scholarly journals Integrating Data Mining, Network Pharmacology, and Molecular Docking Verification to Investigate the Molecular Mechanism of Traditional Chinese Medicine Prescriptions for Treating Male Infertility

2021 ◽  
Keyword(s):  
Data Mining ◽  
Molecular Docking ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Male Infertility ◽  
Molecular Mechanism ◽  
Network Pharmacology

Abstract The authors have requested that this preprint be withdrawn due to erroneous posting.

scholarly journals Integrating Data Mining, Network Pharmacology, and Molecular Docking Verification to Investigate the Molecular Mechanism of Traditional Chinese Medicine Prescriptions for Treating Male Infertility

2021 ◽  
Author(s):  
Xue Bai ◽  
Yibo Tang ◽  
Qiang Li ◽  
Guimin Liu ◽  
Dan Liu ◽  
...  
Keyword(s):  
Data Mining ◽  
Molecular Docking ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Male Infertility ◽  
Signaling Pathway ◽  
Molecular Mechanism ◽  
Oxidant Stress ◽  
Estrogen Signaling ◽  
Network Pharmacology

Abstract Background: Male infertility (MI) affects almost 5% adult men worldwide, and 75% of these cases are unexplained idiopathic. There are limitations in the current treatment due to the unclear mechanism of MI, which highlight the urgent need for a more effective strategy or drug. Traditional Chinese Medicine (TCM) prescriptions have been used to treat MI for thousands of years, but their molecular mechanism is not well defined. Methods: Aiming at revealing the molecular mechanism of TCM prescriptions on MI, a comprehensive strategy integrating data mining, network pharmacology, and molecular docking verification was performed. Firstly, we collected 289 TCM prescriptions for treating MI from National Institute of TCM Constitution and Preventive Medicine for 6 years. Then, Core Chinese Materia Medica (CCMM), the crucial combination of TCM prescriptions, was obtained by the TCM Inheritance Support System from China Academy of Chinese Medical Sciences. Next, the components and targets of CCMM in TCM prescriptions and MI-related targets were collected and analyzed through network pharmacology approach.Results: The results showed that the molecular mechanism of TCM prescriptions for treating MI are regulating hormone, inhibiting apoptosis, oxidant stress and inflammatory. Estrogen signaling pathway, PI3K-Akt signaling pathway, HIF-1 signaling pathway, and TNF signaling pathway are the most important signaling pathways. Molecular docking experiments were used to further validate network pharmacology results. Conclusions: This study not only discovers CCMM and the molecular mechanism of TCM prescriptions for treating MI, but may be helpful for the popularization and application of TCM treatment.

scholarly journals Study on the Mechanism of Baimai Ointment in the Treatment of Osteoarthritis Based on Network Pharmacology and Molecular Docking with Experimental Verification

2021 ◽  
Vol 12 ◽  
Author(s):  
Yingyin Zhu ◽  
Wanling Zhong ◽  
Jing Peng ◽  
Huichao Wu ◽  
Shouying Du
Keyword(s):  
Molecular Docking ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Signaling Pathway ◽  
Molecular Mechanism ◽  
Animal Experiments ◽  
Tibetan Medicine ◽  
Blue Staining ◽  
Network Pharmacology ◽  
Enzyme Linked Immunosorbent Assay

Purpose: The external preparation of the Tibetan medicine formula, Baimai ointment (BMO), has great therapeutic effects on osteoarthritis (OA). However, its molecular mechanism remains almost elusive. Here, a comprehensive strategy combining network pharmacology and molecular docking with pharmacological experiments was adopted to reveal the molecular mechanism of BMO against OA.Methods: The traditional Chinese medicine for systems pharmacology (TCMSP) database and analysis platform, traditional Chinese medicine integrated database (TCMID), GeneCards database, and DisGeNET database were used to screen the active components and targets of BMO in treating OA. A component–target (C-T) network was built with the help of Cytoscape, and the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment through STRING. Autodock Tools which was used to dock the key components and key target proteins was analyzed. Animal experiments were performed to verify the key targets of BMO. Hematoxylin–eosin and toluidine blue staining were used to observe the pathology of joints. Protein expression was determined using enzyme-linked immunosorbent assay.Results: Bioactive compounds and targets of BMO and OA were screened. The network analysis revealed that 17-β-estradiol, curcumin, licochalone A, quercetin, and glycyrrhizic acid were the candidate key components, and IL6, tumor necrosis factor (TNF), MAPK1, VEGFA, CXCL8, and IL1B were the candidate key targets in treating OA. The KEGG indicated that the TNF signaling pathway, NF-κB signaling pathway, and HIF-1 signaling pathway were the potential pathways. Molecular docking implied a strong combination between key components and key targets. The pathology and animal experiments showed BMO had great effects on OA via regulating IL6, TNF, MAPK1, VEGFA, CXCL8, and IL1B targets. These findings were consistent with the results obtained from the network pharmacology approach.Conclusion: This study preliminarily illustrated the candidate key components, key targets, and potential pathways of BMO against OA. It also provided a promising method to study the Tibetan medicine formula or external preparations.

