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 Research on Active Compounds of Huanglian Jiedu Decoction for the Treatment of Corona Virus Disease 2019 Based on Network Pharmacology and Molecular Docking

2020 ◽  
Author(s):  
Leping Liu ◽  
Xinyi Xu ◽  
Xueshuai Cao ◽  
Xi Long ◽  
Yanwei Luo ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Signaling Pathways ◽  
Target Genes ◽  
Virus Disease ◽  
Network Pharmacology ◽  
Signal Pathways ◽  
Active Compounds ◽  
Corona Virus

Abstract Background Huanglian Jiedu Decoction (HLJDD) is a traditional Chinese prescription for the treatment of influenza, inflammation and other ailments related to heat-syndrome, a typical pathological symptom in Traditional Chinese Medicine. It was recommended as one of the basic prescriptions among the Proposed Diagnoses and Treatment issued by China’s National Health Commission. In this work we investigated the molecular mechanism of action of Huanglian Jiedu Decoction in the treatment of Corona Virus Disease 2019 (COVID-19) through network pharmacology and molecular docking approaches. Methods The chemical constituents and action targets of Coptis chinensis, Scutellaria baicalensis, Phellodendron amurense, Gardenia jasminoides in HLJDD were retrieved on Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). The database of UniProt and GeneCards were used to query the target genes that corresponding to the active compounds, and then a compound-target network was constructed using Cytoscape 3.7.2. GO database was used to annotate GO functions. Reactome was used to analyze KEGG enrichment pathway, predicting the possible mechanisms of active compounds. DAVID database was used to analysis the tissue enrichment. The main active ingredient is molecularly docked with the SARS-CoV-2, ACE2 and TMPRSS2. Results We screened 84 compounds and obtained 341 corresponding target genes in the network. Gene annotation showed that the targets were involved mainly in 457 biological functions. 306 signaling pathways was enriched, involving chemokine and cytokine signaling pathways that mediate inflammation, interferon-γ signaling pathway, p53 pathway. And the targets mainly distributed in the lung liver and placenta, involving a variety of immune cells, such as T cells, B cells. The molecular docking results showed that core compounds such as beta-sitosterol, stigmasterol and quercetin had high affinity with SARS-CoV-2, ACE2 and TMPRSS2, which was comparable with drugs like abidol used to COVID-19 treatment by. Conclusions The active compounds in HLJDD may have a therapeutic effect on COVID-19 through regulating multiple signal pathways by targeting genes such as VEGF, NOS2, IL6, MMP9, IL10, and TGFB1.

scholarly journals Study on the Potential Mechanism of Fructus Tribuli in the Treatment of Hypertensive Vascular Remodeling Based on Network Pharmacology and Molecular Docking

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Shuyue Wang ◽  
Fei Guo ◽  
Xiaochen Sun ◽  
Xiao Song ◽  
Yaohui Yuan ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Signaling Pathway ◽  
Vascular Remodeling ◽  
Network Pharmacology ◽  
Research Approach ◽  
Active Components ◽  
Active Compounds ◽  
Ppi Networks

Background. Hypertensive vascular remodeling (HVR) is the pathophysiological basis of hypertension, which is also an important cause of vascular disease and target organ damage. Treatment with Fructus Tribuli (FT), a traditional Chinese medicine, has a positive effect on HVR. However, the pharmacological mechanisms of FT are still unclear. Therefore, this study aimed to reveal the potential mechanisms involved in the effects of FT on HVR based on network pharmacology and molecular docking. Materials and Methods. We selected the active compounds and targets of FT according to the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and the Swiss Target Prediction database, and the targets of HVR were collected from the Online Mendelian Inheritance in Man (OMIM), GeneCards, and DrugBank databases. The protein-protein interaction network (PPI) was established using the STRING database. Moreover, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses and network analysis were performed to further explore the potential mechanisms. Finally, molecular docking methods were used to evaluate the affinity between the active compounds and the main target. Results. Seventeen active compounds of FT  and 164 potential targets for the treatment of HVR were identified. Component-target and PPI networks were constructed, and 12 main active components and 33 main targets were identified by analyzing the topological parameters. Additionally, GO analysis indicated that the potential targets were enriched in 483 biological processes, 52 cellular components, and 110 molecular functions. KEGG analysis revealed that the potential targets were correlated with 122 pathways, such as the HIF-1 signaling pathway, ErbB signaling pathway, and VEGF signaling pathway. Finally, molecular docking showed that the 12 main active components had a good affinity for the top five main targets. Conclusion. This study demonstrated the multiple compounds, targets, and pathway characteristics of FT in the treatment of HVR. The network pharmacology method provided a novel research approach to analyze potential mechanisms.

