SWCNT: a molecular dynamics simulation
Bibliographic record
Abstract
Abstract The use of carbon nanotubes as anticancer drug delivery cargo systems is a promising modality as they are able to perforate cellular membranes and transport the carried therapeutic molecules into the cellular components. Our work describes the encapsulation process of a common anticancer drug, Isatin (1H-indole-2,3-dione) as a guest molecule, in a capped single-walled carbon nanotube (SWCNT) host with chirality of (10,10). The encapsulation process was modelled, considering an aqueous solution, by a molecular dynamics (MD) simulation under a canonical NVT ensemble. The interactions between the atoms of Isatin were obtained from the DREIDING force filed. The storage capacity of the capped SWCNT host was evaluated to quantify its capacity to host multiple Isatin molecules. Our results show that the Isatin can be readily trapped inside the volume cavity of the capped SWCNT and it remained stable, as featured by a reduction in the van der Waals forces between Isatin guest and the SWCNT host (at approximately − 30 kcal mol−1) at the end of the MD simulation (15 ns). Moreover, the free energy of encapsulation was found to be − 34 kcal mol−1 suggesting that the Isatin insertion procedure into the SWCNT occurred spontaneously. As calculated, a capped SWCNT (10,10) with a length of 30 Å, was able to host eleven (11) molecules of Isatin, that all remained steadily encapsulated inside the SWCNT volume cavity, showing a potential for the use of carbon nanotubes as drug delivery cargo systems.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".