scholarly journals A network pharmacology-based investigation on the bioactive ingredients and molecular mechanisms of Gelsemium elegans Benth against colorectal cancer

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Wancai Que ◽  
Maohua Chen ◽  
Ling Yang ◽  
Bingqing Zhang ◽  
Zhichang Zhao ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Molecular Dynamics ◽  
Molecular Docking ◽  
Molecular Dynamics Simulation ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Molecular Mechanism ◽  
Enrichment Analysis ◽  
Dynamics Simulation ◽  
Network Pharmacology

Abstract Background Colorectal cancer (CRC) remains one of the leading causes of cancer-related death worldwide. Gelsemium elegans Benth (GEB) is a traditional Chinese medicine commonly used for treatment for gastrointestinal cancer, including CRC. However, the underlying active ingredients and mechanism remain unknown. This study aims to explore the active components and the functional mechanisms of GEB in treating CRC by network pharmacology-based approaches. Methods Candidate compounds of GEB were collected from the Traditional Chinese Medicine@Taiwan, Traditional Chinese Medicines Integrated Database, Bioinformatics Analysis Tool for Molecular mechanism of Traditional Chinese Medicine, and published literature. Potentially active targets of compounds in GEB were retrieved from SwissTargetPrediction databases. Keywords “colorectal cancer”, “rectal cancer” and “colon cancer” were used as keywords to search for related targets of CRC from the GeneCards database, then the overlapped targets of compounds and CRC were further intersected with CRC related genes from the TCGA database. The Cytoscape was applied to construct a graph of visualized compound-target and pathway networks. Protein-protein interaction networks were constructed by using STRING database. The DAVID tool was applied to carry out Gene Ontology and Kyoto Encyclopedia of Genes and Genome pathway enrichment analysis of final targets. Molecular docking was employed to validate the interaction between compounds and targets. AutoDockTools was used to construct docking grid box for each target. Docking and molecular dynamics simulation were performed by Autodock Vina and Gromacs software, respectively. Results Fifty-three bioactive compounds were successfully identified, corresponding to 136 targets that were screened out for the treatment of CRC. Functional enrichment analysis suggested that GEB exerted its pharmacological effects against CRC via modulating multiple pathways, such as pathways in cancer, cell cycle, and colorectal cancer. Molecular docking analysis showed that the representative compounds had good affinity with the key targets. Molecular dynamics simulation indicated that the best hit molecules formed a stable protein-ligand complex. Conclusion This network pharmacology study revealed the multiple ingredients, targets, and pathways synergistically involved in the anti-CRC effect of GEB, which will enhance our understanding of the potential molecular mechanism of GEB in treatment for CRC and lay a foundation for further experimental research.

scholarly journals The Analysis of The Application and Mechanism of Traditional Chinese Medicine in Osteoarthritis Based on Data Mining and Network Pharmacology

2020 ◽  
Author(s):  
Jie YANG ◽  
Dijin JIAO ◽  
Guoguang Zhang ◽  
Juntong LIU ◽  
Chao QU ◽  
...  
Keyword(s):  
Data Mining ◽  
Molecular Docking ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Cell Metabolism ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
String Database ◽  
The Core ◽  
Drug Molecules

