BN 纳米结构对抗肿瘤药物-电子密度研究的影响及其对恢复时间的影响。

IF 2.1 4区 化学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY
T. Aiswarya, K. K. Singh
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引用次数: 0

摘要

背景:通过将药物输送到预定的细胞位置,在给药系统中使用纳米材料可能会影响患者接受药物的方式,并有助于减轻严重的副作用。我们利用密度泛函理论评估了氮化硼碳纳米笼(BNCNCs)、氮化硼(BNNSs)和氮化硼碳纳米片(BNCNSs)作为美法仑(Mln)药物载体在气相和液相中的应用。我们系统地研究了偶极矩、状态密度、前沿分子轨道和最佳吸附能,以了解这些纳米结构的靶向给药潜力。吸附能分析表明,在气体和水介质中,所有共轭结构都能自发吸附 Mln 药物。吸附能是物理吸附能,这表明吸附过程是可逆的,只需输入更少的能量就能解吸。这种物理接触适合将 Mln 药物毫无疑问地卸载到预定位置。BNNS 和 BNCNS 的反应活性更高,而 BNCNC 的稳定性更高。BNNSs 和 BNCNSs 的恢复时间较短,而 BNCNC 在较高温度下的解吸时间较长。这些结论得到了分子中原子量子理论(QTAIM)结果的证实。经过相互作用分析,发现 BNCNCs 可作为美法仑的潜在载体。通过偶极矩分析,三种纳米结构都显示出较高的亲水性,但在两种介质中掺杂后,BNCNCs 的亲水性更高。总体而言,所有结构都显示出了美法仑药物载体的潜力:方法:采用量子力学方法(即 DFT)研究了拟议结构的基本结构、电学、热力学和其他方面,以开发一种可接受的美仑药物检测器。在吸附过程之前,通过混合 B3LYP 函数和 6-311G + + (2d, p) 基集方法对吸附剂和所有吸附剂进行了优化。采用高斯 09 软件包,以 298 K 为恒温,1 atm 为恒压。使用用于溶解分析的相同函数模型-6-311 G + + (2d, p) 和 B3LYP 以及极化连续模型 (PCM) 模型作为基础集,对结构进行了研究。使用 GaussSum 3.0 软件对状态密度进行了研究。使用 VMD 和 Multiwfn 软件研究了 QTAIM 和 RDG 的相互作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Incrimination and impact on recovery times and effects of BN nanostructures on antineoplastic drug-electronic density study

Context

By delivering the drug to the intended cell location, the use of nanomaterials in the drug delivery system may influence how the patient receives the medication and may assist in mitigating severe side effects. Density functional theory was used to assess the use of boron carbon nitride nanocages (BNCNCs), boron nitride (BNNSs), and boron carbon nitride nanosheets (BNCNSs) as melphalan (Mln) drug carriers in both the gaseous and fluid phases. We systematically examined the dipole moment, density of states, frontier molecular orbital, and optimal adsorption energy to understand the targeted drug delivery potential of these nanostructures. Adsorption energy analysis revealed that in both gas and water media, Mln drug adsorption takes place spontaneously on all the conjugated structures. The occurrence of adsorption energy as physisorbed energy suggests that the process is reversible, and desorption can take place with a much lower energy input. This physical contact is appropriate for the unquestionable unloading of Mln medications to the intended location. The reactivity is higher in BNNSs and BNCNSs, while the stability is higher in BNCNCs. The recovery time shows a shorter time for BNNSs and BNCNSs, while BNCNC shows a potential desorption time in higher temperature. These conclusions are corroborated by the results of the quantum theory of atoms in molecules (QTAIM). After the interaction analysis, it was observed that the BNCNCs can act as potential carriers for the melphalan. From dipole moment analysis, all three nanostructures show a high hydrophilic nature but quite higher in BNCNCs after doping in both media. Overall, all the structures show the potential carrier for melphalan drug.

Methods

The quantum mechanical approach, or DFT, has been used to study the fundamental structural, electrical, thermodynamic, and other aspects of proposed structures to develop an acceptable Mln drug detector. The adsorbate and all adsorbents were optimized via the hybrid B3LYP functional and the 6-311G +  + (2d, p) basis set approach prior to the adsorption process. The Gaussian 09 package was used at 298 K as the constant temperature and 1 atm as the constant pressure. The structures are examined using the same functional models for solvation analysis—6–311 G +  + (2d, p) and B3LYP—as well as the polarized continuum model (PCM) model as the foundation set. Density of states was studied using GaussSum 3.0 software. The interaction studies QTAIM and RDG were studied using VMD and Multiwfn software.

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来源期刊
Journal of Molecular Modeling
Journal of Molecular Modeling 化学-化学综合
CiteScore
3.50
自引率
4.50%
发文量
362
审稿时长
2.9 months
期刊介绍: The Journal of Molecular Modeling focuses on "hardcore" modeling, publishing high-quality research and reports. Founded in 1995 as a purely electronic journal, it has adapted its format to include a full-color print edition, and adjusted its aims and scope fit the fast-changing field of molecular modeling, with a particular focus on three-dimensional modeling. Today, the journal covers all aspects of molecular modeling including life science modeling; materials modeling; new methods; and computational chemistry. Topics include computer-aided molecular design; rational drug design, de novo ligand design, receptor modeling and docking; cheminformatics, data analysis, visualization and mining; computational medicinal chemistry; homology modeling; simulation of peptides, DNA and other biopolymers; quantitative structure-activity relationships (QSAR) and ADME-modeling; modeling of biological reaction mechanisms; and combined experimental and computational studies in which calculations play a major role.
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