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Molecular Networking, Network Pharmacology, and Molecular Docking Approaches Employed to Investigate the Changes in Ephedrae Herba before and after Honey-Processing.

ABSTRACT: Raw Ephedrae herba (REH) and honey-processed Ephedrae herba (HEH) were the different decoction pieces of Ephedrae herba (EH). Honey-processing that changes REH into HEH has been shown to relieve cough and asthma to a synergistic extent. However, the chemical markers and the synergistic mechanism of HEH need to be further studied. In this study, the ultra-high performance liquid chromatography coupled with hybrid quadrupole time of flight mass spectrometry (UPLC-Q-TOF-MS) and molecular networking (MN) were used to investigate the chemical composition of REH and HEH, which led to the identification of 92 compounds. A total of 38 differential chemical markers for REH and HEH were identified using principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA). Network pharmacology suggests that the synergistic effect of HEH in relieving cough and asthma may be due to 31 differential chemical markers acting through 111 biological targets. Among them, four compounds and two targets probably played an important role based on the results of molecular docking. This study enriched our knowledge about the chemical composition of REH and HEH, as well as the synergistic mechanism of HEH.

SUBMITTER: Li H

PROVIDER: S-EPMC9268138 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Investigating the Mechanism of <i>Scutellariae barbata</i> Herba in the Treatment of Colorectal Cancer by Network Pharmacology and Molecular Docking.

Project description:BackgroundColorectal cancer (CRC) is one of the most common gastrointestinal tumors, which accounts for approximately 10% of all diagnosed cancers and cancer deaths worldwide per year. Scutellariae barbatae Herba (SBH) is one of the most frequently used traditional Chinese medicine (TCM) in the treatment of CRC. Although many experiments have been carried out to explain the mechanisms of SBH, the mechanisms of SBH have not been illuminated fully. Thus, we constructed a network pharmacology and molecular docking to investigate the mechanisms of SBH.MethodsWe adopted active constituent prescreening, target predicting, protein-protein interaction (PPI) analysis, Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, differentially expressed gene analysis, and molecular docking to establish a system pharmacology database of SBH against CRC.ResultsA total of 64 active constituents of SBH were obtained and 377 targets were predicted, and the result indicated that quercetin, luteolin, wogonin, and apigenin were the main active constituents of SBH. Glucocorticoid receptor (NR3C1), pPhosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha isoform (PIK3CA), cellular tumor antigen p53 (TP53), transcription factor AP-1 (JUN), mitogen-activated protein kinase 1 (MAPK1), Myc protooncogene protein (MYC), cyclin-dependent kinase 1 (CDK1), and broad substrate specificity ATP-binding cassette transporter ABCG2 (ABCG2) were the major targets of SBH in the treatment of CRC. GO analysis illustrated that the core biological process regulated by SBH was the regulation of the cell cycle. Thirty pathways were presented and 8 pathways related to CRC were involved. Molecular docking presented the binding details of 3 key targets with 6 active constituents.ConclusionsThe mechanisms of SBH against CRC depend on the synergistic effect of multiple active constituents, multiple targets, and multiple pathways.

| S-EPMC8352706 | biostudies-literature

Integrating Network Pharmacology, Molecular Docking, and Experimental Validation to Investigate the Mechanism of (-)-Guaiol Against Lung Adenocarcinoma.

Project description:BACKGROUND Lung adenocarcinoma (LUAD) is the most common type of lung cancer, which poses a serious threat to human life and health. -(-)Guaiol, an effective ingredient of many medicinal herbs, has been shown to have a high potential for tumor interference and suppression. However, knowledge of pharmacological mechanisms is still lacking adequate identification or interpretation. MATERIAL AND METHODS The genes of LUAD patients collected from TCGA were analyzed using limma and WGCNA. In addition, targets of (-)-Guaiol treating LUAD were selected through a prediction network. Venn analysis was then used to visualize the overlapping genes, which were further condensed using the PPI network. GO and KEGG analyses were performed sequentially, and the essential targets were evaluated and validated using molecular docking. In addition, cell-based verification, including the CCK-8 assay, cell death assessment, apoptosis analysis, and western blot, was performed to determine the mechanism of action of (-)-Guaiol. RESULTS The genes included 959 differentially-expressed genes, 6075 highly-correlated genes, and 480 drug-target genes. Through multivariate analysis, 23 hub genes were identified and functional enrichment analyses revealed that the PI3K/Akt signaling pathway was the most significant. Experiment results showed that -(-)Guaiol can inhibit LUAD cell growth and induce apoptosis. Additional evidence suggested that the PI3K/Akt signaling pathway established an inseparable role in the antitumor processes of -(-)Guaiol, which is consistent with network pharmacology results. CONCLUSIONS Our results show that the effect of (-)-Guaiol in LUAD treatment involves the PI3K/Akt signaling pathway, providing a useful reference and medicinal value in the treatment of LUAD.

| S-EPMC9336205 | biostudies-literature

Network pharmacology- and molecular docking-based approaches to unveil the pharmacological mechanisms of dihydroartemisinin against esophageal carcinoma.