Abstract Background: Using Data Mining to retrieve the core drug of osteoarthritis in clinic, predicting the drug molecular action target through the Network Pharmacology, combining with the related targets of osteoarthritis to identify the key nodes of the interaction, exploring the pharmacological mechanism of Traditional Chinese Medicine against osteoarthritis and other possible mechanisms of actions. Methods: Pubmed, CNKI, VIP, CBM and WanFang Database was used to retrieve the commonly used therapeutic formulations for osteoarthritis patients in clinical, and screen out the core drugs through the Ancient and Modern Medical Case Cloud Platform and software Gephi, filtered out the core drug molecules and targets combined with TCMSP database and the targets of osteoarthritis in Genecard, OMIM database, impoting those datas into R project and Cytoscape to construct the intersection model of Drug molecule-osteoarthritis, carrying out PPI network and GO and KEGG enrichment analysis with String database. Vina molecular docking was implemented to draw molecular docking diagram, and the results were analyzed after comprehensive analysis. Results: The core drug pairs were identified as "Eucommiae Cortex - Achyranthis Bidentatae Radix" through correlation analysis, complex network analysis basing on the coefficient. "Eucommiae Cortex - Achyranthis Bidentatae Radix" can intervene cell behaviors through multiple pathways and regulate cell metabolism, cytokine synthesis, oxidative , cellular immunity as a consequence of topology analysis in String Database. Conclusions: "Eucommia bark - achyranthes" drug molecules can be combined with the target to produce hydrogen bond, hydrophobic function and Pi-Pi directly or indirectly affecting the corresponding targets, to participate in the regulation of osteogenesis and osteoclast proliferation, protect the extracellular matrix, inhibition of cell apoptosis and anti-inflammatory for resistance to osteoarthritis, also, providing the basis for interpretation of its action mechanism.

scholarly journals Data Mining, Network Pharmacology, and Molecular Docking Explore the Effects of Core Traditional Chinese Medicine Prescriptions in Patients with Rectal Cancer and Qi and Blood Deficiency Syndrome

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Shiyu Ma ◽  
Lin Zheng ◽  
Lan Zheng ◽  
Xiaolan Bian
Keyword(s):  
Data Mining ◽  
Rectal Cancer ◽  
Molecular Docking ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Deficiency Syndrome ◽  
Network Pharmacology ◽  
Hub Genes ◽  
The Core ◽  
High Degree

Background. “Zheng” (syndrome) is the basic unit and the basis of traditional Chinese medicine (TCM) treatment. In clinical practice, we have been able to improve the survival time and quality of life for patients with rectal cancer through the treatment of “FuZhengXiaoJi” (strengthening the Qi and reducing accumulation). Purpose. In this study, we elucidated the core prescriptions for patients with rectal cancer and Qi and blood deficiency syndrome, and we explored the potential mechanisms of the prescriptions using an integrated strategy that coupled data mining with network pharmacology. Methods. A Bron–Kerbosch (BK) algorithm was applied to find the core prescriptions. The active ingredients, targets, activated signaling pathways, and biological functions of core prescriptions were analyzed using network pharmacology and directly associated proteins were docked using molecular docking technology to elucidate the multicomponent, multitarget, and inter-related components associated with TCM systematically. Results. Data mining identified 3 core prescriptions, and most of the herbs consisted of “FuZhengXiaoJi” Fang. Network pharmacology identified 15 high-degree active ingredients among the 3 core prescriptions and 16 high-degree hub genes linked with both rectal cancer and the 3 core prescriptions. Additional Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses of these 16 targets showed that the most significant pathways were MAPK, interleukin-17, tumor necrosis factor (TNF), and vascular endothelial growth factor (VEGF) pathways. From the 16 genes, TGFB1, IL1B, IL10, IL6, PTGS2, and PPARG closely interacted with the tumor microenvironment, and PPARG, MYC, and ERBB2 were closely linked to survival. In molecular docking, quercetin, kaempferol, and lauric acid showed good binding energy to each target. Conclusion. Data mining, network pharmacology, and molecular docking may help identify core prescriptions, high-degree ingredients, and high-degree hub genes to apply to diseases and treatments. Furthermore, these studies may help discover hub genes that affect the tumor microenvironment and survival. The combination of these tools may help elucidate the relationship between herbs acting on “Zheng” (syndrome) and diseases, thus expanding the understanding of TCM mechanisms.

scholarly journals Tianma Formula Alleviates Dementia via ACER2-Mediated Sphingolipid Signaling Pathway Involving Aβ

