Department of Chemistry, College of Science, Semnan University, Semnan, Iran.
Department of Chemistry, Faculty of Science, Imam Hossein University, Tehran, Iran.
Drug Deliv. 2020 Dec;27(1):1201-1217. doi: 10.1080/10717544.2020.1801890.
Superparamagnetic iron oxide nanoparticles have been synthesized using chain length of (3-aminopropyl) triethoxysilane for cancer therapy. First, we have developed a layer by layer functionalized with grafting 2,4-toluene diisocyanate as a bi-functional covalent linker onto a nano-FeO support. Then, they were characterized by Fourier transform infrared, X-ray powder diffraction, field emission scanning electron microscopy, energy-dispersive X-ray spectroscopy, and VSM techniques. Finally, all nanoparticles with positive or negative surface charges were tested against K562 (myelogenous leukemia cancer) cell lines to demonstrate their therapeutic efficacy by MTT assay test. We found that the higher toxicity of FeO@SiO@APTS ∼ Schiff base-Cu(II) (IC: 1000 μg/mL) is due to their stronger degradation, with larger intracellular release of iron ions, as compared to surface passivated NPs. For first time, the molecular dynamic simulations of all compounds were carried out afterwards optimizing using MM+, Semi-empirical (AM1) and Ab-initio (STO-3G), Forcite Gemo Opt, Forcite Dynamics, Forcite Energy and CASTEP in Materials studio 2017. The energy (eV), space group, lattice parameters (Å), unit cell parameters (Å), and electron density of the predicted structures were taken from the CASTEP module of Materials Studio. The docking methods were used to predict the DNA binding affinity, ribonucleotide reductase, and topoisomerase II.
使用(3-氨丙基)三乙氧基硅烷的链长合成超顺磁氧化铁纳米粒子用于癌症治疗。首先,我们通过层层功能化,将 2,4-甲苯二异氰酸酯接枝到纳米 FeO 载体上作为双官能共价连接体。然后,通过傅里叶变换红外光谱、X 射线粉末衍射、场发射扫描电子显微镜、能谱和 VSM 技术对其进行了表征。最后,所有带正电荷或负电荷的纳米粒子都与 K562(髓性白血病癌细胞)细胞系进行了测试,通过 MTT 测定试验证明了它们的治疗效果。我们发现,由于更强的降解,具有更大的细胞内铁离子释放,FeO@SiO@APTS∼Schiff 碱-Cu(II)(IC:1000μg/mL)的毒性更高。首次对所有化合物进行了分子动力学模拟,随后使用 MM+、半经验(AM1)和从头算(STO-3G)、Forcite Gemo Opt、Forcite Dynamics、Forcite Energy 和 CASTEP 在 Materials studio 2017 中进行了优化。预测结构的能量(eV)、空间群、晶格参数(Å)、晶胞参数(Å)和电子密度取自 Materials Studio 的 CASTEP 模块。采用对接方法预测 DNA 结合亲和力、核糖核苷酸还原酶和拓扑异构酶 II。