scholarly journals Network pharmacology based investigation into the bioactive ingredients and molecular mechanisms of QingFeiPaiDu Decoction treating COVID-19

2020 ◽  
Author(s):  
Yan Liu ◽  
Lewen Xiong ◽  
YanYu Wang ◽  
Mengxiong Luo ◽  
Longfei Zhang ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Cellular Response ◽  
Molecular Mechanisms ◽  
Endocrine Resistance ◽  
Hydrolytic Enzyme ◽  
Nitrogen Compound ◽  
Network Pharmacology ◽  
Signal Pathways ◽  
Protein Kinase Activity ◽  
Active Ingredients

Abstract Objective: To study the QingFeiPaiDu Decoction (QFPDD) in the treatment of Corona Virus Disease 2019 (COVID-19) bioactive ingredient and its potential mechanism. Methods: Combined with the clinical symptoms of COVID-19 patients, a "component-target-disease" network model was constructed based on the network pharmacology method, and potential active components, targets and molecular mechanisms of QFPDD for COVID-19 were screened out through topology parameter analysis.Results: We collected 376 active ingredients of QFPDD from the database, and 18833 potential anti-novel coronaviruses (SARS-CoV-2) targets were analyzed and screened. The principal targets involved PIK3CA, PIK3R1, APP, SRC, MAPK1, MAPK3, AKT1, HSP90AA1, EP300, CDK1, etc. We obtained 574 GO entries by Gene Ontology enrichment analysis and obtained 214 signal pathways with P<0.05 by KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analysis. Among them, the antiviral biological processes of QFPDD included a cellular response to nitrogen compound, protein kinase activity, membrane raft, etc. Pathways involved in the regulation include Pathways in cancer, Endocrine resistance, PI3K-Akt signaling pathway, Proteoglycans in cancer, etc. Molecular docking results showed that the core ingredients of QFPDD have a better affinity to the 2019-nCoV 3CL hydrolytic enzyme (Mpro) and angiotensin-converting enzyme 2 (ACE2). Conclusion: Through network pharmacology research and molecular docking verification, this paper preliminarily explored the potential molecular mechanism and relevant active ingredients of QFPDD playing an anti-SARS-CoV-2 role, providing a reference for the further development and utilization of QFPDD and the development of new specific antiviral drugs.

scholarly journals Network pharmacology and molecular docking study on the active ingredients of qidengmingmu capsule for the treatment of diabetic retinopathy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mingxu Zhang ◽  
Jiawei Yang ◽  
Xiulan Zhao ◽  
Ying Zhao ◽  
Siquan Zhu
Keyword(s):  
Diabetic Retinopathy ◽  
Molecular Docking ◽  
Molecular Mechanisms ◽  
Hypoxia Inducible Factor ◽  
Enrichment Analysis ◽  
Docking Study ◽  
Network Pharmacology ◽  
Biological Processes ◽  
Active Ingredients ◽  
Molecular Docking Study

AbstractDiabetic retinopathy (DR) is a leading cause of irreversible blindness globally. Qidengmingmu Capsule (QC) is a Chinese patent medicine used to treat DR, but the molecular mechanism of the treatment remains unknown. In this study, we identified and validated potential molecular mechanisms involved in the treatment of DR with QC via network pharmacology and molecular docking methods. The results of Ingredient-DR Target Network showed that 134 common targets and 20 active ingredients of QC were involved. According to the results of enrichment analysis, 2307 biological processes and 40 pathways were related to the treatment effects. Most of these processes and pathways were important for cell survival and were associated with many key factors in DR, such as vascular endothelial growth factor-A (VEGFA), hypoxia-inducible factor-1A (HIF-1Α), and tumor necrosis factor-α (TNFα). Based on the results of the PPI network and KEGG enrichment analyses, we selected AKT1, HIF-1α, VEGFA, TNFα and their corresponding active ingredients for molecular docking. According to the molecular docking results, several key targets of DR (including AKT1, HIF-1α, VEGFA, and TNFα) can form stable bonds with the corresponding active ingredients of QC. In conclusion, through network pharmacology methods, we found that potential biological mechanisms involved in the alleviation of DR by QC are related to multiple biological processes and signaling pathways. The molecular docking results also provide us with sound directions for further experiments.

