Wenjun Wang1, Tianlong Liu2, Liudi Yang3, Yang Ma4, Fang Dou5, Lei Shi6, Aidong Wen7, Yi Ding8. 1. Department of Pharmacy, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China; College of Pharmacy, Shaanxi University of Chinese Medicine, Xi'an, 712000, China. 2. Department of Pharmacy, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China; Department of Pharmacy, 940 Hospital of PLA Joint Logistics Support Forces, Lanzhou, 730050, China. 3. Department of Acupuncture-moxibustion-massage, Shaanxi University of Chinese Medicine, Xi'an, 712000, China. 4. College of Pharmacy, Shaanxi University of Chinese Medicine, Xi'an, 712000, China. 5. Department of Pharmacy, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China. 6. Department of Pharmacy, Guangzhou General Hospital of Guangzhou Military Command, Guangzhou, 510000, China. 7. Department of Pharmacy, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China. Electronic address: adwen-2004@hotmail.com. 8. Department of Pharmacy, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China; Department of Pharmacy, Guangzhou General Hospital of Guangzhou Military Command, Guangzhou, 510000, China. Electronic address: dingyi.007@163.com.
Abstract
BACKGROUND & AIMS: Numerous references made clear that Triphala is revered as a multiuse therapeutic and perhaps even panacea historically. Nevertheless, the protective mechanism of Triphala on cardio-cerebral vascular diseases (CCVDs) remains not comprehensive understanding. Hence, a network pharmacology-based method was suggested in this study to address this problem. METHODS: This study was based on network pharmacology and bioinformatics analysis. Information on compounds in herbal medicines of Triphala formula was acquired from public databases. Oral bioavailability as well as drug-likeness were screened by using absorption, distribution, metabolism, and excretion (ADME) criteria. Then, components of Triphala, candidate targets of each component and known therapeutic targets of CCVDs were collected. Compound-target gene and compounds-CCVDs target networks were created through network pharmacology data sources. In addition, key targets and pathway enrichment were analyzed by STRING database and DAVID database. Moreover, we verified three of the key targets (PTGS2, MMP9 and IL6) predicted by using western blot analysis. RESULTS: Network analysis determined 132 compounds in three herbal medicines that were subjected to ADME screening, and 23 compounds as well as 65 genes formed the principal pathways linked to CCVDs. And 10 compounds, which actually linked to more than three genes, are determined as crucial chemicals. Core genes in this network were IL6, TNF, VEGFA, PTGS2, CXCL8, TP53, CCL2, IL10, MMP9 and SERPINE1. And pathways in cancer, TNF signaling pathway, neuroactive ligand-receptor interaction, etc. related to CCVDs were identified. In vitro experiments, the results indicated that compared with the control group (no treatment), PTGS2, MMP9 and IL6 were up-regulated by treatment of 10 ng/mL TNF-α, while pretreatment with 20-80 μg/mL Triphala could significantly inhibit the expression of PTGS2, MMP9 and IL6. With increasing Triphala concentration, the expression of PTGS2, MMP9 and IL6 decreased. CONCLUSIONS: This study revealed the complex components and pharmacological mechanism of Triphala, and obtained some potential therapeutic targets of CCVDs, which could provide theoretical basis for the research and development of new drugs for treating CCVDs.
BACKGROUND & AIMS: Numerous references made clear that Triphala is revered as a multiuse therapeutic and perhaps even panacea historically. Nevertheless, the protective mechanism of Triphala on cardio-cerebral vascular diseases (CCVDs) remains not comprehensive understanding. Hence, a network pharmacology-based method was suggested in this study to address this problem. METHODS: This study was based on network pharmacology and bioinformatics analysis. Information on compounds in herbal medicines of Triphala formula was acquired from public databases. Oral bioavailability as well as drug-likeness were screened by using absorption, distribution, metabolism, and excretion (ADME) criteria. Then, components of Triphala, candidate targets of each component and known therapeutic targets of CCVDs were collected. Compound-target gene and compounds-CCVDs target networks were created through network pharmacology data sources. In addition, key targets and pathway enrichment were analyzed by STRING database and DAVID database. Moreover, we verified three of the key targets (PTGS2, MMP9 and IL6) predicted by using western blot analysis. RESULTS: Network analysis determined 132 compounds in three herbal medicines that were subjected to ADME screening, and 23 compounds as well as 65 genes formed the principal pathways linked to CCVDs. And 10 compounds, which actually linked to more than three genes, are determined as crucial chemicals. Core genes in this network were IL6, TNF, VEGFA, PTGS2, CXCL8, TP53, CCL2, IL10, MMP9 and SERPINE1. And pathways in cancer, TNF signaling pathway, neuroactive ligand-receptor interaction, etc. related to CCVDs were identified. In vitro experiments, the results indicated that compared with the control group (no treatment), PTGS2, MMP9 and IL6 were up-regulated by treatment of 10 ng/mL TNF-α, while pretreatment with 20-80 μg/mL Triphala could significantly inhibit the expression of PTGS2, MMP9 and IL6. With increasing Triphala concentration, the expression of PTGS2, MMP9 and IL6 decreased. CONCLUSIONS: This study revealed the complex components and pharmacological mechanism of Triphala, and obtained some potential therapeutic targets of CCVDs, which could provide theoretical basis for the research and development of new drugs for treating CCVDs.
Authors: Chun Li; Xia Du; Yang Liu; Qi-Qi Liu; Wen Bing Zhi; Chun Liu Wang; Jie Zhou; Ye Li; Hong Zhang Journal: Evid Based Complement Alternat Med Date: 2020-01-08 Impact factor: 2.629