Dataset Information

Modular Characteristics and Mechanism of Action of Herbs for Endometriosis Treatment in Chinese Medicine: A Data Mining and Network Pharmacology-Based Identification.

ABSTRACT: Endometriosis is a common benign disease in women of reproductive age. It has been defined as a disorder characterized by inflammation, compromised immunity, hormone dependence, and neuroangiogenesis. Unfortunately, the mechanisms of endometriosis have not yet been fully elucidated, and available treatment methods are currently limited. The discovery of new therapeutic drugs and improvements in existing treatment schemes remain the focus of research initiatives. Chinese medicine can improve the symptoms associated with endometriosis. Many Chinese herbal medicines could exert antiendometriosis effects via comprehensive interactions with multiple targets. However, these interactions have not been defined. This study used association rule mining and systems pharmacology to discover a method by which potential antiendometriosis herbs can be investigated. We analyzed various combinations and mechanisms of action of medicinal herbs to establish molecular networks showing interactions with multiple targets. The results showed that endometriosis treatment in Chinese medicine is mainly based on methods of supplementation with blood-activating herbs and strengthening qi. Furthermore, we used network pharmacology to analyze the main herbs that facilitate the decoding of multiscale mechanisms of the herbal compounds. We found that Chinese medicine could affect the development of endometriosis by regulating inflammation, immunity, angiogenesis, and other clusters of processes identified by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. The antiendometriosis effect of Chinese medicine occurs mainly through nervous system-associated pathways, such as the serotonergic synapse, the neurotrophin signaling pathway, and dopaminergic synapse, among others, to reduce pain. Chinese medicine could also regulate VEGF signaling, toll-like reporter signaling, NF-?B signaling, MAPK signaling, PI3K-Akt signaling, and the HIF-1 signaling pathway, among others. Synergies often exist in herb pairs and herbal prescriptions. In conclusion, we identified some important targets, target pairs, and regulatory networks, using bioinformatics and data mining. The combination of data mining and network pharmacology may offer an efficient method for drug discovery and development from herbal medicines.

SUBMITTER: Zheng W

PROVIDER: S-EPMC7069061 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Modular Characteristics and Mechanism of Action of Herbs for Endometriosis Treatment in Chinese Medicine: A Data Mining and Network Pharmacology-Based Identification.

Zheng Weilin W Wu Jiayi J Gu Jiangyong J Weng Heng H Wang Jie J Wang Tao T Liang Xuefang X Cao Lixing L

Frontiers in pharmacology 20200306

Endometriosis is a common benign disease in women of reproductive age. It has been defined as a disorder characterized by inflammation, compromised immunity, hormone dependence, and neuroangiogenesis. Unfortunately, the mechanisms of endometriosis have not yet been fully elucidated, and available treatment methods are currently limited. The discovery of new therapeutic drugs and improvements in existing treatment schemes remain the focus of research initiatives. Chinese medicine can improve the ...[more]

PMID: 32210799

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Project description:Type 2 diabetes (T2D) has emerged as a global epidemic, and conventional treatment approaches often face limitations in achieving long-term glycemic control and preventing complications. Traditional Chinese Medicine (TCM) offers a valuable alternative for managing T2D, with a long history of effectively using herbal formulations in clinical practice. However, the modular characteristics of these herbs and their specific mechanisms of action remain poorly understood. To comprehensively investigate the modular characteristics and mechanisms of Chinese herbs in treating T2D, as well as explore the synergistic interactions among different herbs and their modular components, we employed data mining, systematic pharmacology, and molecular docking. Our aim was to gain a comprehensive understanding of the potential therapeutic targets and pathways involved in herbal T2D treatment. In this study, a total of 1114 studies investigating the effects of TCM interventions in the treatment of T2D in adults were included. The analysis revealed 170 distinct types of Chinese herbs, 118 active components, and 238 common targets shared between the medicine and T2D. Additionally, this study identified six hub proteins (TNF, MMP2, PTGS, CASP3, CASP8, and CASP9) and two key chemicals (Diosgenin and Formononetin) found in TCM-mediated T2D suppression. It was observed that these proteins could bind with the ingredients. The MMP2-Diosgenin interaction exhibited the lowest binding free energy (-13.05 kJ/mol) and was primarily driven by hydrogen bonds with ALA-165. TNF-Diosgenin (-10.5 kcal/mol) showed three hydrogen bonds with LEU-37, ARG-82, and ASN-30. PTGS2 and Diosgenin (-8.71 kJ/mol) demonstrated a hydrogen bond with HIS-214. Furthermore, CASP9-Formononetin (-6.53 kcal/mol) exhibited the lowest binding free energy and hydrogen bonds with GLU-261 and SER-339 as the primary forces involved. CASP3-Formononetin (-6.07 kcal/mol) displayed three hydrogen bonds with ASN-342, TRP-348, and GLU-379. Lastly, CASP8 and Formononetin (-6.06 kJ/mol) formed a hydrogen bond with THR-390, TYR-392, and TYR-334. Moreover, critical therapeutic pathways, such as the immune inflammatory response, AGE-RAGE, and IL-17 signaling pathway, were found to be associated with T2D Chinese herb therapy. In conclusion, this study sheded light on the modular characteristics and mechanism of action of herbs used in Chinese Medicine for the treatment of T2D, which provided valuable insights for both researchers and practitioners in the field of Chinese Medicine, offering potential avenues for improved treatment strategies and personalized approaches to address the complex nature of T2D.

