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Analysis of the molecular mechanism of Pudilan (PDL) treatment for COVID-19 by network pharmacology tools.

ABSTRACT: BACKGROUND:Pudilan (PDL), a four-herb prescription with the traditional function of heat-clearing and detoxifying, has been clinically used as an anti-SARS-CoV-2 infectory agent in China. PDL might also have therapeutic potentials for COVID-19 while the underlying mechanisms remain to be clarified. METHODS:We used network pharmacology analysis and selected 68 co-targeted genes/proteins as targets of both PDL and COVID-19. These co-targeted genes/proteins were predicted by SwissDock Server for their high-precision docking simulation, and analyzed by STRING for proteins to protein interaction (PPI), pathway and GO (gene ontology) enrichment. The therapeutic effect for PDL treatment on COVID-19 was validated by the TCMATCOV (TCM Anti COVID-19) platform. RESULTS:PDL might prevent the entrance of SARS-CoV-2 entry into cells by blocking the angiotensin-converting enzyme 2 (ACE2). It might inhibit the cytokine storm by affecting C-reactive protein (CRP), interferon-? (IFN-?), interleukin- 6 (IL-6), interleukin- 10 (IL-10), tumor necrosis factor (TNF), epidermal growth factor receptor (EGFR), C-C motif chemokine ligand 5 (CCL5), transforming growth factor-?1 (TGF?1), and other proteins. PDL might moderate the immune system to shorten the course of the disease, delay disease progression, and reduce the mortality rate. CONCLUSION:PDL might have a therapeutic effect on COVID-19 through three aspects, including the moderate immune system, anti-inflammation, and anti-virus entry into cells.

SUBMITTER: Kong Q

PROVIDER: S-EPMC7260557 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Analysis of the molecular mechanism of Pudilan (PDL) treatment for COVID-19 by network pharmacology tools.

Kong Qi Q Wu Yue Y Gu Yu Y Lv Qi Q Qi Feifei F Gong Shuran S Chen Xiuping X

Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie 20200530

<h4>Background</h4>Pudilan (PDL), a four-herb prescription with the traditional function of heat-clearing and detoxifying, has been clinically used as an anti-SARS-CoV-2 infectory agent in China. PDL might also have therapeutic potentials for COVID-19 while the underlying mechanisms remain to be clarified.<h4>Methods</h4>We used network pharmacology analysis and selected 68 co-targeted genes/proteins as targets of both PDL and COVID-19. These co-targeted genes/proteins were predicted by SwissDoc ...[more]

PMID: 32505821

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Project description:IntroductionThe novel coronavirus pneumonia that broke out in 2019 has become a global epidemic. According to the diagnosis and treatment plan issued in China and the existing clinical data, Shufeng Jiedu (SFJD) Capsule can be effectively used in the treatment of COVID-19 patients. This study aimed to explore its mechanism of action by network pharmacology and molecular docking technology.MethodsThe Chinese Medicine System Pharmacology Analysis Platform (TCMSP), a Bioinformatics Analysis Tool for Molecular mechANism of Traditional Chinese Medicine (BATMAN-TCM), the Encyclopedia of Traditional Chinese Medicine (ETCM) and related literature records were used to search the composition and main active compounds of SFJD, and to screen out the targets of drug components. Disease-associated genes were obtained by the Human Gene Database (GeneCards), the Human Online Mendelian Inheritance Platform (OMIM) and the DisGeNET database, and the co-targeted genes/proteins as targets of both SFJD and COVID-19 were selected by the Comparative Toxicogenomics Database (CTD). Co-targeted genes/proteins were analyzed by STRING, the Database for Annotation, Visualization and Integrated Discovery (DAVID) and Reactome for proteins to protein interaction (PPI), pathway and GO (gene ontology) enrichment, and predicted by AutoDock for their high-precision docking simulation. In addition, the therapeutic effect for SFJD treatment on COVID-19 was validated by the Chinese medicine anti-novel coronavirus pneumonia drug effect prediction and analysis platform (TCMCOVID).ResultsScreening resulted in 163 compounds and 463 targeted genes. The PPI core network contains 76 co-targeted proteins. The Reactome pathways were enriched in signaling by interleukins, immune system, etc. Finally, 6 key proteins of TNF, IL-10, IL-2, IL-6, STAT1 and CCL2 were selected and successfully docked with 4 active ingredients of quercetin, luteolin, wogonin and kaempferol.ConclusionSFJD may play a role in the prevention and treatment of COVID-19 through multiple active compounds acting on multiple targets and then multiple pathways.

