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A network pharmacology analysis on drug-like compounds from Ganoderma lucidum for alleviation of atherosclerosis
Journal of Food Biochemistry ( IF 3.5 ) Pub Date : 2021-08-18 , DOI: 10.1111/jfbc.13906 Ki Kwang Oh 1 , Md Adnan 1 , Dong Ha Cho 1
Journal of Food Biochemistry ( IF 3.5 ) Pub Date : 2021-08-18 , DOI: 10.1111/jfbc.13906 Ki Kwang Oh 1 , Md Adnan 1 , Dong Ha Cho 1
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Ganoderma lucidum (GL) is known as a potent alleviator against chronic inflammatory disease like atherosclerosis (AS), but its mechanisms against AS have not been unveiled. This research aimed to identify the key compounds(s) and mechanism(s) of GL against AS through network pharmacology. The compounds from GL were identified by gas chromatography–mass spectrum (GC-MS), and SwissADME screened their physicochemical properties. Then, the target(s) associated with the screened compound(s) or AS related targets were identified by public databases, and we selected the overlapping targets using a Venn diagram. The networks between overlapping targets and compounds were visualized, constructed, and analyzed by RStudio. Finally, we performed a molecular docking test (MDT) to explore key target(s), compound(s), on AutoDockVina. A total of 35 compounds in GL were detected via GC-MS, and 34 compounds (accepted by Lipinski's rule) were selected as drug-like compounds (DLCs). A total of 34 compounds were connected to the number of 785 targets, and DisGeNET and Online Mendelian Inheritance in Man (OMIM) identified 2,606 AS-related targets. The final 98 overlapping targets were extracted between the compounds-targets and AS-related targets. On Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, the number of 27 signaling pathways were sorted out, and a hub signaling pathway (MAPK signaling pathway), a core gene (PRKCA), and a key compound (Benzamide, 4-acetyl-N-[2,6-dimethylphenyl]) were selected among the 27 signaling pathways via MDT. Overall, we found that the identified 3 DLCs from GL have potent anti-inflammatory efficacy, improving AS by inactivating the MAPK signaling pathway.
中文翻译：
灵芝类药物缓解动脉粥样硬化的网络药理学分析
灵芝(GL) 被认为是对抗动脉粥样硬化 (AS) 等慢性炎症性疾病的有效缓解剂，但其对抗 AS 的机制尚未公开。本研究旨在通过网络药理学确定 GL 抗 AS 的关键化合物和机制。GL 中的化合物通过气相色谱-质谱 (GC-MS) 进行鉴定，SwissADME 筛选了它们的理化性质。然后，与筛选的化合物相关的目标或与 AS 相关的目标由公共数据库识别，我们使用维恩图选择重叠的目标。重叠目标和化合物之间的网络通过 RStudio 进行可视化、构建和分析。最后，我们进行了分子对接测试 (MDT)，以探索 AutoDockVina 上的关键目标、化合物。通过GC-MS共检测到GL中的35种化合物，其中34种化合物（符合Lipinski规则）被选为类药物化合物（DLCs）。总共有 34 种化合物与 785 个目标相关联，DisGeNET 和 Online Mendelian Inheritance in Man (OMIM) 确定了 2,606 个与 AS 相关的目标。在化合物目标和 AS 相关目标之间提取了最终的 98 个重叠目标。在京都基因与基因组百科全书（KEGG）通路富集上，梳理出27条信号通路，一个枢纽信号通路（MAPK信号通路），一个核心基因（PRKCA），一个关键化合物（苯甲酰胺，4-乙酰基-N-[2,6-二甲基苯基]) 通过 MDT 在 27 条信号通路中选择。总体而言，我们发现来自 GL 的 3 种 DLCs 具有强大的抗炎功效，
更新日期：2021-09-06
中文翻译：
灵芝类药物缓解动脉粥样硬化的网络药理学分析
灵芝(GL) 被认为是对抗动脉粥样硬化 (AS) 等慢性炎症性疾病的有效缓解剂，但其对抗 AS 的机制尚未公开。本研究旨在通过网络药理学确定 GL 抗 AS 的关键化合物和机制。GL 中的化合物通过气相色谱-质谱 (GC-MS) 进行鉴定，SwissADME 筛选了它们的理化性质。然后，与筛选的化合物相关的目标或与 AS 相关的目标由公共数据库识别，我们使用维恩图选择重叠的目标。重叠目标和化合物之间的网络通过 RStudio 进行可视化、构建和分析。最后，我们进行了分子对接测试 (MDT)，以探索 AutoDockVina 上的关键目标、化合物。通过GC-MS共检测到GL中的35种化合物，其中34种化合物（符合Lipinski规则）被选为类药物化合物（DLCs）。总共有 34 种化合物与 785 个目标相关联，DisGeNET 和 Online Mendelian Inheritance in Man (OMIM) 确定了 2,606 个与 AS 相关的目标。在化合物目标和 AS 相关目标之间提取了最终的 98 个重叠目标。在京都基因与基因组百科全书（KEGG）通路富集上，梳理出27条信号通路，一个枢纽信号通路（MAPK信号通路），一个核心基因（PRKCA），一个关键化合物（苯甲酰胺，4-乙酰基-N-[2,6-二甲基苯基]) 通过 MDT 在 27 条信号通路中选择。总体而言，我们发现来自 GL 的 3 种 DLCs 具有强大的抗炎功效，
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