开发含有糜棱草的植物治疗纳米制剂,并将其作为治疗骨质疏松症的候选制剂对人类骨髓干细胞进行评估。

IF 3 3区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS
Sibel Kaymak, Ozan Baris Kurtur, Bahar Gok, Yasemin Budama-Kilinc, Serda Kecel-Gunduz, Ebru Özdemir Nath, Murat Kartal
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引用次数: 0

摘要

导言骨质疏松症是常见的骨科疾病之一,表现为骨量减少。最近,利用药用植物寻找预防或治疗骨质疏松症的有效低毒疗法已成为一个热门话题:在本研究中,我们旨在制备一种装载有麦饭石的可控药物载体系统,以确定其在抗骨质疏松症方面的应用潜力:方法:制备麦角石膏提取物(GEE)并测定其成分。通过分子对接和 MD 方法揭示了这些成分与 Cathepsin K(CatK)的分子相互作用,CatK 是骨质疏松症药物开发中的一个靶点。此外,还研究了 ADMET 特性。合成了负载 GEE 的壳聚糖纳米颗粒(CNPs)。测定了纳米颗粒的形态、包封效率、负载能力、释放曲线、平均粒径、多分散指数和 zeta 电位。研究了 GEE 和 GEE 负载 CNPs 对 L929 细胞和人骨髓干细胞(hBMC)成骨增殖曲线的细胞毒性效应:MD 分析显示动态系统中没有断裂或原子变化,对接分析证实相同残基继续相互作用。结果:MD 分析表明,动态体系中的原子没有发生断裂,对接分析证实了相同残基之间的持续相互作用。结果表明,GEE 负载 CNP 制剂生产成功,对 L929 没有毒性作用,对 hBMC 具有成骨增殖作用:根据所获得的体外和硅学结果,评估认为 GEE 负载 CNP 可用作药物控释系统,作为具有植物治疗特性的候选制剂用于骨质疏松症治疗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Development of phytotherapeutic nanoformulation containing Gypsophila eriocalyx and its evaluation as a candidate formulation for osteoporosis treatment on human bone marrow stem cells.

Introduction: Osteoporosis, one of the common bone diseases, manifests itself as a decrease in bone mass. Recently, the use of medicinal plants in the search for effective and low-toxicity therapeutics for the prevention or treatment of osteoporosis has become a trending topic.

Objective: In this study, we aim to prepare a controlled drug carrier system loaded with Gypsophila eriocalyx to determine its potential for anti-osteoporosis applications.

Methods: Gypsophila eriocalyx extract (GEE) was prepared, and components were determined. The molecular interactions of the components with Cathepsin K (CatK), which is used as a target in drug development against osteoporosis, were revealed by in silico molecular docking and MD methods. ADMET profiles were also examined. GEE-loaded chitosan nanoparticles (CNPs) were synthesized. The nanoparticles' morphology, encapsulation efficiency, loading capacity, release profile, average size, polydispersity index, and zeta potentials were determined. The cytotoxic effects of GEE and GEE-loaded CNPs on the L929 and osteogenic proliferation profiles on human bone marrow stem cells (hBMC) were examined.

Results: The MD analysis revealed no breaks or atomic changes in the dynamic system, and the docking analysis confirmed the continued interaction of identical residues. It was determined that the GEE-loaded CNP formulation was produced successfully, had no toxic effect on the L929, and had an osteogenic proliferation effect on hBMC.

Conclusion: In line with the in vitro and in silico results obtained, it was evaluated that GEE-loaded CNPs can be used as a controlled drug release system as a candidate formulation with phytotherapeutic properties for osteoporosis treatment.q1.

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来源期刊
Phytochemical Analysis
Phytochemical Analysis 生物-分析化学
CiteScore
6.00
自引率
6.10%
发文量
88
审稿时长
1.7 months
期刊介绍: Phytochemical Analysis is devoted to the publication of original articles concerning the development, improvement, validation and/or extension of application of analytical methodology in the plant sciences. The spectrum of coverage is broad, encompassing methods and techniques relevant to the detection (including bio-screening), extraction, separation, purification, identification and quantification of compounds in plant biochemistry, plant cellular and molecular biology, plant biotechnology, the food sciences, agriculture and horticulture. The Journal publishes papers describing significant novelty in the analysis of whole plants (including algae), plant cells, tissues and organs, plant-derived extracts and plant products (including those which have been partially or completely refined for use in the food, agrochemical, pharmaceutical and related industries). All forms of physical, chemical, biochemical, spectroscopic, radiometric, electrometric, chromatographic, metabolomic and chemometric investigations of plant products (monomeric species as well as polymeric molecules such as nucleic acids, proteins, lipids and carbohydrates) are included within the remit of the Journal. Papers dealing with novel methods relating to areas such as data handling/ data mining in plant sciences will also be welcomed.
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