scholarly journals A Network Pharmacology-Based Study on the Anti-Lung Cancer Effect of Dipsaci Radix

2020 ◽  
Vol 2020 ◽  
pp. 1-9 ◽  
Author(s):  
Jiayan Wu ◽  
Shengkun Hong ◽  
Xiankuan Xie ◽  
Wangmi Liu
Keyword(s):  
Lung Cancer ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
Interaction Network ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Hub Genes ◽  
Active Compounds

Objective. Dipsaci Radix (DR) has been used to treat fracture and osteoporosis. Recent reports have shown that myeloid cells from bone marrow can promote the proliferation of lung cancer. However, the action and mechanism of DR has not been well defined in lung cancer. The aim of the present study was to define molecular mechanisms of DR as a potential therapeutic approach to treat lung cancer. Methods. Active compounds of DR with oral bioavailability ≥30% and drug-likeness index ≥0.18 were obtained from the traditional Chinese medicine systems pharmacology database and analysis platform. The potential target genes of the active compounds and bone were identified by PharmMapper and GeneCards, respectively. The compound-target network and protein-protein interaction network were built by Cytoscape software and Search Tool for the Retrieval of Interacting Genes webserver, respectively. GO analysis and pathway enrichment analysis were performed using R software. Results. Our study demonstrated that DR had 6 active compounds, including gentisin, sitosterol, Sylvestroside III, 3,5-Di-O-caffeoylquinic acid, cauloside A, and japonine. There were 254 target genes related to these active compounds as well as to bone. SRC, AKT1, and GRB2 were the top 3 hub genes. Metabolisms and signaling pathways associated with these hub genes were significantly enriched. Conclusions. This study indicated that DR could exhibit the anti-lung cancer effect by affecting multiple targets and multiple pathways. It reflects the traditional Chinese medicine characterized by multicomponents and multitargets. DR could be considered as a candidate for clinical anticancer therapy by regulating bone physiological functions.

Memory impairment and neural dysfunction after continuous infusion of anti-nerve growth factor antibody into the septum in adult rats

Neuroscience ◽  
1993 ◽  
Vol 57 (3) ◽  
pp. 495-499 ◽  
Author(s):  
A. Nitta ◽  
K. Murase ◽  
Y. Furukawa ◽  
K. Hayashi ◽  
T. Hasegawa ◽  
...  
Keyword(s):  
Nerve Growth Factor ◽  
Growth Factor ◽  
Continuous Infusion ◽  
Memory Impairment ◽  
Adult Rats ◽  
Nerve Growth ◽  
Neural Dysfunction

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 A network pharmacology-based approach to explore the active ingredients and molecular mechanism of Lei-gong-gen formula granule on a spontaneously hypertensive rat model

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Qiaofeng Li ◽  
Taijin Lan ◽  
Songhua He ◽  
Weiwei Chen ◽  
Xiaolan Li ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Nicotinic Acid ◽  
Signaling Pathway ◽  
Antihypertensive Effect ◽  
Spontaneously Hypertensive Rat ◽  
Shikimic Acid ◽  
Network Pharmacology ◽  
Active Compounds

