Effect of Poria cocos Terpenes: Verifying Modes of Action Using Molecular Docking, Drug-Induced Transcriptomes, and Diffusion Network Analyses

• Published in: International journal of molecular sciences Vol. 25; no. 9; p. 4636
• Main Authors: Park, Musun, Yi, Jin-Mu, Kim, No Soo, Lee, Seo-Young, Lee, Haeseung
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 01.05.2024
• Subjects: Alzheimer Disease - drug therapy; Alzheimer Disease - genetics; Alzheimer Disease - metabolism; Alzheimer’s disease; Animals; Antioxidants; Antioxidants - chemistry; Antioxidants - pharmacology; Cardiomyopathy; Computational Biology - methods; Diabetes; diffusion network; Disease; Gene Expression Profiling - methods; Genes; Herbal medicine; Humans; Hypertension; Infections; Microglia - drug effects; Microglia - metabolism; molecular docking; Molecular Docking Simulation; Poria cocos; Proteins; terpenes; Terpenes - chemistry; Terpenes - pharmacology; transcriptome; Transcriptome - drug effects; Wolfiporia - chemistry; antioxidant; molecular docking; Alzheimer’s disease; Poria cocos; terpenes; transcriptome; diffusion network
• ISSN: 1422-0067; 1661-6596; 1422-0067
• DOI: 10.3390/ijms25094636

We characterized the therapeutic biological modes of action of several terpenes in F.A Wolf (PC) and proposed a broad therapeutic mode of action for PC. Molecular docking and drug-induced transcriptome analysis were performed to confirm the pharmacological mechanism of PC terpene, and a new analysis method, namely diffusion network analysis, was proposed to verify the mechanism of action against Alzheimer's disease. We confirmed that the compound that exists only in PC has a unique mechanism through statistical-based docking analysis. Also, docking and transcriptomic analysis results could reflect results in clinical practice when used complementarily. The detailed pharmacological mechanism of PC was confirmed by constructing and analyzing the Alzheimer's disease diffusion network, and the antioxidant activity based on microglial cells was verified. In this study, we used two bioinformatics approaches to reveal PC's broad mode of action while also using diffusion networks to identify its detailed pharmacological mechanisms of action. The results of this study provide evidence that future pharmacological mechanism analysis should simultaneously consider complementary docking and transcriptomics and suggest diffusion network analysis, a new method to derive pharmacological mechanisms based on natural complex compounds.