Project description:Objective: Dihydroartemisinin (DHA) is an active metabolite of artemisinin and its derivatives, which is a potent drug extensively applied in clinical treatment of malaria. The antitumor properties of DHA have received increasing attention. However, there is no systematic summary on the pharmacological mechanisms of DHA against esophageal carcinoma (ESCA). The present study implemented network pharmacology- and molecular docking-based approaches to unveil the pharmacological mechanisms of DHA against ESCA. Methods: DHA targets were accessed through integrating the SwissTargetPrediction, HERB, as well as BATMAN-TCM platforms. In TCGA-ESCA dataset, genes with differential expression were screened between 161 ESCA and 11 normal tissue specimens. DHA targets against ESCA were obtained through intersection. Their biological significance was evaluated with functional enrichment analysis. A prognostic signature was established via uni- and multivariate cox regression analyses. DHA-target interactions were predicted via molecular docking. Molecular dynamics simulation was implemented to examine the stability of DHA binding to potential targets. Results: The study predicted 160 DHA targets as well as 821 genes with differential expression in ESCA. Afterwards, 16 DHA targets against ESCA were obtained, which remarkably correlated to cell cycle progression. The ADORA2B- and AURKA-based prognostic signature exhibited the reliability and independency in survival prediction. The stable docking of DHA-ADORA2B and DHA-AURKA was confirmed. Conclusion: Collectively, this study systematically revealed the basis and mechanism of DHA against ESCA through targeting multi-target and multi-pathway mechanisms, and thus offered theoretical and scientific basis for the clinical application of DHA.

| S-EPMC9732420 | biostudies-literature

A Combined Network Pharmacology and Molecular Docking Approach to Investigate Candidate Active Components and Multitarget Mechanisms of Hemerocallis Flowers on Antidepressant Effect.

Project description:ObjectiveThe purpose of our research is to systematically explore the multiple mechanisms of Hemerocallis fulva Flowers (HF) on depressive disorder (DD).MethodsThe components of HF were searched from the literature. The targets of components were obtained from PharmMapper. After that, Cytoscape software was used to build a component-target network. The targets of DD were collected from DisGeNET, PharmGKB, TTD, and OMIM. Protein-protein interactions (PPIs) among the DD targets were executed to screen the key targets. Afterward, the GO and KEGG pathway enrichment analysis were performed by the KOBAS database. A compound-target-KEGG pathway network was built to analyze the key compounds and targets. Finally, the potential active substances and targets were validated by molecular docking.ResultsA total of 55 active compounds in HF, 646 compound-related targets, and 527 DD-related targets were identified from public databases. After treated with PPI, 219 key targets of DD were acquired. The gene enrichment analysis suggested that HF probably benefits DD patients by modulating pathways related to the nervous system, endocrine system, amino acid metabolism, and signal transduction. The network analysis showed the critical components and targets of HF on DD. Results of molecular docking increased the reliability of this study.ConclusionsIt predicted and verified the pharmacological and molecular mechanism of HF against DD from a holistic perspective, which will also lay a foundation for further experimental research and rational clinical application of DD.

| S-EPMC8266453 | biostudies-literature

Integrated meta-analysis, network pharmacology, and molecular docking to investigate the efficacy and potential pharmacological mechanism of Kai-Xin-San on Alzheimer's disease.