scholarly journals Molecular mechanism underlying the hypolipidemic effect of Shanmei Capsule based on network pharmacology and molecular docking

2021 ◽  
Vol 29 ◽  
pp. 239-256
Author(s):  
Qian Wang ◽  
Lijing Du ◽  
Jiana Hong ◽  
Zhenlin Chen ◽  
Huijian Liu ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Molecular Mechanism ◽  
Kegg Pathway ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Signal Pathways ◽  
Hypolipidemic Effect ◽  
Active Ingredients ◽  
Pathway Enrichment

BACKGROUND: Shanmei Capsule is a famous preparation in China. However, the related mechanism of Shanmei Capsule against hyperlipidemia has yet to be revealed. OBJECTIVE: To elucidate underlying mechanism of Shanmei Capsule against hyperlipidemia through network pharmacology approach and molecular docking. METHODS: Active ingredients, targets of Shanmei Capsule as well as targets for hyperlipidemia were screened based on database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were performed via Database for Annotation, Visualization, and Integrated Discovery (DAVID) 6.8 database. Ingredient-target-disease-pathway network was visualized utilizing Cytoscape software and molecular docking was performed by Autodock Vina. RESULTS: Seventeen active ingredients in Shanmei Capsule were screened out with a closely connection with 34 hyperlipidemia-related targets. GO analysis revealed 40 biological processes, 5 cellular components and 29 molecular functions. A total of 15 signal pathways were enriched by KEGG pathway enrichment analysis. The docking results indicated that the binding activities of key ingredients for PPAR-α are equivalent to that of the positive drug lifibrate. CONCLUSIONS: The possible molecular mechanism mainly involved PPAR signaling pathway, Bile secretion and TNF signaling pathway via acting on MAPK8, PPARγ, MMP9, PPARα, FABP4 and NOS2 targets.

scholarly journals Exploring the Mechanisms Underlying the Therapeutic Effect of Salvia Miltiorrhiza Against Diabetic Nephropathy Using Network Pharmacology and Molecular Docking

2020 ◽  
Author(s):  
Li-Li Zhang ◽  
Lin Han ◽  
Xin-Miao Wang ◽  
Yu Wei ◽  
Jing-Hui Zheng ◽  
...  
Keyword(s):  
Diabetic Nephropathy ◽  
Molecular Docking ◽  
Therapeutic Effect ◽  
Molecular Mechanisms ◽  
Function Analysis ◽  
Salvia Miltiorrhiza ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Ppi Network ◽  
Active Ingredients

Abstract BackgroundThe mechanisms underlying the therapeutic effect of Salvia Miltiorrhiza (SM) against diabetic nephropathy (DN) using systematic network pharmacology and molecular docking methods were examined.MethodsTCMSP database was used to screen the active ingredients of SM. Gene targets were obtained using Swiss Target Prediction and TCMSP databases. Related targets of DN were retrieved from the Genecards and DisGeNET databases. Next, a PPI network was constructed using the common targets of SM-DN in the STRING database. The Metascape platform was used for GO function analysis and Cytoscape plug-in ClueGO was used for KEGG pathway enrichment analysis. Molecular docking was performed using iGEMDOCK and AutoDock Vina software. Pymol and LigPlos were used for mapping the network. ResultsSixty-six active ingredients and 189 targets were screened from SM. Among them, 64 targets overlapped with DN targets. The PPI network diagram revealed that AKT1, VEGFA, IL6, TNF, MAPK1, TP53, EGFR, STAT3, MAPK14, and JUN were the top 10 relevant targets. GO and KEGG analyses mainly focused on advanced glycation end products, oxidative stress, inflammatory response, and immune regulation. Molecular docking revealed that the potential target genes closely related to DN, including TNF, NOS2, and AKT1, were more stable in combination with salvianolic acid B, and their stability was better than that of tanshinone IIA.ConclusionThis study reveals the active components and potential molecular mechanisms involved in the therapeutic effect of SM against DN and provides a reference for the wide application of SM in clinically managing DN.

