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The present study explored the biological connotation of traditional Chinese medicine(TCM) syndromes of rheumatoid arthritis(RA) from the "disease-syndrome-symptom" association network. RA patients with four TCM syndromes(dampness-heat obstruction, phlegm-stasis obstruction, Qi-blood deficiency, and liver and kidney deficiency), three for each type, were assigned as the RA TCM syndrome group, and three healthy volunteers as the normal control group. The differential gene sets of four syndromes were screened out through transcriptome expression profiling and bioinformatics mining. The relevant gene sets of syndrome-related clinical symptoms were collected from TCMIP v2.0(http://www.tcmip.cn/). The "disease-syndrome-symptom" association networks of four RA syndromes were established by using the intersection genes of syndrome-related differential genes and symptom-related genes, and the key network target genes of each syndrome were screened out and the corresponding biological functions were mined through topological feature calculation and enrichment analysis. The genes associated with clinical symptoms such as vasculitis, joint pain, and fever in the damp-heat obstruction syndrome ranked the top, and the key network target genes of this syndrome were most significantly enriched in the pathways related to material and energy metabolism and thermal reaction biological processes. The clinical symptom-related genes of the phlegm-stasis obstruction syndrome were most significantly enriched in the pathways related to "immunity-inflammation", nervous system regulation, and sensory response. The clinical symptoms such as hypoglycemia, hypotension, weight loss, palpitation, and arrhythmia in Qi-blood deficiency syndrome were predominant, and its key network target genes were most significantly enriched in the pathways related to the nervous system and "immunity-inflammation" response. The abnormal symptoms in the liver and kidney in the liver and kidney deficiency syndrome were commonly seen, and its key network target genes were most significantly enriched in the "immunity-inflammation" regulatory pathways, and liver and kidney development and metabolic response. In conclusion, the differences and connections of the biological basis between different TCM syndromes of RA are in line with the theoretical interpretation of TCM on the etiology and pathogenesis of RA. This study summarized the objective essence of syndromes to a certain extent from the "disease-syndrome-symptom" association network and is expected to provide a theoretical basis for the discovery of serum biomarkers of RA syndromes.
Subject(s)
Humans , Arthritis, Rheumatoid/genetics , Hot Temperature , Kidney , Medicine, Chinese Traditional , SyndromeABSTRACT
Traditional Chinese medicine(TCM) has unique advantages in the prevention and treatment of diseases owing to its holistic view and more than 2 000 years of experience in the clinical use of natural medicine. The "holistic" characteristic of TCM gives birth to a new generation of research paradigm featuring "network" and "system", which has been developing rapidly in the era of biomedical big data and artificial intelligence. Network pharmacology, a representative research field, provides new ideas and methods for the research of the interdiscipline of artificial intelligence and medicine, the analysis of massive biomedical data, and the transformation from data to knowledge. TCM plays an important role in proposing the core theory of "network target" and promoting the establishment and development of network pharmacology, and has taken the lead in formulating the first international standard of network pharmacology--Network Pharmacology Evaluation Method Guidance. In terms of theory, network target can systematically link drugs and diseases and quantitatively interpret the overall regulatory mechanism of drugs. In the aspect of method, network pharmacology is developing towards a research model that combines computational, experimental, and clinical approaches. This review introduces the resent important progress of TCM network pharmacology in predicting drug targets, understanding the biological basis of drugs and diseases, and searching for disease and syndrome biomarkers. Under the guidance of Network Pharmacology Evaluation Method Guidance, the development of network pharmacology is expected to become more and more standardized and healthy. Network target will help produce more high-quality research outcomes in TCM and effectively boost the modernization and internationalization of TCM.
