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      Discovering Traditional Chinese Medicine (TCM) Formulas for Complex Diseases Based on a Combination of Reverse Systematic Pharmacology and TCM Meridian Tropism Theory: Taking COVID-19 as an Example

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          Abstract

          Objective: Infections and death have been a part of our daily lives since the COVID-2019 pandemic outbreak in 2019, and the societal and economic consequences have lingered for an unanticipated duration. Novel and effective treatments are still desperately needed around the world to combat the infection. Here, we discovered a novel traditional Chinese medicine formula (TCMF) to potentially combat COVID-19 through reverse systematic pharmacology (disease → targets → TCMF → disease). Methods: Combining Integrative network pharmacology and the traditional Chinese medicine (TCM) theory, a TCMF for COVID-19 was identified. In silico physiological interactions between herbs and disease hub targets were validated by molecular docking and dynamics simulation. Results: Based on disease-related gene/pathway targets and a combination of reverse pharmacology and TCM meridian tropism theory, a COVID-19-associated herb database was constructed. A new TCMF, including Gancao, Baitouweng, Congbai, and Diyu (GBCD), was discovered for anti-COVID-19 therapy. The KEGG and GO analyses of 49 intersecting genes suggested that GBCD could combat COVID-19 through antiviral, antiinflammation, immunoregulation, and cytoprotection activities. Moreover, these possible effects were validated through docking and MD simulation. Conclusions: To the best of our knowledge, this study is the first to combine reverse pharmacology and meridian tropism theories for TCMF development, and a novel herbal combination, GBCD, was discovered for anti-COVID-19 therapy.

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          Most cited references61

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          Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China

          Summary Background A recent cluster of pneumonia cases in Wuhan, China, was caused by a novel betacoronavirus, the 2019 novel coronavirus (2019-nCoV). We report the epidemiological, clinical, laboratory, and radiological characteristics and treatment and clinical outcomes of these patients. Methods All patients with suspected 2019-nCoV were admitted to a designated hospital in Wuhan. We prospectively collected and analysed data on patients with laboratory-confirmed 2019-nCoV infection by real-time RT-PCR and next-generation sequencing. Data were obtained with standardised data collection forms shared by WHO and the International Severe Acute Respiratory and Emerging Infection Consortium from electronic medical records. Researchers also directly communicated with patients or their families to ascertain epidemiological and symptom data. Outcomes were also compared between patients who had been admitted to the intensive care unit (ICU) and those who had not. Findings By Jan 2, 2020, 41 admitted hospital patients had been identified as having laboratory-confirmed 2019-nCoV infection. Most of the infected patients were men (30 [73%] of 41); less than half had underlying diseases (13 [32%]), including diabetes (eight [20%]), hypertension (six [15%]), and cardiovascular disease (six [15%]). Median age was 49·0 years (IQR 41·0–58·0). 27 (66%) of 41 patients had been exposed to Huanan seafood market. One family cluster was found. Common symptoms at onset of illness were fever (40 [98%] of 41 patients), cough (31 [76%]), and myalgia or fatigue (18 [44%]); less common symptoms were sputum production (11 [28%] of 39), headache (three [8%] of 38), haemoptysis (two [5%] of 39), and diarrhoea (one [3%] of 38). Dyspnoea developed in 22 (55%) of 40 patients (median time from illness onset to dyspnoea 8·0 days [IQR 5·0–13·0]). 26 (63%) of 41 patients had lymphopenia. All 41 patients had pneumonia with abnormal findings on chest CT. Complications included acute respiratory distress syndrome (12 [29%]), RNAaemia (six [15%]), acute cardiac injury (five [12%]) and secondary infection (four [10%]). 13 (32%) patients were admitted to an ICU and six (15%) died. Compared with non-ICU patients, ICU patients had higher plasma levels of IL2, IL7, IL10, GSCF, IP10, MCP1, MIP1A, and TNFα. Interpretation The 2019-nCoV infection caused clusters of severe respiratory illness similar to severe acute respiratory syndrome coronavirus and was associated with ICU admission and high mortality. Major gaps in our knowledge of the origin, epidemiology, duration of human transmission, and clinical spectrum of disease need fulfilment by future studies. Funding Ministry of Science and Technology, Chinese Academy of Medical Sciences, National Natural Science Foundation of China, and Beijing Municipal Science and Technology Commission.
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            Cytoscape: a software environment for integrated models of biomolecular interaction networks.

            Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
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              AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading.

              AutoDock Vina, a new program for molecular docking and virtual screening, is presented. AutoDock Vina achieves an approximately two orders of magnitude speed-up compared with the molecular docking software previously developed in our lab (AutoDock 4), while also significantly improving the accuracy of the binding mode predictions, judging by our tests on the training set used in AutoDock 4 development. Further speed-up is achieved from parallelism, by using multithreading on multicore machines. AutoDock Vina automatically calculates the grid maps and clusters the results in a way transparent to the user. Copyright 2009 Wiley Periodicals, Inc.
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                Author and article information

                Journal
                ACS Omega
                ACS Omega
                ao
                acsodf
                ACS Omega
                American Chemical Society
                2470-1343
                24 July 2023
                01 August 2023
                : 8
                : 30
                : 26871-26881
                Affiliations
                []School of Nursing, Tianjin University of Traditional Chinese Medicine , 10 Poyanghu Road, West Area, Tuanbo New Town, Jinghai District, Tianjin 301617, P. R. China
                []School of Integrative Medicine, Tianjin University of Traditional Chinese Medicine , 10 Poyanghu Road, West Area, Tuanbo New Town, Jinghai District, Tianjin 301617, P. R. China
                Author notes
                [* ]Email: bianyuhong_2012@ 123456163.com . Tel: +86-022-59596539.
                [* ]Email: yh_liu888@ 123456163.com . Tel: +86-15522507906.
                Author information
                https://orcid.org/0000-0003-1764-4462
                Article
                10.1021/acsomega.3c01489
                10398703
                a6e07da6-c1a9-4736-9fb4-adff8e84d61e
                © 2023 The Authors. Published by American Chemical Society

                Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works ( https://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 07 March 2023
                : 06 July 2023
                Funding
                Funded by: National Natural Science Foundation of China, doi 10.13039/501100001809;
                Award ID: 71974143
                Funded by: Ministry of Science and Technology of the People''s Republic of China, doi 10.13039/501100002855;
                Award ID: 2018YFC1706500
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                ao3c01489

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