Project description:ContextKai-Xin-San (KXS) has been used to treat Alzheimer's disease (AD) for thousands of years. However, no quantitative data regarding AD treatment using KXS are available. Moreover, its active compounds and mechanism of action for the treatment of AD remain largely unclear.ObjectivesTo evaluate the efficacy and the potential pharmacological mechanisms of KXS in AD treatment.Materials and methodsA systematic collection of KXS experiments was conducted from PubMed, Web of Science, Embase, CNKI, VIP, and Wanfang Data up to February, 2020. Review Manager 5 software was used for meta-analysis. In network pharmacology, components of KXS were screened, AD-related genes were then identified and the 'component-target-pathway' network constructed. Molecular docking was finally employed for in silico simulation matching between representative KXS compounds and their target genes.ResultsMeta-analysis revealed that KXS improves the cognitive benefits in AD models by reducing the time of escape latency (SMD = -16.84) as well as increasing the number of cross-platform (SMD = 2.56) and proportion of time in the target quadrant (SMD = 7.52). Network pharmacology identified 25 KXS active compounds and 44 genes targets. DRD2, MAOA, ACHE, ADRA2A and CHRM2 were core target proteins. Besides, 22 potential pathways of KXS were identified, like cholinergic synapses, the cGMP/PKG pathway and calcium signalling. Molecular docking showed that stigmasterol, aposcopolamine and inermin can closely bind three targets (ACHE, ADRA2A and CHRM2).Discussion and conclusionThese findings suggest that KXS exerts effect on AD through multi-target, multi-component and multi-pathway mechanism. Future studies may explore the active components of KXS.

| S-EPMC7534219 | biostudies-literature

Integrating Network Pharmacology and Molecular Docking Approaches to Decipher the Multi-Target Pharmacological Mechanism of Abrus precatorius L. Acting on Diabetes.

Project description:Type 2 diabetes mellitus (T2DM) is a notable health care load that imposes a serious impact on the quality of life of patients. The small amount of reported data and multiple spectra of pathophysiological mechanisms of T2DM make it a challenging task and serious economic burden in health care management. Abrus precatorius L. is a slender, perennial, deciduous, and woody twining plant used in various regions of Asia to treat a variety of ailments, including diabetes mellitus. Various in vitro studies revealed the therapeutic significance of A. precatorius against diabetes. However, the exact molecular mechanism remains unclarified. In the present study, a network pharmacology technique was employed to uncover the active ingredients, their potential targets, and signaling pathways in A. precatorius for the treatment of T2DM. In the framework of this study, we explored the active ingredient-target-pathway network and figured out that abrectorin, abrusin, abrisapogenol J, sophoradiol, cholanoic acid, precatorine, and cycloartenol decisively contributed to the development of T2DM by affecting AKT1, MAPK3, TNFalpha, and MAPK1 genes. Later, molecular docking was employed to validate the successful activity of the active compounds against potential targets. Lastly, we conclude that four highly active constituents, namely, abrusin, abrisapogenol J, precatorine, and cycloartenol, help in improving the body's sensitivity to insulin and regulate the expression of AKT1, MAPK3, TNFalpha, and MAPK1, which may act as potential therapeutic targets of T2DM. Integrated network pharmacology and docking analysis revealed that A. precatorius exerted a promising preventive effect on T2DM by acting on diabetes-associated signaling pathways. This provides a basis to understand the mechanism of the anti-diabetes activity of A. precatorius.

| S-EPMC9029140 | biostudies-literature

Network pharmacology and molecular docking approaches predict the mechanisms of Corididius chinensis in treating manganese-induced nervous system diseases: A review.

Project description:Neurotoxicity could be induced by long exposure to manganese (Mn). The traditional Chinese medicine, Corididius chinensis (Cc) has been proven to have a certain curative effect on Mn poisoning. Therefore, network pharmacology was performed to explore potential therapeutic targets and pharmacological mechanisms of Cc. We found ingredients by building our own database through literature, (which is the first to screen traditional Chinese medicine without traditional Chinese medicine systems pharmacology database and analysis platform databases and it is applicable whenever a Chinese medicine is not found in the traditional Chinese medicine systems pharmacology database and analysis platform database) and potential targets of Mn-induced nervous system diseases from the OMIM, GeneCards, and DrugBank database were identified. A protein-protein interaction network was constructed using Cytoscape. Gene ontology and Kyoto encyclopedia of genes and genomes pathway enrichment analysis was performed for the treatment of Mn-induced nervous system disease, and molecular docking was carried out to verify the results of network pharmacology analysis. After screening disease-related genes, 12 intersecting genes overlapped between 284 target proteins of the active compound and 195 potential disease targets. The pathways of neurodegeneration_multiple diseases and Alzheimer disease pathway may be the most potential pathway of Cc treating Mn-induced nervous system diseases. CASP9 and PTGS2 in neurodegeneration_multiple diseases, NOS1, NOS2 in Alzheimer disease pathway were identified as core targets. Especially, molecule docking analysis unveil that aspongpyrazine A docking NOS2 is the most potential therapeutic drug and target, which primarily involved in the processes of oxidative stress and inflammation.

| S-EPMC10615487 | biostudies-literature

Network Pharmacology-Based Approach to Investigate the Molecular Targets of Rhubarb for Treating Cancer.

