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Uncovering the Pharmacological Mechanism of Stemazole in the Treatment of Neurodegenerative Diseases Based on a Network Pharmacology Approach.

ABSTRACT: Stemazole exerts potent pharmacological effects against neurodegenerative diseases and protective effects in stem cells. However, on the basis of the current understanding, the molecular mechanisms underlying the effects of stemazole in the treatment of Alzheimer's disease and Parkinson's disease have not been fully elucidated. In this study, a network pharmacology-based strategy integrating target prediction, network construction, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, and molecular docking was adopted to predict the targets of stemazole relevant to the treatment of neurodegenerative diseases and to further explore the involved pharmacological mechanisms. The majority of the predicted targets were highly involved in the mitogen-activated protein kinase (MAPK) signaling pathway. RAC-alpha serine/threonine-protein kinase (AKT1), caspase-3 (CASP3), caspase-8 (CASP8), mitogen-activated protein kinase 8 (MAPK8), and mitogen-activated protein kinase 14 (MAPK14) are the core targets regulated by stemazole and play a central role in its anti-apoptosis effects. This work provides a scientific basis for further elucidating the mechanism underlying the effects of stemazole in the treatment of neurodegenerative diseases.

SUBMITTER: Zhang J

PROVIDER: S-EPMC7013392 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Uncovering the Pharmacological Mechanism of Stemazole in the Treatment of Neurodegenerative Diseases Based on a Network Pharmacology Approach.

Zhang Jing J Li Huajun H Zhang Yubo Y Zhao Chaoran C Zhu Yizi Y Han Mei M

International journal of molecular sciences 20200109 2

Stemazole exerts potent pharmacological effects against neurodegenerative diseases and protective effects in stem cells. However, on the basis of the current understanding, the molecular mechanisms underlying the effects of stemazole in the treatment of Alzheimer's disease and Parkinson's disease have not been fully elucidated. In this study, a network pharmacology-based strategy integrating target prediction, network construction, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes ( ...[more]

PMID: 31936558

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Project description:Traditional Chinese medicine (TCM) with the characteristics of "multi-component-multi-target-multi-pathway" has obvious advantages in the prevention and treatment of complex diseases, especially in the aspects of "treating the same disease with different treatments". However, there are still some problems such as unclear substance basis and molecular mechanism of the effectiveness of formula. Network pharmacology is a new strategy based on system biology and poly-pharmacology, which could observe the intervention of drugs on disease networks at systematical and comprehensive level, and especially suitable for study of complex TCM systems. Rheumatoid arthritis (RA) is a chronic inflammatory autoimmune disease, causing articular and extra articular dysfunctions among patients, it could lead to irreversible joint damage or disability if left untreated. TCM formulas, Danggui-Sini-decoction (DSD), Guizhi-Fuzi-decoction (GFD), and Huangqi-Guizhi-Wuwu-Decoction (HGWD), et al., have been found successful in controlling RA in clinical applications. Here, a network pharmacology-based approach was established. With this model, key gene network motif with significant (KNMS) of three formulas were predicted, and the molecular mechanism of different formula in the treatment of rheumatoid arthritis (RA) was inferred based on these KNMSs. The results show that the KNMSs predicted by the model kept a high consistency with the corresponding C-T network in coverage of RA pathogenic genes, coverage of functional pathways and cumulative contribution of key nodes, which confirmed the reliability and accuracy of our proposed KNMS prediction strategy. All validated KNMSs of each RA therapy-related formula were employed to decode the mechanisms of different formulas treat the same disease. Finally, the key components in KNMSs of each formula were evaluated by in vitro experiments. Our proposed KNMS prediction and validation strategy provides methodological reference for interpreting the optimization of core components group and inference of molecular mechanism of formula in the treatment of complex diseases in TCM.

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Dataset Information

Uncovering the Pharmacological Mechanism of Stemazole in the Treatment of Neurodegenerative Diseases Based on a Network Pharmacology Approach.

Publications

Uncovering the Pharmacological Mechanism of Stemazole in the Treatment of Neurodegenerative Diseases Based on a Network Pharmacology Approach.

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