scholarly journals Siteng Fang Reverses Multidrug Resistance in Gastric Cancer: A Network Pharmacology and Molecular Docking Study

2021 ◽  
Vol 11 ◽  
Author(s):  
Lingjian Guo ◽  
Haixia Shi ◽  
Limin Zhu
Keyword(s):  
Gastric Cancer ◽  
Molecular Docking ◽  
Multidrug Resistance ◽  
Signaling Pathway ◽  
Akt Signaling ◽  
Proteoglycan Synthesis ◽  
Network Pharmacology ◽  
Signal Pathways ◽  
Akt Signaling Pathway ◽  
Active Ingredients

Siteng Fang (STF) has been shown to inhibit migration, invasion, and adhesion as well as promote apoptosis in gastric cancer (GC) cells. However, whether it can reverse the multidrug resistance (MDR) of GC to chemotherapy drugs is unknown. Thus, we aimed to elucidate the mechanism of STF in reversing the MDR of GC. The chemical composition of STF and genes related to GC were obtained from the TCMNPAS(TCM Network Pharmacology Analysis System, TCMNPAS) Database, and the targets of the active ingredients were predicted using the Swiss Target Prediction Database. The obtained data were mapped to obtain the key active ingredients and core targets of STF in treating GC. The active component-target network and protein interaction network were constructed by Cytoscape and String database, and the key genes and core active ingredients were obtained. The biological functions and related signal pathways corresponding to the key targets were analyzed and then verified via molecular docking. A total of 14 core active ingredients of STF were screened, as well as 20 corresponding targets, which were mainly enriched in cancer pathway, proteoglycan synthesis, PI3K-AKT signaling pathway, and focal adhesion. Molecular docking showed that the core active ingredients related to MDR, namely quercetin and diosgenin, could bind well to the target. In summary, STF may reverse the MDR of GC and exert synergistic effect with chemotherapeutic drugs. It mediates MDR mainly through the action of quercetin and diosgenin on the PI3K/AKT signaling pathway. These findings are the first to demonstrate the molecular mechanism of STF in reversing MDR in GC, thus providing a direction for follow-up basic research.

scholarly journals Network Pharmacology Study and Molecular Docking on the Mechanism of Treatment of Colorectal Cancer by Xiao-Chai-Hu-Tang

2021 ◽  
Author(s):  
Jingyun Jin ◽  
Bin Chen ◽  
Xiangyang Zhan ◽  
Zhiyi Zhou ◽  
Hui Liu ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Gene Ontology ◽  
Molecular Docking ◽  
Signaling Pathway ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Signal Pathways ◽  
Active Ingredients ◽  
Pathway Gene