Abstract Background Lei-gong-gen formula granule (LFG) is a folk prescription derived from Zhuang nationality, the largest ethnic minority among 56 nationalities in China. It consists of three herbs, namely Eclipta prostrata (L.) L., Smilax glabra Roxb, and Centella asiatica (L.) Urb. It has been widely used as health protection tea for hundreds of years to prevent hypertension in Guangxi Zhuang Autonomous Region. The purpose of this study is to validate the antihypertensive effect of LFG on the spontaneously hypertensive rat (SHR) model, and to further identify the effective components and anti-hypertension mechanism of LFG. Methods The effects of LFG on blood pressure, body weight, and heart rate were investigated in vivo using the SHR model. The levels of NO, ANG II, and ET-1 in the serum were measured, and pathological changes in the heart were examined by H&E staining. The main active components of LFG, their corresponding targets, and hypertension associated pathways were discerned through network pharmacology analysis based on the Traditional Chinese Medicine Systems Pharmacology (TCMSP), Traditional Chinese Medicine Integrated Database (TCMID), and the Bioinformatics Analysis Tool for Molecular Mechanism of Traditional Chinese Medicine (BATMAN-TCM). Then the predicted results were further verified by molecular biology experiments such as RT-qPCR and western blot. Additionally, the potential active compounds were predicted by molecular docking technology, and the chemical constituents of LFG were analyzed and identified by UPLC-QTOF/MS technology. Finally, an in vitro assay was performed to investigate the protective effects of potential active compounds against hydrogen peroxide (H2O2) induced oxidative damage in human umbilical vein endothelial cells (HUVEC). Results LFG could effectively reduce blood pressure and increase serum NO content in SHR model. Histological results showed that LFG could ameliorate pathological changes such as cardiac hypertrophy and interstitial inflammation. From network pharmacology analysis, 53 candidate active compounds of LFG were collected, which linked to 765 potential targets, and 828 hypertension associated targets were retrieved, from which 12 overlapped targets both related to candidate active compounds from LFG and hypertension were screened and used as the potential targets of LFG on antihypertensive effect. The molecular biology experiments of the 12 overlapped targets showed that LFG could upregulate the mRNA and protein expressions of NOS3 and proto-oncogene tyrosine-protein kinase SRC (SRC) in the thoracic aorta. Pathway enrichment analysis showed that the PI3K-AKT signaling pathway was closely related to the expression of NOS3 and SRC. Moreover, western blot results showed that LFG significantly increased the protein expression levels of PI3K and phosphorylated AKT in SHR model, suggesting that LFG may active the PI3K-AKT signaling pathway to decrease hypertension. Molecular docking study further supported that p-hydroxybenzoic acid, cedar acid, shikimic acid, salicylic acid, nicotinic acid, linalool, and histidine can be well binding with NOS3, SRC, PI3K, and AKT. UPLC-QTOF/MS analysis confirmed that p-hydroxybenzoic acid, shikimic acid, salicylic acid, and nicotinic acid existed in LFG. Pre-treatment of HUVEC with nicotinic acid could alleviate the effect on cell viability induced by H2O2 and increase the NO level in cell supernatants. Conclusions LFG can reduce the blood pressure in SHR model, which might be attributed to increasing the NO level in serum for promoting vasodilation via upregulating SRC expression level and activating the PI3K-AKT-NOS3 signaling pathway. Nicotinic acid might be the potential compound for LFG antihypertensive effect.

scholarly journals Exploring the Mechanisms of Lian Hua Qing Wen Capsule against COVID-19 by Network Pharmacology and Molecular Docking Approach

2020 ◽  
Author(s):  
Li Chen ◽  
Hua Qu ◽  
Yu Tan ◽  
Tao Han Wu ◽  
Zhuo Da Shi
Keyword(s):  
Molecular Docking ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Signaling Pathway ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Active Compounds ◽  
Related Target ◽  
Docking Approach ◽  
Omim Database

Abstract Background The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 or COVID-19) disease has led to a wide-spread global pandemic. There is no specific antiviral drug proven effective for the treatment of patients with COVID-19 at present. Combination of western and traditional Chinese medicine (TCM) is recommended, and Lian Hua Qing Wen (LHQW) capsule is a basic prescription and widely used to treat COVID-19 in China. However, the mechanisms of LHQW capsule treating COVID-19 are not clear. The aim of the study is to explore the mechanisms of LHQW capsule treating COVID-19 based on network pharmacy and molecular docking approach. Methods The active compounds and targets of LHQW capsule were obtained from traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP). COVID-19 related target genes were obtained from GeneCards database and OMIM database. Protein–protein interaction (PPI) networks of LHQW capsule targets and COVID-19-related genes were visualized and merged to identify the candidate targets for LHQW capsule treating COVID-19. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were also performed. The hub genes involved in the gene-related pathways were screened and their corresponding compounds were used for in vitro validation of molecular docking predictions.Results A total of 185 active compounds of LHQW capsule were screened out, and 263 targets were predicted. Third hundred and fifty-two COVID-19 related target genes were obtained from GeneCards database and OMIM database. GO functional enrichment analysis showed that the biological processes of LHQW capsule treating COVID-19 were closely linked with the regulation of inflammation, immunity, cytokines production, vascular permeability, oxidative stress and apoptosis. KEGG enrichment analysis revealed that the pathways of LHQW capsule treating COVID-19 were significantly enriched in AGE−RAGE signaling pathway in diabetic complications, Kaposi sarcoma−associated herpesvirus infection, TNF, IL−17, and Toll−like receptor (TLR) signaling pathway. The hub targets genes in the gene-related pathways analysis of LHQW capsule treating COVID-19 included MAPK1, MAPK3, RELA, IL-6 and CASP8, which closely associated with inflammation, cytokines storm and apoptosis. Finally, molecular docking showed that top 5 compounds of LHQW capsule also had good binding activities to the important targets in COVID-19.Conclusions The mechanisms of LHQW capsule treating COVID-19 may involve in inhibiting inflammatory response, cytokine storm and virus infection, and regulating immune reactions, apoptosis and endothelial barrier.

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.

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