Encapsulation of anticancer drugs into carbon nanotubes: Heuristic algorithm approach and mathematical model
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Issued Date
2025-05-01
Resource Type
eISSN
19326203
Scopus ID
2-s2.0-105006488261
Pubmed ID
40392888
Journal Title
Plos One
Volume
20
Issue
5 May
Rights Holder(s)
SCOPUS
Bibliographic Citation
Plos One Vol.20 No.5 May (2025)
Suggested Citation
Sumetpipat K., Baowan D. Encapsulation of anticancer drugs into carbon nanotubes: Heuristic algorithm approach and mathematical model. Plos One Vol.20 No.5 May (2025). doi:10.1371/journal.pone.0321403 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/110532
Title
Encapsulation of anticancer drugs into carbon nanotubes: Heuristic algorithm approach and mathematical model
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Corresponding Author(s)
Other Contributor(s)
Abstract
This research combines mathematical derivation and optimization techniques to investigate the non-covalent encapsulation of chemotherapy drugs (fluorouracil, proflavine, methylene blue, and doxorubicin) within carbon nanotubes, aiming to improve targeted drug delivery in cancer therapy. We derive analytical expression for the interaction energy between an atom and an infinite cylinder, and utilize the U-NSGA-III algorithm to optimize the system’s energy by varying molecular positions and tube radius. Optimal tube radii for single- and dual-drug encapsulations are determined. Fixing the tube radius at 10 Å and varying the number of drug molecules, we observe that the shortest distance from the drug’s center of mass to the tube wall is independent of the number of encapsulated molecules, depending only on the drug type. Moreover, equilibrium configurations exhibit two primary patterns, clustering near the tube wall or dispersion around the circumference, suggesting potential control mechanisms for drug release kinetics. This hybrid approach, integrating analytical and computational methods, significantly reduces computational cost, providing a foundation for studying drug-nanocarrier interactions, ultimately accelerating the development of more effective and targeted cancer treatments.