2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Haochang Lin ◽  
Sha Wu ◽  
Zhiying Weng ◽  
Hongyan Wang ◽  
Rui Shi ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Signaling Pathway ◽  
Molecular Mechanism ◽  
Sphingolipid Metabolism ◽  
Network Pharmacology ◽  
Rna Seq ◽  
C Elegans ◽  
Metabolism Pathway

Objective. To reveal the molecular mechanism of the antagonistic effect of traditional Chinese medicine Tianma formula (TF) on dementia including vascular dementia (VaD) and Alzheimer’s disease (AD) and to provide a scientific basis for the study of traditional Chinese medicine for prevention and treatment of dementia. Method. The TF was derived from the concerted application of traditional Chinese medicine. We detected the pharmacological effect of TF in VaD rats. The molecular mechanism of TF was examined by APP/PS1 mice in vivo, Caenorhabditis elegans (C. elegans) in vitro, ELISA, pathological assay via HE staining, and transcriptome. Based on RNA-seq analysis in VaD rats, the differentially expressed genes (DEGs) were identified and then verified by quantitative PCR (qPCR) and ELISA. The molecular mechanisms of TF on dementia were further confirmed by network pharmacology and molecular docking finally. Results. The Morris water maze showed that TF could improve the cognitive memory function of the VaD rats. The ELISA and histological analysis suggested that TF could protect the hippocampus via reducing tau and IL-6 levels and increasing SYN expression. Meanwhile, it could protect the neurological function by alleviating Aβ deposition in APP/PS1 mice and C. elegans. In the RNA-seq analysis, 3 sphingolipid metabolism pathway-related genes, ADORA3, FCER1G, and ACER2, and another 5 nerve-related genes in 45 key DEGs were identified, so it indicated that the protection mechanism of TF was mainly associated with the sphingolipid metabolism pathway. In the qPCR assay, compared with the model group, the mRNA expressions of the 8 genes mentioned above were upregulated, and these results were consistent with RNA-seq. The protein and mRNA levels of ACER2 were also upregulated. Also, the results of network pharmacology analysis and molecular docking were consistent with those of RNA-seq analysis. Conclusion. TF alleviates dementia by reducing Aβ deposition via the ACER2-mediated sphingolipid signaling pathway.

scholarly journals Study on Medication Rules of Traditional Chinese Medicine against Antineoplastic Drug-Induced Cardiotoxicity Based on Network Pharmacology and Data Mining

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Wenchao Dan ◽  
Jinlei Liu ◽  
Xinyuan Guo ◽  
Boran Zhang ◽  
Yi Qu ◽  
...  
Keyword(s):  
Data Mining ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Target Prediction ◽  
Antineoplastic Drug ◽  
Matrix Metalloproteinase 2 ◽  
Network Pharmacology ◽  
China National Knowledge Infrastructure ◽  
Drug Induced ◽  
Mitogen Activated Protein

Background and Aim. Antineoplastic drug-induced cardiotoxicity (ADIC) becomes the second leading cause of death for tumor survivors after tumor recurrence and metastasis, and there may be great room for development in the future of traditional Chinese medicine (TCM). However, the theory of anticardiotoxicity of TCM has not yet formed a system. This study aimed to explore the material basis and the rule of TCM against ADIC based on network pharmacology and data mining. Methods. The targets of antineoplastic drugs with cardiotoxicity were obtained from the National Center for Biotechnology Information (NCBI) database, China national knowledge infrastructure (CNKI) database, and Swiss Target Prediction platform. Then, the cardiotoxicity-related targets were derived from the Gene Cards, Disgenet, OMIM, and DrugBank databases, as well as the drug of current clinical guidelines. The targets both in these two sets were regarded as potential targets to alleviate ADIC. Then, candidate compounds and herbs were matched via Traditional Chinese Medicine Systems Pharmacology (TCMSP) platform. Cytoscape3.7.1 was used to set up the target-compound-herb network. Molecular docking between core targets and compounds was performed with AutodockVina1.1.2. The rules of herbs were summarized by analyzing their property, flavor, and channel tropism. Results. Twenty-one potential targets, 332 candidate compounds, and 400 kinds of herbs were obtained. Five core targets including potassium voltage-gated channel subfamily H member 2 (KCNH2), cyclin-dependent kinase 1 (CDK1), matrix metalloproteinase 2 (MMP2), mitogen-activated protein kinase1 (MAPK1), and tumor protein p53 (TP53) and 29 core compounds (beta-sitosterol, quercetin, kaempferol, etc.) were collected. Five core herbs (Yanhusuo, Gouteng, Huangbai, Lianqiao, and Gancao) were identified. Also, the TCM against ADIC were mainly bitter and acrid in taste, warm in property, and distributed to the liver and lung meridians. Conclusion. TCM against ADIC has great potential. Our study provides a new method and ideas for clinical applications of integrated Chinese and western medicine in treating ADIC.