Abstract Background and objective: To predict the targets and signal pathways of Xiao-Chai-Hu-Tang (XCHT) in the treatment of colorectal cancer (CRC) based on network pharmacology, to further analyze its anti-CRC material basis and mechanism of action.Methods: TCMSP and TCMID databases were adopted to screen the active ingredients and potential targets of XCHT. CRC-related targets were retrieved by analyzing published microarray data (accession number GSE110224) from the Gene Expression Omnibus (GEO) database. The above common targets were used to construct the “herb-active ingredients-target” network by Cytoscape 3.8.0 software. And then, the protein-to-protein interaction（PPI）was constructed and analyzed with BisoGenet and CytoNCA plug-in in Cytoscape. Gene Ontology (GO) functional and the Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment analysis for target genes were then performed using the R package of cluster Profiler. Further, AutoDock Vina software was used to conduct molecular docking studies on the active ingredients and key targets to verify the network pharmacological analysis results.Results: A total of 71 active ingredients of XCHT and 20 potential targets for anti-CRC were identified. The network analysis revealed that quercetin, stigmasterol, kaempferol, baicalein, acacetin may be the key compounds. And PTGS2, NR3C2, CA2, MMP1 may be the key targets. The active ingredients of XCHT interacted with most disease targets of CRC. It fully showed that XCHT exerted its therapeutic effect through the synergistic action of the multi-compound, multi-target, and multi-pathway. Gene ontology enrichment analysis showed 46 GO entries, including 20 biological processes, 6 cellular components, and 20 molecular functions. 11 KEGG signaling pathways had been identified, including IL-17 signaling pathway, TNF signaling pathway, Toll-like receptor signaling pathway, and NF-kappa B signaling pathway. It showed that XCHT played a role in the treatment of CRC by regulating different signal pathways. Molecular docking confirmed the correlation between five core compounds (including quercetin, stigmasterol, kaempferol, baicalein, and acacetin) and PTGS2.Conclusion: The potential active ingredients, possible targets, and key biological pathways for the efficacy of XCHT in the treatment of CRC were preliminarily described, which provided a theoretical basis for further experimental verification research.

scholarly journals Network pharmacology and molecular docking study on the mechanism of colorectal cancer treatment using Xiao-Chai-Hu-Tang

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0252508
Author(s):  
Jingyun Jin ◽  
Bin Chen ◽  
Xiangyang Zhan ◽  
Zhiyi Zhou ◽  
Hui Liu ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Molecular Docking ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Signaling Pathways ◽  
Target Genes ◽  
Network Pharmacology ◽  
Signal Pathways ◽  
Active Ingredients ◽  
Molecular Docking Study

Background and objective We aimed to predict the targets and signal pathways of Xiao-Chai-Hu-Tang (XCHT) in the treatment of colorectal cancer (CRC) based on network pharmacology, just as well as to further analyze its anti-CRC material basis and mechanism of action. Methods We adopted Traditional Chinese Medicine Systems Pharmacology Database (TCMSP) and Traditional Chinese Medicine Integrated Database (TCMID) databases to screen the active ingredients and potential targets of XCHT. CRC-related targets were retrieved by analyzing published microarray data (accession number GSE110224) from the Gene Expression Omnibus (GEO) database. The common targets were used to construct the “herb-active ingredient-target” network using the Cytoscape 3.8.0 software. Next, we constructed and analyzed protein-to-protein interaction (PPI) using BisoGenet and CytoNCA plug-in in Cytoscape. We then performed Gene Ontology (GO) functional and the Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment analyses of target genes using the R package of clusterProfiler. Furthermore, we used the AutoDock Tools software to conduct molecular docking studies on the active ingredients and key targets to verify the network pharmacological analysis results. Results We identified a total of 71 active XCHT ingredients and 20 potential anti-CRC targets. The network analysis revealed quercetin, stigmasterol, kaempferol, baicalein, and acacetin as potential key compounds, and PTGS2, NR3C2, CA2, and MMP1 as potential key targets. The active ingredients of XCHT interacted with most CRC disease targets. We showed that XCHT’s therapeutic effect was attributed to its synergistic action (multi-compound, multi-target, and multi-pathway). Our GO enrichment analysis showed 46 GO entries, including 20 biological processes, 6 cellular components, and 20 molecular functions. We identified 11 KEGG signaling pathways, including the IL-17, TNF, Toll-like receptor, and NF-kappa B signaling pathways. Our results showed that XCHT could play a role in CRC treatment by regulating different signaling pathways. The molecular docking experiment confirmed the correlation between five core compounds (quercetin, stigmasterol, kaempferol, baicalein, and acacetin) just as well as PTGS2, NR3C2, CA2, and MMP1. Conclusion In this study, we described the potential active ingredients, possible targets, and key biological pathways responsible for the efficacy of XCHT in CRC treatment, providing a theoretical basis for further research.

