Wang Le, Tan Nana, Hu Jiayao, Wang Huan, Duan Dongzhu, Ma Lin, Xiao Jian, Wang Xiaoling
Shaanxi Key Laboratory of Phytochemistry, College of Chemistry and Chemical Engineering, Baoji University of Arts and Sciences, Baoji, Shaanxi, 721013, China.
BMC Syst Biol. 2017 Dec 28;11(1):144. doi: 10.1186/s12918-017-0523-0.
Osmanthus fragrans has been used as folk medicine for thousands of years. The extracts of Osmanthus fragrans flowers were reported to have various bioactivities including free radical scavenging, anti-inflammation, neuroprotection and antitumor effects. However, there is still lack of knowledge about its essential oil.
In this work, we analyzed the chemical composition of the essential oil from Osmanthus fragrans var. thunbergii by GC-MS. A complex network approach was applied to investigate the interrelationships between the ingredients, target proteins, and related pathways for the essential oil. Statistical characteristics of the networks were further studied to explore the main active ingredients and potential bioactivities of O. fragrans var. thunbergii essential oil.
A total of 44 ingredients were selected from the chemical composition of O. fragrans var. thunbergii essential oil, and that 191 potential target proteins together with 70 pathways were collected for these compounds. An ingredient-target-pathway network was constructed based on these data and showed scale-free property as well as power-law degree distribution. Eugenol and geraniol were screened as main active ingredients with much higher degree values. Potential neuroprotective and anti-tumor effect of the essential oil were also found. A core subnetwork was extracted from the ingredient-target-pathway network, and indicated that eugenol and geraniol contributed most to the neuroprotection of this essential oil. Furthermore, a pathway-based protein association network was built and exhibited small-world property. MAPK1 and MAPK3 were considered as key proteins with highest scores of centrality indices, which might play an important role in the anti-tumor effect of the essential oil.
This work predicted the main active ingredients and bioactivities of O. fragrans var. thunbergii essential oil, which would benefit the development and utilization of Osmanthus fragrans flowers. The application of complex network theory was proved to be effective in bioactivities studies of essential oil. Moreover, it provides a novel strategy for exploring the molecular mechanisms of traditional medicines.
桂花作为民间药物已使用了数千年。据报道，桂花花提取物具有多种生物活性，包括自由基清除、抗炎、神经保护和抗肿瘤作用。然而，关于其精油仍缺乏了解。
在本研究中，我们通过气相色谱 - 质谱联用（GC-MS）分析了金桂变种精油的化学成分。应用复杂网络方法研究了该精油成分、靶蛋白和相关通路之间的相互关系。进一步研究网络的统计特征，以探索金桂变种精油的主要活性成分和潜在生物活性。
从金桂变种精油的化学成分中总共筛选出44种成分，并为这些化合物收集了191个潜在靶蛋白和70条通路。基于这些数据构建了成分 - 靶标 - 通路网络，该网络具有无标度特性和幂律度分布。丁香酚和香叶醇被筛选为具有更高度值的主要活性成分。还发现了该精油潜在的神经保护和抗肿瘤作用。从成分 - 靶标 - 通路网络中提取了一个核心子网，表明丁香酚和香叶醇对该精油的神经保护作用贡献最大。此外，构建了一个基于通路的蛋白质关联网络，该网络具有小世界特性。丝裂原活化蛋白激酶1（MAPK1）和丝裂原活化蛋白激酶3（MAPK3）被认为是具有最高中心性指数得分的关键蛋白，它们可能在该精油的抗肿瘤作用中发挥重要作用。
本研究预测了金桂变种精油的主要活性成分和生物活性，这将有利于桂花的开发利用。证明了复杂网络理论在精油生物活性研究中的有效性。此外，它为探索传统药物的分子机制提供了一种新策略。