Project description:BackgroundTraditional Chinese medicine (TCM) is increasingly extensively being applied as a complementary and alternative therapy for gastric cancer (GC); however, there is a lack of large-scale evidence-based deep learning for the guidance of its clinical prescription.MethodsThe combinational search terms of "Gastric cancer and/or gastric malignancy" and "Traditional Chinese Medicine" were used to retrieve clinical study-based herbal prescriptions from public database over the past 3 decades [1990-2020]. Association rules mining (ARM) was used to analyze the prescription patterns of the herbs extracted from the eligible studies. Deep machine learning and computational prediction were conducted to explore candidate prescriptions with general applicability for GC. The action mechanism of the preferred prescription was investigated through network pharmacology, and further validated via in vivo and in vitro experiments.ResultsA total of 194 clinical study-based herbal prescriptions with good efficacy for GC were collected. TCM with focus on invigorating the Spleen and tonifying the vital-Qi is a promising adjuvant therapy for GC. The preferred prescription is composed of Atractylodis Macrocephalae Rhizoma, Astragali Radix, Pinelliae Rhizoma, Citri Reticulatae Pericarpium, Herba Hedyotidis Diffusae, Crataegi Fructus, and so on. We screened 74 bioactive compounds and 2,128 predictive targets of the preferred prescription from public databases. Eventually, 135 GC-related genes were identified as the targets of the preferred prescription. The compound-target network revealed that the crucial substances in the preferred prescription are quercetin, kaempferol, baicalein, and nobiletin. Experimentally, the preferred prescription was validated to modulate GC cell survival and inhibit tumor progression mainly via the hTERT/MDM2-p53 signaling pathway in vivo and in vitro.ConclusionsTCM aimed at invigorating the Spleen and tonifying the vital-Qi is a promising adjuvant therapy for GC, which offers a guidance for worldwide use of TCM in the treatment of GC.

Project description:Colorectal cancer (CRC) is now the second most deadly cancer globally. Chinese herbal medicine (CHM) plays an indispensable role in CRC treatment in China. However, the core herbs (the CHs) in the treatment of CRC and their underlying therapeutic mechanisms remain unclear. This study aims to uncovering the CHs and their mechanisms of action of CRC treatment, applying data mining and network pharmacology approach. First, CHM prescriptions treating CRC were collected from clinical studies from the Chinese National Knowledge Infrastructure (CNKI) and MEDLINE databases, and the CHs were identified through data mining. Then, the bioactive compounds and the corresponding putative targets of the CHs were obtained from three traditional Chinese medicine (TCM) databases. CRC related targets were acquired from three disease databases; the overlapping targets between the CHs and CRC were identified as the therapeutic targets. Subsequently, functional enrichment analysis was performed to elucidate the mechanisms of the CHs on CRC. Moreover, networks were constructed to screen the major bioactive compounds and therapeutic targets. Finally, prognostic values of the major target genes were evaluated by survival analysis, and molecular docking simulation was performed to assess the binding affinity of key targets and major bioactive compounds. It came out that 10 the CHs from 113 prescriptions and 190 bioactive compounds with 118 therapeutic targets were identified. The therapeutic targets were mainly enriched in the biological progress of transcription, apoptosis, and response to cytokine. Various cancer-associated signaling pathways, including microRNAs, TNF, apoptosis, PI3K-Akt, and p53, were involved. Furthermore, 15 major bioactive compounds and five key target genes (VEGFA, CASP3, MYC, CYP1Y1, and NFKB1) with prognostic significance were identified. Additionally, most major bioactive compounds might bind firmly to the key target proteins. This study provided an overview of the anti-CRC mechanisms of the CHs, which might refer to the regulation of apoptosis, transcription, and inflammation.