Subject(s)
Artificial Intelligence , Drugs, Chinese Herbal/pharmacology , Medicine, Chinese Traditional , Network Pharmacology , Research DesignABSTRACT
Traditional Chinese medicine (TCM) is a precious treasure of the Chinese nation and has unique advantages in the prevention and treatment of diseases. The holistic view of TCM coincides with the new generation of medical research paradigm characterized by network and system. TCM gave birth to a new method featuring holistic and systematic "network target", a core theory and method of network pharmacology. TCM is also an important research object of network pharmacology. TCM network pharmacology, which aims to understand the network-based biological basis of complex diseases, TCM syndromes and herb treatments, plays a critical role in the origin and development process of network pharmacology. This review introduces new progresses of TCM network pharmacology in recent years, including predicting herb targets, understanding biological foundation of diseases and syndromes, network regulation mechanisms of herbal formulae, and identifying disease and syndrome biomarkers based on biological network. These studies show a trend of combining computational, experimental and clinical approaches, which is a promising direction of TCM network pharmacology research in the future. Considering that TCM network pharmacology is still a young research field, it is necessary to further standardize the research process and evaluation indicators to promote its healthy development.
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Objective: Integrating drug-likeness and network targets to preliminarily predict and explore the targets and pathways of Danggui Buxue Jiawei decoction(DBJD)in the prevention and treatment of diabetic retinopathy(DR). Methods: The chemical constituents of DBJD were identified by UPLC-Q-TOF/HRMS E analytical techniques. The related websites were used to esti mate the drug-likeness for all identified constituents. Then, for the selected drug-like constituents, targets-predicting was carried out on PharmMapper, and the targets for DR were searched by CTD, TTD and GeneCards. The component-target and disease-target net works were integrated to establish a large network, and core targets were searched on the basis of the DC, CC and BC values of the large network. Moreover, indirect targets were further searched on the basis of the core targets. Then, an all potential targets-related network was constructed and related key targets were searched by the constructed network. The key targets were verified by docking with the related components. Gene ontology(GO)biological analysis, Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analysis and Reactome pathway analysis were carried out on all potential targets. Eventually, a large Prescription-Medicinal material-Component-Direct target-Indirect target-Pathway integrated network was established for the DBJD studies. Results: A total of 55 chemical constituents were identified by UPLC-Q-TOF/HRMS E. Among them, 33 components were selected by the drug-likeness esti mation. The core targets consisted of 36 targets, and 20 indirect targets were obtained by relating with the core targets. By comparing de gree values, 6 key targets were established: AKT1, MAPK3, VEGFA, INS, MAPK1 and CASP3. In molecular docking tests, these key targets showed good binding activities with tanshinone, salvianolic acid B, ginsenoside Rg 1, notoginsenoside R 1, tanshinone Ⅱ A and other quality control components. Pathway analysis suggested that DBJD could likely interfere with the diabetic retinopathy by regulating oxidative stress, inflammatory factors and sugar metabolism. Conclusion: Accurate prediction of the action mechanism of complex Chinese medicinal ingredients based on the drug-likeness and network targets may be helpful to improve the blindness in relat ed research and accelerate the research process in modernization of traditional Chinese medicine. In this study, the molecular mecha nism of DBJD for the prevention and treatment of DR is preliminarily investigated and discussed, which could provide a valuable refer ence for future in-depth study.
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The herb-drug combination is becoming more and more common. The safety evaluation method is a complex evaluation system. This paper analyzed Pubmed database from 2008 to 2018, and summarized the characteristics of safety evaluation method, and the characteristics are listed as below: (1) Exposure safety issues in real world; (2) The combination use is complex and difficult to evaluate. There are the existing safety assessment methods including literature induction, prospective test, questionnaire survey, etc. Although safety evaluation has been carried out from different angles, there is still a lack of comprehensive and reasonable safety evaluation method. The team tried to combine clinical phenotype and mechanism characteristics to provide more reasonable methodological support for clinical safety evaluation.
