Grienke Ulrike, Kaserer Teresa, Pfluger Florian, Mair Christina E, Langer Thierry, Schuster Daniela, Rollinger Judith M
Institute of Pharmacy/Pharmacognosy and Center for Molecular Biosciences Innsbruck, University of Innsbruck, Innrain 80-82, 6020 Innsbruck, Austria.
Institute of Pharmacy/Pharmaceutical Chemistry, Computer-Aided Molecular Design Group, Center for Molecular Biosciences Innsbruck, University of Innsbruck, Innrain 80-82, 6020 Innsbruck, Austria.
Phytochemistry. 2015 Jun;114:114-24. doi: 10.1016/j.phytochem.2014.10.010. Epub 2014 Nov 6.
The species complex around the medicinal fungus Ganoderma lucidum Karst. (Ganodermataceae) is widely known in traditional medicines, as well as in modern applications such as functional food or nutraceuticals. A considerable number of publications reflects its abundance and variety in biological actions either provoked by primary metabolites, such as polysaccharides, or secondary metabolites, such as lanostane-type triterpenes. However, due to this remarkable amount of information, a rationalization of the individual Ganoderma constituents to biological actions on a molecular level is quite challenging. To overcome this issue, a database was generated containing meta-information, i.e., chemical structures and biological actions of hitherto identified Ganoderma constituents (279). This was followed by a computational approach subjecting this 3D multi-conformational molecular dataset to in silico parallel screening against an in-house collection of validated structure- and ligand-based 3D pharmacophore models. The predictive power of the evaluated in silico tools and hints from traditional application fields served as criteria for the model selection. Thus, the focus was laid on representative druggable targets in the field of viral infections (5) and diseases related to the metabolic syndrome (22). The results obtained from this in silico approach were compared to bioactivity data available from the literature. 89 and 197 Ganoderma compounds were predicted as ligands of at least one of the selected pharmacological targets in the antiviral and the metabolic syndrome screening, respectively. Among them only a minority of individual compounds (around 10%) has ever been investigated on these targets or for the associated biological activity. Accordingly, this study discloses putative ligand target interactions for a plethora of Ganoderma constituents in the empirically manifested field of viral diseases and metabolic syndrome which serve as a basis for future applications to access yet undiscovered biological actions of Ganoderma secondary metabolites on a molecular level.
围绕药用真菌灵芝(多孔菌科)的物种复合体在传统医学以及现代应用(如功能性食品或营养保健品)中广为人知。大量出版物反映了其在由初级代谢产物(如多糖)或次级代谢产物(如羊毛甾烷型三萜)引发的生物活性方面的丰富性和多样性。然而,由于信息量巨大,要在分子水平上使灵芝的各个成分与生物活性合理化颇具挑战性。为克服这一问题,生成了一个数据库,其中包含元信息,即迄今已鉴定的灵芝成分(279种)的化学结构和生物活性。随后采用一种计算方法,将这个三维多构象分子数据集针对内部收集的经过验证的基于结构和配体的三维药效团模型进行虚拟平行筛选。评估的虚拟工具的预测能力以及传统应用领域的提示作为模型选择的标准。因此,重点放在了病毒感染领域(5种)和与代谢综合征相关疾病(22种)的代表性可成药靶点上。将这种虚拟方法获得的结果与文献中可得的生物活性数据进行比较。在抗病毒和代谢综合征筛选中,分别有89种和197种灵芝化合物被预测为所选药理学靶点中至少一种的配体。其中,只有少数个别化合物(约10%)曾在这些靶点上或针对相关生物活性进行过研究。因此,本研究揭示了在经验证的病毒疾病和代谢综合征领域中大量灵芝成分的假定配体 - 靶点相互作用,这为未来在分子水平上探索灵芝次级代谢产物尚未发现的生物活性的应用奠定了基础。