scholarly journals Decoding the Mechanism of Huanglian Jiedu Decoction in Treating Pneumonia Based on Network Pharmacology and Molecular Docking

2021 ◽  
Vol 9 ◽  
Author(s):  
Xianhai Li ◽  
Hua Tang ◽  
Qiang Tang ◽  
Wei Chen
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Molecular Mechanisms ◽  
Clinical Symptoms ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Interleukin 17 ◽  
Active Ingredients ◽  
Hub Genes

Huang-Lian-Jie-Du decoction (HLJDD) has been used to treat pneumonia for thousands of years in China. However, our understanding of its mechanisms on treating pneumonia is still unclear. In the present work, network pharmacology was used to analyze the potential active ingredients and molecular mechanisms of HLJDD on treating pneumonia. A total of 102 active ingredients were identified from HLJDD, among which 54 were hit by the 69 targets associated with pneumonia. By performing Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, we obtained the main pathways associated with pneumonia and those associated with the mechanism of HLJDD in the treatment of pneumonia. By constructing the protein–protein interaction network of common targets, 10 hub genes were identified, which were mainly involved in the tumor necrosis factor (TNF) signaling pathway, interleukin 17 (IL-17) signaling pathway, and nucleotide-binding oligomerization domain (NOD)-like receptor signaling pathway. Moreover, the results of molecular docking showed that the active ingredients of HLJDD had a good affinity with the hub genes. The final results indicate that HLJDD has a greater effect on bacterial pneumonia than on viral pneumonia. The therapeutic effect is mainly achieved by regulating the host immune inflammatory response and oxidative stress reaction, antibacterial microorganisms, alleviating the clinical symptoms of pneumonia, repairing damaged cells, and inhibiting cell migration.

scholarly journals Study on the Multitarget Mechanism and Key Active Ingredients of Herba Siegesbeckiae and Volatile Oil against Rheumatoid Arthritis Based on Network Pharmacology

2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Xin Yang ◽  
Yahui Li ◽  
Runlin Lv ◽  
Haibing Qian ◽  
Xiangyun Chen ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Molecular Docking ◽  
Essential Oil ◽  
Small Molecule ◽  
Molecular Mechanisms ◽  
Experimental Studies ◽  
Volatile Oil ◽  
Network Pharmacology ◽  
Chemical Components ◽  
Active Ingredients

Background. Herba Siegesbeckiae (HS, Xixiancao in Chinese) is widely used to treat inflammatory joint diseases such as rheumatoid arthritis (RA) and arthritis, and its molecular mechanisms and active ingredients have not been completely elucidated. Methods. In this study, the small molecule ligand library of HS was built based on Traditional Chinese Medicine Systems Pharmacology (TCMSP). The essential oil from HS was extracted through hydrodistillation and analyzed by Gas Chromatography-Mass Spectrometer (GC-MS). The target of RA was screened based on Comparative Toxicogenomics Database (CTD). The key genes were output by the four algorithms’ maximum neighborhood component (MNC), degree, maximal clique centrality (MCC), and stress in cytoHubba in Cytoscape, while biological functions and pathways were also analyzed. The key active ingredients and mechanism of HS and essential oil against RA were verified by molecular docking technology (Sybyl 2.1.1) in treating RA. The interaction between 6 active ingredients (degree ≥ 5) and CSF2, IL1β, TNF, and IL6 was researched based on the software Ligplot. Results. There were 31 small molecule constituents of HS and 16 main chemical components of essential oil (relative content >1%) of HS. There were 47 chemical components in HS. Networks showed that 9 core targets (TNF, IL1β, CSF2, IFNG, CTLA4, IL18, CD26, CXCL8, and IL6) of RA were based on Venn diagrams. In addition, molecular docking simulation indicated that CSF2, IL1β, TNF, and IL6 had good binding activity with the corresponding compounds (degree > 10).The 6 compounds (degree ≥ 5) of HS and essential oil had good interaction with 5 or more targets. Conclusion. This study validated and predicted the mechanism and key active ingredients of HS and volatile oil in treating RA. Additionally, this study provided a good foundation for further experimental studies.

