Uncovering Mechanisms of Zanthoxylum piperitum Fruits for the Alleviation of Rheumatoid Arthritis Based on Network Pharmacology

Potential of Gut Microbial Metabolites in Treating Osteoporosis and Obesity: A Network Pharmacology and Bioinformatics Approach

BACKGROUND The gut microbial metabolites demonstrate significant activity against metabolic diseases including osteoporosis (OP) and obesity, but active compounds, targets, and mechanisms have not been fully identified. Hence, the current investigation explored the mechanisms of active metabolites and targets against OP and obesity by using network pharmacology approaches. MATERIAL AND METHODS The gutMGene database was used to collect gut microbial targets-associated metabolites; DisGeNET and OMIM databases were used to identify targets relevant to OP and obesity. A total of 63 and 89 overlapped targets were considered the final OP and obesity targets after creating a Venn diagram of metabolites-related targets and disease-related targets. Furthermore, the top 20% of degrees, betweenness, and closeness were used to form the sub-network of protein-protein interaction of these targets. Finally, the biotransformation-increased receptors and biological mechanisms were identified and validated using ADMET properties analysis, molecular docking, and molecular dynamic simulation. RESULTS GO, KEGG pathway analysis, and protein-protein interactions were performed to establish metabolites and target networks. According to the enrichment analysis, OP and obesity are highly linked to the lipid and atherosclerosis pathways. Moreover, ADMET analysis depicts that the major metabolites have drug-likeliness activity and no or less toxicity. Following that, the molecular docking studies showed that compound K and TP53 target have a remarkable negative affinity (-8.0 kcal/mol) among all metabolites and targets for both diseases. Finally, the conformity of compound K against the targeted protein TP53 was validated by 250ns MD simulation. CONCLUSIONS Therefore, we summarized that compound K can regulate TP53 and could be developed as a therapy option for OP and obesity.

Bioactive Compounds and Signaling Pathways of Wolfiporia extensa in Suppressing Inflammatory Response by Network Pharmacology

Wolfiporia extensa (WE) is a medicinal mushroom and an excellent source of naturally occurring anti-inflammatory substances. However, the particular bioactive compound(s) and mechanism(s) of action against inflammation have yet to be determined. Here, we studied anti-inflammatory bioactive compounds and their molecular mechanisms through network pharmacology. Methanol (ME) extract of WE (MEWE) was used for GC-MS analysis to identify the bioactives, which were screened by following Lipinski’s rules. Public databases were used to extract selected bioactives and inflammation-related targets, and Venn diagrams exposed the common targets. Then, STRING and Cytoscape tools were used to construct protein-protein (PPI) network and mushroom-bioactives-target (M-C-T) networks. Gene Ontology and KEGG pathway analysis were performed by accessing the DAVID database and molecular docking was conducted to validate the findings. The chemical reactivity of key compounds and standard drugs was explored by the computational quantum mechanical modelling method (DFT study). Results from GC-MS revealed 27 bioactives, and all obeyed Lipinski’s rules. The public databases uncovered 284 compound-related targets and 7283 inflammation targets. A Venn diagram pointed to 42 common targets which were manifested in the PPI and M-C-T networks. KEGG analysis pointed to the HIF-1 signaling pathway and, hence, the suggested strategy for preventing the onset of inflammatory response was inhibition of downstream NFKB, MAPK, mTOR, and PI3K-Akt signaling cascades. Molecular docking revealed the strongest binding affinity for “N-(3-chlorophenyl) naphthyl carboxamide” on five target proteins associated with the HIF-1 signaling pathway. Compared to the standard drug utilized in the DFT (Density Functional Theory) analysis, the proposed bioactive showed a good electron donor component and a reduced chemical hardness energy. Our research pinpoints the therapeutic efficiency of MEWE and this work suggests a key bioactive compound and its action mechanism against inflammation.