Exploring the mechanisms of Drynariae Rhizoma on treating memory impairment through network pharmacology

2021 ◽  
Author(s):  
Wangmi Liu ◽  
Jiayan Wu
Keyword(s):  
Molecular Docking ◽  
Nerve Growth Factor ◽  
Chinese Medicine ◽  
Growth Factor ◽  
Traditional Chinese Medicine ◽  
Memory Impairment ◽  
Network Pharmacology ◽  
Active Compounds ◽  
Major Health Problem ◽  
Nerve Growth

Abstract Background Memory impairment continues to be a major health problem and increases with age, especially in the elderly population worldwide. However, a causal mechanism has not been clearly identified. Currently, an interaction between bone and brain, the so-called “bone-brain crosstalk,” has emerged. We used a network pharmacology approach to explore the potential mechanisms of Drynariae Rhizoma (DR), a traditional Chinese medicine for fracture treatment, for therapeutic intervention of human conditions associated with memory impairment. Methods The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform was used to screen out the active compounds of DR, and the targets of the active compounds were predicted using PharmMapper. Targets related to memory impairment were downloaded from the DisGeNET database. The compound-target network and protein-protein interaction network were built by NetworkAnalyst and Cytoscape software. Gene ontology analysis and Reactome pathway enrichment analysis were performed using NetworkAnalyst. SYBYL-X software was used to perform molecular docking simulation. Results Our study demonstrated that DR had 7 active compounds. There were 60 target genes related to these active compounds as well as to memory impairment. Signalling by nerve growth factor was among the top 3 enriched Reactome terms. Akt1 was an important signalling hub gene belonging to signalling by nerve growth factor pathway. Molecular docking results showed that the one of the active compounds, xanthogalenol, exhibited acceptable affinities to Akt1. Conclusion This study demonstrated the molecular mechanism that DR may alleviate memory impairment via regulation of Akt1 and signalling by nerve growth factor pathway. These results offer new ideas in searching for novel strategies for the treatment of memory impairment.

scholarly journals A Network Pharmacology Study on the Active Ingredients and Potential Targets ofTripterygium wilfordiiHook for Treatment of Rheumatoid Arthritis

2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Wei Hu ◽  
Wanjin Fu ◽  
Xin Wei ◽  
Yang Yang ◽  
Chao Lu ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Molecular Mechanism ◽  
Rheumatic Diseases ◽  
Chinese Herbs ◽  
Network Pharmacology ◽  
Disease Network ◽  
Rheumatoid Arthritis Disease ◽  
Compound Target

Traditional Chinese medicine has specific effect on some chronic diseases in clinic, especially in rheumatic diseases.Tripterygium wilfordiiHook (TWH) is a traditional Chinese medicine commonly used in the treatment of rheumatoid arthritis (RA); the unique therapeutic effect has been confirmed by a large number of research papers. TWH has many compounds that lead to its active compounds. However, the potential targets and pharmacological and molecular mechanism of its action treatment of rheumatic diseases are not entirely clear. Therefore, the network pharmacology approach is needed to further study and explore its treatment mechanism. We have successfully set up 10 networks, including four major networks and other networks. Four major networks include rheumatoid arthritis disease network, compound-compound target network of TWH, TWH compound target-rheumatoid arthritis disease network, and TWH-rheumatoid arthritis disease-mechanism network. Other networks consist of RA disease and TWH related targets clusters, biological processes, and pathways network. Our study successfully predicted, explained, and confirmed the TWH of RA disease molecular synergy and found the potential of RA related targets, cluster, biological process, and pathways. This study not only provides prompts to the researcher who explores pharmacological and biological molecular mechanism of TWH applying to RA disease, but also proves a feasible method for discovering potential activated compounds from Chinese herbs.

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