scholarly journals Identification of the active substances and mechanisms of ginger for the treatment of colon cancer based on network pharmacology and molecular docking

2020 ◽  
Author(s):  
MengMeng Zhang ◽  
Dan Wang ◽  
Feng Lu ◽  
Rong Zhao ◽  
Xun Ye ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Molecular Docking ◽  
Cancer Prevention ◽  
Signaling Pathways ◽  
Cellular Response ◽  
Endocrine Resistance ◽  
Docking Simulation ◽  
Network Pharmacology ◽  
Integrated Network ◽  
Colon Cancer Prevention

Abstract Background and objective: Colon cancer is increasing in people recently and ginger (Zingiber officinale), as a commonly used herbal medicine, has been suggested as a potential agent against colon cancer. This study was aimed to identify the bioactive compounds and potential mechanisms of ginger for colon cancer prevention by an integrated network pharmacology approach.Methods: Putative ingredients of ginger and its related targets were discerned from the TCMSP database. After that, the targets interacting with colon cancer were collected using Genecards, OMIM, and Drugbank databases. KEGG pathway and GO enrichment analysis were performed to explore the signaling pathways related to ginger for colon cancer treatments. The PPI and compound-target-disease networks were constructed using Cytoscape.Results: Six potential active compounds, 285 interacting targets in addition to 1356 disease-related targets were collected, of which 118 intersection targets were obtained. A total of 34 key targets including PIK3CA, SRC, and TP53 were identified. These targets were mainly focused on the biological processes of phosphatidylinositol 3-kinase signaling, cellular response to oxidative stress, and cellular response to peptide hormone stimulus. The KEGG enrichment manifested that three signaling pathways were closely related to colon cancer prevention of ginger, including cancer, endocrine resistance, and hepatitis B pathways. TP53, HSP90AA1, MAPK8, JAK2, CASP3, and ERBB2 were viewed as the most important genes, which were validated by molecular docking simulation.Conclusion: This study demonstrated that ginger produced preventive effects against colon cancer by regulating multi-target and multi-pathway with multi-components. And, the combined data provide novel insight for ginger compounds developed as new drug for anti-colon cancer.

scholarly journals Bicuculline From Corydalis Species As A Natural Anti-COVID-19 Drug

2020 ◽  
pp. 1-6
Author(s):  
Shaodong Chen ◽  
Keyword(s):  
Molecular Docking ◽  
Hydrolytic Enzyme ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Network Pharmacology ◽  
Literature Mining ◽  
Pathway Enrichment Analysis ◽  
Active Ingredients ◽  
Target Network

Objective: To perform molecular docking of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) 3CL hydrolytic enzyme (3CLpro) and Angiotensin-Converting Enzyme II (ACE2) receptors, and to seek potential natural anti-COVID-19 drugs using computer virtual screening technology. Methods: In this study, the Autodock Vina software was first used to achieve the molecular docking of the targets, namely, sars-cov-2 3CL hydrolase and ACE2. Then, the herbals acting on 3CLpro and ACE2 receptors were retrieved from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), and the active ingredients were also selected. After that, the chemical-target network was constructed based on the network pharmacology, and the functional enrichment analysis of Gene Ontology (GO) and the pathway enrichment analysis of Kyoto Gene and Genome Encyclopedia (KEGG) were carried out by DAVID to speculate about the mechanism of action of the core drug. Results: A total of six potential anti-COVID-19 active ingredients were selected from natural herbs. They were evaluated by the “ADME” and "Lipinski” rules and their content in the natural herbs were determined by the literature mining method. Finally, Bicuculline was selected as the anti-covid-19 candidate drug. Conclusion: Bicuculline has a stronger ability to combine with 3CLpro and ACE2 than chemical drugs recommended in the clinical practice. Internet pharmacological analysis confirms that Bicuculline can effectively resist COVID-19 pneumonia through multiple pathways.

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