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DOI 10.1007/s00894-022-05337-y

Медицинская библиотека · Journal of molecular modeling · 2022

DFT study of therapeutic potential of graphitic carbon nitride as a carrier for controlled release of melphalan: an anticancer drug.

Perveen Mehvish, Aslam Farwa, Nazir Sidra, Khan Muhammad Issa, Zahra Ghulam, Iqbal Javed

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Аннотация

In the present research, the drug-delivery efficiency of graphitic carbon nitride (g-CN) for melphalan (an anti-cancer drug) was evaluated. To investigate the efficacy of g-CN as a drug-delivery system, the electronic properties of melphalan drug, g-CN, and g-CN-melphalan were calculated at the ground and excited states. The adsorption energy calculated for g-CN-melphalan complex in the water phase is - 1.51 eV. The interactions between g-CN and melphalan were investigated by a non-covalent interactions (NCl) analysis, which showed that there were weak interactions between g-CN and melphalan drug. These low intermolecular forces will allow for easy off-loading of the melphalan at the targeted site. Frontier molecular-orbitals (FMOs) analysis showed that the charge was transferred from melphalan to g-CN during the excitation process. Charge transfer was studied by charge decomposition analysis. Calculations at the excited state revealed that the g-CN-melphalan complex's λmax showed a redshift of 15 nm and 39 nm in the gas and water phase, respectively. The photoinduced electron transfer (PET) process was studied for 1-2 excited state by using electron hole theory. PET process suggests that fluorescence quenching may take place. The findings demonstrated that g-CN can be used as a drug-delivery system for melphalan drug to treat cancer. This investigation may also encourage more consideration of different 2D substances for drug delivery.

Для цитирования: Perveen Mehvish, Aslam Farwa, Nazir Sidra, Khan Muhammad Issa, Zahra Ghulam, Iqbal Javed. DFT study of therapeutic potential of graphitic carbon nitride as a carrier for controlled release of melphalan: an anticancer drug.. Journal of molecular modeling. 2022. DOI: 10.1007/s00894-022-05337-y.

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