Project description:BackgroundAs a traditional Chinese medicine, rhubarb (also named Dahuang) is used to treat various diseases.ObjectiveTo explore the possible antitumor mechanism of rhubarb by using network pharmacology and molecular docking in this study.MethodsBioactive ingredients and related targets of rhubarb were obtained from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. And the gene names corresponding to the proteins were found in the UniProt database. Then, the tumor-related targets were screened out from GeneCards and OMIM databases. Key antitumor targets of rhubarb were acquired by overlapping the above targets via the Venn diagram. The antitumor targets network of rhubarb active components was constructed by using Cytoscape 3.6.0 software. The protein interactions network was constructed using the STRING database. The GO and KEGG pathways involved in the targets were analyzed by using the DAVID database. Autodock Vina software was used to verify the molecular docking of rhubarb components and key targets.ResultsThrough screening and analysis, 10 active ingredients and 58 antitumor prediction targets were obtained and constructed a compound-target network. The targets such as CASP3, JUN, MYC, TNF, and PTGS2 may play a crucial role. These targets are involved in cancer pathway, calcium signaling pathway, cell apoptosis, small-cell lung cancer pathway, p53 signaling pathway, and TNF signaling pathway. The docking results indicated that the rhein binding with the CASP3 showed the highest binding energy.ConclusionBased on the network pharmacology, the characteristics of multicomponent, multitarget, and multipathway of rhubarb were discussed, which provided a scientific basis for explaining the mechanism in treating cancer and new ideas for further research.

| S-EPMC8208856 | biostudies-literature

Investigate the binding of catechins to trypsin using docking and molecular dynamics simulation.

Project description:To explore the inhibitory mechanism of catechins for digestive enzymes, we investigated the binding mode of catechins to a typical digestive enzyme-trypsin and analyzed the structure-activity relationship of catechins, using an integration of molecular docking, molecular dynamics simulation and binding free energy calculation. We found that catechins with different structures bound to a conservative pocket S1 of trypsin, which is comprised of residues 189-195, 214-220 and 225-228. In the trypsin-catechin complexes, Asp189 by forming strong hydrogen bonding, and Gln192, Trp215 and Gly216 through hydrophobic interactions, all significantly contribute to the binding of catechins. The number and the position of hydroxyl and aromatic groups, the structure of stereoisomers, and the orientation of catechins in the binding pocket S1 of trypsin all affect the binding affinity. The binding affinity is in the order of Epigallocatechin gallate (EGCG) > Epicatechin gallate (ECG) > Epicatechin (EC) > Epigallocatechin (EGC), and 2R-3R EGCG shows the strongest binding affinity out of other stereoisomers. Meanwhile, the synergic conformational changes of residues and catechins were also analyzed. These findings will be helpful in understanding the knowledge of interactions between catechins and trypsin and referable for the design of novel polyphenol based functional food and nutriceutical formulas.

| S-EPMC4418572 | biostudies-literature

Network Pharmacology Integrated Molecular Docking Reveals the Antiosteosarcoma Mechanism of Biochanin A.

Project description:BackgroundAs the malignant tumor with the highest incidence in teenagers, osteosarcoma has become a major problem in oncology research. In addition to surgical management, the pharmacotherapeutic strategy for osteosarcoma treatment is an attractive way to explore. It has been demonstrated that biochanin A has an antitumor capacity on multiple kinds of solid tumor, including osteosarcoma. But the precise mechanism of biochanin A against osteosarcoma is still needed to be discovered.ObjectiveTo identify the potential therapeutic targets of biochanin A in treating osteosarcoma.MethodsIn present study, an integrated approach including network pharmacology and molecular docking technique was conducted, which mainly comprises target prediction, network construction, gene ontology, and pathway enrichment. CCK8 test was employed to evaluate the cell viability of MG63 cells. Western-blot was used to verify the target proteins of biochanin A.ResultsNinety-six and 114 proteins were obtained as the targets of biochanin A and osteosarcoma, respectively. TP53, IGF1, JUN, BGLAP, ATM, MAPK1, ATF3, H2AFX, BAX, CDKN2A, and EGF were identified as the potential targets of biochanin A against osteosarcoma. Based on the western-blot detection, the expression of BGLAP, BAX, and ATF3 in MG63 cell line changed under the treatment of biochanin A.ConclusionBiochanin A can effectively suppress the proliferation of osteosarcoma and regulate the expression of BGLAP, BAX, and ATF3, which may act as the potential therapeutic targets of osteosarcoma.

| S-EPMC6339762 | biostudies-literature

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