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Recently, integrative pharmacology(IP) has become a pivotal paradigm for the modernization of traditional Chinese medicines(TCM) and combinatorial drugs discovery, which is an interdisciplinary science for establishing the in vitro and in vivo correlation between absorption, distribution, metabolism, and excretion/pharmacokinetic(ADME/PK) profiles of TCM and the molecular networks of disease by the integration of the knowledge of multi-disciplinary and multi-stages. In the present study, an internet-based Computation Platform for IP of TCM(TCM-IP, www.tcmip.cn) is established to promote the development of the emerging discipline. Among them, a big data of TCM is an important resource for TCM-IP including Chinese Medicine Formula Database, Chinese Medical Herbs Database, Chemical Database of Chinese Medicine, Target Database for Disease and Symptoms, et al. Meanwhile, some data mining and bioinformatics approaches are critical technology for TCM-IP including the identification of the TCM constituents, ADME prediction, target prediction for the TCM constituents, network construction and analysis, et al. Furthermore, network beautification and individuation design are employed to meet the consumer's requirement. We firmly believe that TCM-IP is a very useful tool for the identification of active constituents of TCM and their involving potential molecular mechanism for therapeutics, which would wildly applied in quality evaluation, clinical repositioning, scientific discovery based on original thinking, prescription compatibility and new drug of TCM, et al.
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Traditional Chinese Medicine (TCM), a crucial component of the current medical system, has been extensively used in clinical practice due to its valuable therapeutic efficacy, and its potentials as an important source of new pharmacophores. TCM is characterized by holistic theory, which emphasizes maintaining the balance of the patient's whole body using herbal formulae (fangji in Chinese) composed of mixtures of herbs with multiple bioactive ingredients. Because of the complex nature of these formulae, it is necessary to develop systematic methods to identify their bioactive ingredients and to clarify their mechanisms of action. With the rapid progress in bioinformatics, systems biology, and polypharmacology, "network pharmacology", which shifts the "one target, one drug" paradigm to the "network target, multi-component" strategy, has attracted the attention because it can not only reveal the underlying complex interactions between a herbal formula and cellular proteins but detect the influence of their interactions on the function and behavior of the system. Growing evidence shows that the network pharmacology strategy can be a powerful approach to modern research on TCM. The present paper focuses on the basis of network pharmacology and the recent progress in its methodology, illustrates its utility in screening bioactive ingredients and elucidating the mechanisms of action of TCM herbal formulae, analyzes its limitations and problems, and discusses its development direction and application prospects.
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Traditional Chinese medicine (TCM) holds a holistic theory, and specializes in balancing disordered human body using numerous natural products, particularly Chinese herbal formulae. TCM has certain treatment advantages for patients suffering from various complex diseases. However, due to the complex nature of TCM, it remains difficult to unveil such holistic medicine by the current reductionism research strategies, which treat both herbal ingredients and targets in isolation. Recently, an emerging network pharmacology approach has been introduced to tackle this bottleneck problem. A TCM-derived novel therapeutic concept, "network target", which is different from the Western medicine's "onetarget" concept, has been proposed from China. The network target strategy is able to illustrate the complex interactions among the biological systems, drugs, and complex diseases from a network perspective, and thus provides an innovative approach to access ancient remedies in a precision manner and at a systematic level, which also highlights TCM's potential in current medical systems.
Subject(s)
Humans , Herbal Medicine , Medicine, Chinese TraditionalABSTRACT
Traditional Chinese medicine(TCM),a comprehensive medicinal system,is characterized by holistic theory that emphasizes the regulation of the integrity of the human body and the interactions between human individuals and their environments. The diagnostic and therapeutic methods of TCM are based on the differentiation of syndrome(Zheng in Chinese)and the use of herbal formula(Fang-Ji in Chinese). There is an urgent need to develop scientific research methods in accordance with the above characteristics for TCM modernization. In the era of big data and with the rapid progress in systems biology,polypharmacology and bioinformatics,network pharmacology has emerged as a promising drug discovery approach that takes the same view as the theory of TCM. This methodology has explored correlations between drugs and complex diseases from the perspective of the holistic theory and has highlighted the paradigm shift from″one drug,one target″to″network target″. Thus,it is an original idea to combine network pharmacology with the modern research of TCM. This paper briefly analyzed and discussed the progress and major scientific challenges in network pharmacology applied to TCM diagnosis and treatment. To promote the development of TCM network pharmacology , several suggestions were also raised.