Project description:Xuanbai Chengqi Decoction (XBCQD), a classic traditional Chinese medicine, has been widely used to treat COVID-19 in China with remarkable curative effect. However, the chemical composition and potential therapeutic mechanism is still unknown. Here, we used multiple open-source databases and literature mining to select compounds and potential targets for XBCQD. The COVID-19 related targets were collected from GeneCards and NCBI gene databases. After identifying putative targets of XBCQD for the treatment of COVID-19, PPI network was constructed by STRING database. The hub targets were extracted by Cytoscape 3.7.2 and MCODE analysis was carried out to extract modules in the PPI network. R 3.6.3 was used for GO enrichment and KEGG pathway analysis. The effective compounds were obtained via network pharmacology and bioinformatics analysis. Drug-likeness analysis and ADMET assessments were performed to select core compounds. Moreover, interactions between core compounds and hub targets were investigated through molecular docking, molecular dynamic (MD) simulations and MM-PBSA calculations. As a result, we collected 638 targets from 61 compounds of XBCQD and 845 COVID-19 related targets, of which 79 were putative targets. Based on the bioinformatics analysis, 10 core compounds and 34 hub targets of XBCQD for the treatment of COVID-19 were successfully screened. The enrichment analysis of GO and KEGG indicated that XBCQD mainly exerted therapeutic effects on COVID-19 by regulating signal pathways related to viral infection and inflammatory response. Meanwhile, the results of molecular docking showed that there was a stable binding between the core compounds and hub targets. Moreover, MD simulations and MM-PBSA analyses revealed that these compounds exhibited stable conformations and interacted well with hub targets during the simulations. In conclusion, our research comprehensively explained the multi-component, multi-target, and multi-pathway intervention mechanism of XBCQD in the treatment of COVID-19, which provided evidence and new insights for further research.

Project description:BackgroundCoronavirus disease 2019 (COVID-19) is a new global public health emergency. The therapeutic benefits of Cold‒Damp Plague Formula (CDPF) against COVID-19, which was used to treat "cold‒dampness stagnation in the lung" in Trial Versions 6 and 7 of the "Diagnosis and Treatment Protocol for COVID-19", have been demonstrated, but the effective components and their mechanism of action remain unclear.MethodsIn this study, a network pharmacology approach was employed, including drug-likeness evaluation, oral bioavailability prediction, protein‒protein interaction (PPI) network construction and analysis, Gene Ontology (GO) terms, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotation, and virtual docking, to predict the bioactive components, potential targets, and molecular mechanism of CDPF for COVID-19 treatment.ResultsThe active compound of herbs in CDPF and their candidate targets were obtained through database mining, and an herbs-ingredients-targets network was constructed. Subsequently, the candidate targets of the active compounds were compared to those relevant to COVID-19, to identify the potential targets of CDPF for COVID-19 treatment. Subsequently, the PPI network was constructed, which provided a basis for cluster analysis and hub gene screening. The seed targets in the most significant module were selected for further functional annotation. GO enrichment analysis identified four main areas: (1) cellular responses to external stimuli, (2) regulation of blood production and circulation, (3) free radical regulation, (4) immune regulation and anti-inflammatory effects. KEGG pathway analysis also revealed that CDPF could play pharmacological roles against COVID-19 through "multi components‒multi targets‒multi pathways" at the molecular level, mainly involving anti-viral, immune-regulatory, and anti-inflammatory pathways; consequently, a "CDPF-herbs-ingredients-targets-pathways-COVID-19" network was constructed. In hub target analysis, the top hub target IL6, and ACE2, the receptor via which SARS-CoV-2 typically enters host cells, were selected for molecular docking analyses, and revealed good binding activities.ConclusionsThis study revealed the active ingredients and potential molecular mechanism by which CDPF treatment is effective against COVID-19, and provides a reference basis for the wider application and further mechanistic investigations of CDPF in the fight against COVID-19.

