多药耐药蛋白P-gp与纳米颗粒(富勒烯和碳纳米管)相互作用以评估其药物传递潜力:理论分子对接研究。

Q4 Pharmacology, Toxicology and Pharmaceutics International Journal of Computational Biology and Drug Design Pub Date : 2013-01-01 Epub Date: 2013-09-30 DOI:10.1504/IJCBDD.2013.056801
Sergey Shityakov, Carola Förster
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引用次数: 27

摘要

p -糖蛋白(P-gp)介导的外排系统在维持哺乳动物细胞内源性和外源性化合物的化学平衡中起着重要作用。然而,尽管对P-gp与药物样分子的潜在相互作用进行了广泛的描述,但对碳纳米颗粒与这类蛋白质分子的相互作用知之甚少。因此,研究人员利用不同的分子对接技术,如梯度优化算法(ADVina)、拉马克遗传算法(FastDock)和基于形状的方法(PatchDock),分析了巴克敏斯特富勒烯(C20、C60、C70)、带帽单壁碳纳米管(SWCNT或C168)和P-gp相互作用等碳纳米颗粒,以估计这些结构之间的结合亲和力。本研究的理论结果表明,富勒烯可能是P-gp结合剂,因为它的吉布斯自由结合能(ΔG)和平均力势(PMF)值较低。此外,swcnts的结合在能量上是不利的,导致剩余面积(Ares)的升高导致结合亲和力的总体降低,这也影响了π-π堆积机制。此外,获得的数据可能潜在地调用使用碳纳米结构的实验研究,例如用于开发药物递送载体的swcnts,来管理和评估药物样化合物到靶细胞,因为生物体可能没有开发出分子传感元件来检测这些类型的碳分子。
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Multidrug resistance protein P-gp interaction with nanoparticles (fullerenes and carbon nanotube) to assess their drug delivery potential: a theoretical molecular docking study.

P-glycoprotein (P-gp)-mediated efflux system plays an important role to maintain chemical balance in mammalian cells for endogenous and exogenous chemical compounds. However, despite the extensive characterisation of P-gp potential interaction with drug-like molecules, the interaction of carbon nanoparticles with this type of protein molecule is poorly understood. Thus, carbon nanoparticles were analysed, such as buckminsterfullerenes (C20, C60, C70), capped armchair single-walled carbon nanotube (SWCNT or C168), and P-gp interactions using different molecular docking techniques, such as gradient optimisation algorithm (ADVina), Lamarckian genetic algorithm (FastDock), and shape-based approach (PatchDock) to estimate the binding affinities between these structures. The theoretical results represented in this work show that fullerenes might be P-gp binders because of low levels of Gibbs free energy of binding (ΔG) and potential of mean force (PMF) values. Furthermore, the SWCNT binding is energetically unfavourable, leading to a total decrease in binding affinity by elevation of the residual area (Ares), which also affects the π-π stacking mechanisms. Further, the obtained data could potentially call experimental studies using carbon nanostructures, such as SWCNT for development of drug delivery vehicles, to administer and assess drug-like chemical compounds to the target cells since organisms probably did not develop molecular sensing elements to detect these types of carbon molecules.

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来源期刊
International Journal of Computational Biology and Drug Design
International Journal of Computational Biology and Drug Design Pharmacology, Toxicology and Pharmaceutics-Drug Discovery
CiteScore
1.00
自引率
0.00%
发文量
8
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