Doxorubicin Adsorbed on Carbon Nanotubes: Helical Structure and New Release Trigger

Autor(en): Sadaf, Shamaila
Walder, Lorenz 
Stichwörter: ANTICANCER DRUG; CANCER-CELLS; carbon nanotubes; Chemistry; Chemistry, Multidisciplinary; doxorubicin; electrochemistry; eQCM; FUNCTIONALIZATION; glutathione; HYDROCHLORIDE; IN-VIVO; Materials Science; Materials Science, Multidisciplinary; MOLECULAR-DYNAMICS; NANO-GRAPHENE OXIDE; PHOTOTHERMAL THERAPY; semi-empirical; STM; SYSTEM; TARGETED DRUG-DELIVERY
Erscheinungsdatum: 2017
Herausgeber: WILEY
Journal: ADVANCED MATERIALS INTERFACES
Volumen: 4
Ausgabe: 19
Zusammenfassung: 
The well-known drug delivery system doxorubicin physically loaded on carbon nanotubes (Dox@CNT) is visualized by scanning tunneling microscopy at the molecular level, revealing rich architectural variability of Dox@CNT, and allowing to measure and rationalize reported loading efficiencies (80-200%) for the first time from image analysis. Reduction of Dox@CNT is identified as a so far unknown intrinsic release mechanism of biochemically relevance for Dox from Dox@CNT requiring no further CNT surface modification beside Dox loading. Electron injection into Dox@CNT from an electrode or from the biological reducing agent glutathione (GSH) leads to irreversible release of Dox. Its rate follows a linear free energy relationship (reduction potential vs log (Dox release rate)) with half-life times from below seconds to hours. With extracellular GSH levels in the micromolar range and intracellular GSH concentrations of 10 x 10(-3)m or even higher, the findings can explain the preferential intracellular release of Dox from its physically adsorbed state on CNTs. The influence of acidity on the release rate of Dox on pristine 6,5-CNTs in the absence of GSH is found to be negligible. The experimental findings are strongly supported by semi-empirical calculations.
ISSN: 21967350
DOI: 10.1002/admi.201700649

Show full item record

Page view(s)

2
Last Week
0
Last month
0
checked on Mar 2, 2024

Google ScholarTM

Check

Altmetric