Project description:ObjectiveTo explore the target, signaling pathways and their biological functions of Qingfei Paidu Decoction in the treatment of COVID-19 based on network pharmacology and molecular docking technology.MethodsThe active components and target proteins in 21 drugs such as Ephedrae Herba and Pinelliae Rhizoma in Qingfei Paidu decoction were analyzed, and the signaling pathways and biological functions of the target proteins common with COVID-19 were screened by using TCMSP, Swiss Target Prediction, CooLGeN, GeneCards, DAVID and other databases. The network diagram of Qingfei Paidu decoction was constructed using Gephi software.ResultsWe identified 163 active ingredients, including MOL004798, MOL000519, MOL004824, MOL000554, MOL010428, and MOL013443, from 18 drugs in Qingfei Paidu decoction (such as Ephedrae Herba, Pinelliae Rhizoma, Glycyrrhizae Radix Et Rhiizoma, Farfarae Flos, Asteris Radix Et Rhizoma and Aurantii Fructus Immaturus). These ingredients activate renin-angiotensin system signaling pathway and apoptosis signaling pathway by regulating 10 protein targets (ACE, ACE2, AGTR1, FURIN, TNF, CASP3, CASP6, DPP4, MCL1 and POLD1) to execute 42 biological functions such as renin-angiotensin regulation of blood volume and systemic arterial blood pressure to treat COVID-19. The results of preliminary molecular docking showed that MOL000519 (from Pinelliae Rhizoma), MOL000554 (from Farfarae Flos), MOL004798 (from Ephedrae Herba), MOL004824 (from Glycyrrhizae Radix Et Rhiizoma), MOL010428 (from Asteris Radix Et Rhizoma), and MOL013443 (from Aurantii Fructus Immaturus) had good affinity with SARS-CoV-2 3CL hydrolase to form complexes with stable conformations and high binding activity (binding energy ≤- 5 kJ/mol).ConclusionsQingfei Paidu decoction can treat COVID-19 through its multiple medicinal ingredients that have multiple targets and involve multiple signaling pathways for different biological functions. Our finding provides reference for further investigation into the pharmacological mechanism of Qingfei Paidu decoction in treating COVID-19.

Project description:ObjectiveBased on bioinformatics and network pharmacology, the treatment of Saussurea involucrata (SAIN) on novel coronavirus (COVID-19) was evaluated by the GEO clinical sample gene difference analysis, compound-target molecular docking, and molecular dynamics simulation. role in the discovery of new targets for the prevention or treatment of COVID-19, to better serve the discovery and clinical application of new drugs.Materials and methodsTaking the Traditional Chinese Medicine System Pharmacology Database (TCMSP) as the starting point for the preliminary selection of compounds and targets, we used tools such as Cytoscape 3.8.0, TBtools 1.098, AutoDock vina, R 4.0.2, PyMol, and GROMACS to analyze the compounds of SAIN and targets were initially screened. To further screen the active ingredients and targets, we carried out genetic difference analysis (n = 72) through clinical samples of COVID-19 derived from GEO and carried out biological process (BP) analysis on these screened targets (P ≤ 0.05)., gene = 9), KEGG pathway analysis (FDR≤0.05, gene = 9), protein interaction network (PPI) analysis (gene = 9), and compounds-target-pathway network analysis (gene = 9), to obtain the target Point-regulated biological processes, disease pathways, and compounds-target-pathway relationships. Through the precise molecular docking between the compounds and the targets, we further screened SAIN's active ingredients (Affinity ≤ -7.2 kcal/mol) targets and visualized the data. After that, we performed molecular dynamics simulations and consulted a large number of related Validation of the results in the literature.ResultsThrough the screening, analysis, and verification of the data, it was finally confirmed that there are five main active ingredients in SAIN, which are Quercitrin, Rutin, Caffeic acid, Jaceosidin, and Beta-sitosterol, and mainly act on five targets. These targets mainly regulate Tuberculosis, TNF signaling pathway, Alzheimer's disease, Pertussis, Toll-like receptor signaling pathway, Influenza A, Non-alcoholic fatty liver disease (NAFLD), Neuroactive ligand-receptor interaction, Complement and coagulation cascades, Fructose and mannose metabolism, and Metabolic pathways, play a role in preventing or treating COVID-19. Molecular dynamics simulation results show that the four active ingredients of SAIN, Quercitrin, Rutin, Caffeic acid, and Jaceosidin, act on the four target proteins of COVID-19, AKR1B1, C5AR1, GSK3B, and IL1B to form complexes that can be very stable in the human environment. Tertiary structure exists.ConclusionOur study successfully explained the effective mechanism of SAIN in improving COVID-19, and at the same time predicted the potential targets of SAIN in the treatment of COVID-19, AKR1B1, IL1B, and GSK3B. It provides a new basis and provides great support for subsequent research on COVID-19.

Dataset Information

Analysis of the molecular mechanism of Pudilan (PDL) treatment for COVID-19 by network pharmacology tools.

Publications

Analysis of the molecular mechanism of Pudilan (PDL) treatment for COVID-19 by network pharmacology tools.

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