Project description:Chronic heart failure (CHF) is a major public health problem in huge population worldwide. The detailed understanding of CHF mechanism is still limited. Zheng (syndrome) is the criterion of diagnosis and therapeutic in Traditional Chinese Medicine (TCM). Syndrome prediction may be a better approach for understanding of CHF mechanism basis and its treatment. The authors studied disturbed metabolic biomarkers to construct a predicting mode to assess the diagnostic value of different syndrome of CHF and explore the Chinese herbal medicine (CHM) efficacy on CHF patients. A cohort of 110 patients from 11 independent centers was studied and all patients were divided into 3 groups according to TCM syndrome differentiation: group of Qi deficiency syndrome, group of Qi deficiency and Blood stasis syndrome, and group of Qi deficiency and Blood stasis and Water retention syndrome. Plasma metabolomic profiles were determined by UPLC-TOF/MS and analyzed by multivariate statistics. About 6 representative metabolites were highly possible to be associated with CHF, 4, 7, and 5 metabolites with Qi deficiency syndrome, Qi deficiency and Blood stasis syndrome, and Qi deficiency and Blood stasis and Water retention syndrome (VIP > 1, p < 0.05). The diagnostic model was further constructed based on the metabolites to diagnose other CHF patients with satisfying sensitivity and specificity (sensitivity and specificity are 97.1 and 80.6% for CHF group vs. NH group; 97.1 and 80.0% for QD group vs. NH group; 97.1 and 79.5% for QB group vs. NH group; 97.1 and 88.9% for QBW group vs. NH group), validating the robustness of plasma metabolic profiling to diagnostic strategy. By comparison of the metabolic profiles, 9 biomarkers, 2-arachidonoylglycerophosphocholine, LysoPE 16:0, PS 21:0, LysoPE 20:4, LysoPE 18:0, linoleic acid, LysoPE 18:2, 4-hydroxybenzenesulfonic acid, and LysoPE 22:6, may be especially for the effect of CHM granules. A predicting model was attempted to construct and predict patient based on the related symptoms of CHF and the potential biomarkers regulated by CHM were explored. This trial was registered with NCT01939236 (https://clinicaltrials.gov/).

Project description:Chinese medicine is a complex system guided by traditional Chinese medicine (TCM) theories, which has proven to be especially effective in treating chronic and complex diseases. However, the underlying modes of action (MOA) are not always systematically investigated. Herein, a systematic study was designed to elucidate the multi-compound, multi-target and multi-pathway MOA of a Chinese medicine ,QSYQ, on myocardial infarction. Male Sprague Dawley rat model of myocardial infarction were administered QSYQ intragastrically for 7 days while the control group was not treated. The differentially expressed genes (DEGs) were identified from myocardial infarction rat model treated with QSYQ, followed by constructing a cardiovascular disease (CVD)-related multilevel compound-target-pathway network connecting main compounds to those DEGs supported by literature evidences and the pathways that are functionally enriched. Three conditions were compared with three replicates each: (1) sham, i.e. without left anterior descending coronary artery (LAD) ligation; (2) model, with LAD ligation; (3) QSYQ, with LAD ligation and treated with QSYQ intragastrically for 7 days, the dosage was 105.6 mg/kg once a day. Rats were sacrificed after 7 days of i.g. administration under 10% chloral hydrate anesthesia (300mg/kg). Three tissue samples on the border between infarct and non-infarct area were dissected from left ventricles of each group. The tissue samples were stored at -80M-bM-^DM-^C refrigerator. Total RNA was extracted using TRIZol Reagent (Invitrogen) and purified using RNeasy Mini kit (QIAGEN), following manufacturersM-bM-^@M-^Y protocols. RNA quality was evaluated using an Agilent 2100 Bioanalyzer and electrophoresis in 2% (w/v) agarose gels. Only RNA with RNA integrity numbers (RINs) greater than 7.0 and 28SrRNA/18S rRNA ratio greater than 0.7 was used for microarray analyses. Whole genome microarray analysis was performed using Affymetrix rat Genome 230 2.0 chips.

Dataset Information

Modular Characteristics and Mechanism of Action of Herbs for Endometriosis Treatment in Chinese Medicine: A Data Mining and Network Pharmacology-Based Identification.

Publications

Modular Characteristics and Mechanism of Action of Herbs for Endometriosis Treatment in Chinese Medicine: A Data Mining and Network Pharmacology-Based Identification.

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