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Characterization of the Interaction of a Novel Anticancer Molecule with PMMA, PCL, and PLGA Polymers via Computational Chemistry
The development of anticancer drugs is costly and time intensive. Computational approaches optimize the process by studying molecules such as naphthoquinones. This research explores the quantitative structure–activity relationship (QSPR) and molecular interactions among 2,2-dimethyl-3-((3-nitropheny...
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Published in: | Applied sciences 2025-01, Vol.15 (1), p.468 |
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Main Authors: | , , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites |
Online Access: | Get full text |
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Summary: | The development of anticancer drugs is costly and time intensive. Computational approaches optimize the process by studying molecules such as naphthoquinones. This research explores the quantitative structure–activity relationship (QSPR) and molecular interactions among 2,2-dimethyl-3-((3-nitrophenyl)amino)-2,3-dihydronaphtho[1,2-b]furan-4,5-dione (QPhNO2), a Nor-β-Lapachone derivative with anticancer properties, and the following polymers for nanoencapsulation: polymethyl methacrylate (PMMA), polycaprolactone (PCL), and poly-lactic-co-glycolic acid (PLGA). Spartan 14 optimized the compounds using density functional theory (DFT), while ArgusLab performed docking, and Discovery Studio analyzed post-docking results. Simulations indicated that polymers with larger energy gaps are more stable and less prone to deformation than QPhNO2, facilitating interaction with polymer chains. The binding energies for PMMA/QPhNO2, PCL/QPhNO2, and PLGA/QPhNO2 interactions were −4.607, −4.437, and −1.814 kcal/mol, respectively. Docking analysis revealed non-bonded interactions between polymers and QPhNO2. These findings highlight the role of computational methods in nanoencapsulation and molecular characterization, guiding the development of future analogs and combinations. |
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ISSN: | 2076-3417 2076-3417 |
DOI: | 10.3390/app15010468 |