The Abundant Phytocannabinoids in Rheumatoid Arthritis: Therapeutic Targets and Molecular Processes Identified Using Integrated Bioinformatics and Network Pharmacology

The endocannabinoid system consists of several phytocannabinoids, cannabinoid receptors, and enzymes that aid in numerous steps necessary to manifest any pharmacological activity. It is well known that the endocannabinoid system inhibits the pathogenesis of the inflammatory and autoimmune disease rheumatoid arthritis (RA). To the best of our knowledge, no research has been done that explains the network-pharmacology-based anti-rheumatic processes by focusing on the endocannabinoid system. Therefore, the purpose of this study is to further our understanding of the signaling pathways, associated proteins, and genes underlying RA based on the abundant natural endocannabinoids. The knowledge on how the phytocannabinoids in Cannabis sativa affect the endocannabinoid system was gathered from the literature. SwissTarget prediction and BindingDB databases were used to anticipate the targets for the phytocannabinoids. The genes related to RA were retrieved from the DisGeNET and GeneCards databases. Protein–protein interactions (high confidence > 0.7) were carried out with the aid of the string web server and displayed using Cytoscape. The Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathway analysis was used to perform enrichment analyses on the endocannabinoid–RA common targets. ShinyGO 0.76 was used to predict the biological processes listed in the Gene Ontology (GO) classification system. The binding affinity between the ligand and the receptors was precisely understood using molecular docking, induced-fit docking, and a molecular dynamics simulation. The network pharmacology analyses predicted that processes like response to oxygen-containing compounds and peptodyl-amino acid modification are related to the potential mechanisms of treatment for RA. These biological actions are coordinated by cancer, neuroactive ligand–receptor interaction, lipids and atherosclerosis, the calcium signaling pathway, and the Rap1 signaling pathway. According to the results of molecular docking, in the context of RA, phytocannabinoids may bind to important target proteins such PIK3CA, AKT1, MAPK9, PRKCD, BRAF, IGF1R, and NOS3. This entire study predicted the phytocannabinoids’ systemic biological characteristics. Future experimental research is needed, however, to confirm the results so far.

Elucidation of Prebiotics, Probiotics, Postbiotics, and Target from Gut Microbiota to Alleviate Obesity via Network Pharmacology Study

The metabolites produced by the gut microbiota have been reported as crucial agents against obesity; however, their key targets have not been revealed completely in complex microbiome systems. Hence, the aim of this study was to decipher promising prebiotics, probiotics, postbiotics, and more importantly, key target(s) via a network pharmacology approach. First, we retrieved the metabolites related to gut microbes from the gutMGene database. Then, we performed a meta-analysis to identify metabolite-related targets via the similarity ensemble approach (SEA) and SwissTargetPrediction (STP), and obesity-related targets were identified by DisGeNET and OMIM databases. After selecting the overlapping targets, we adopted topological analysis to identify core targets against obesity. Furthermore, we employed the integrated networks to microbiota-substrate-metabolite-target (MSMT) via R Package. Finally, we performed a molecular docking test (MDT) to verify the binding affinity between metabolite(s) and target(s) with the Autodock 1.5.6 tool. Based on holistic viewpoints, we performed a filtering step to discover the core targets through topological analysis. Then, we implemented protein-protein interaction (PPI) networks with 342 overlapping target, another subnetwork was constructed with the top 30% degree centrality (DC), and the final core networks were obtained after screening the top 30% betweenness centrality (BC). The final core targets were IL6, AKT1, and ALB. We showed that the three core targets interacted with three other components via the MSMT network in alleviating obesity, i.e., four microbiota, two substrates, and six metabolites. The MDT confirmed that equol (postbiotics) converted from isoflavone (prebiotics) via Lactobacillus paracasei JS1 (probiotics) can bind the most stably on IL6 (target) compared with the other four metabolites (3-indolepropionic acid, trimethylamine oxide, butyrate, and acetate). In this study, we demonstrated that the promising substate (prebiotics), microbe (probiotics), metabolite (postbiotics), and target are suitable for obsesity treatment, providing a microbiome basis for further research.

Network pharmacology-based study to identify the significant pathways of Lentinula edodes against cancer

Lentinula edodes (LE) is known as a good food source with potent anticancer efficacy, but its active chemical compounds and pathways against cancer have not been revealed. This study was to uncover the active chemical constituents and pathways of LE against cancer through network pharmacology. The chemical compositions were recognized by gas chromatography-mass spectrometry (GC-MS) and filtered drug-like compounds (DLCs) by SwissADME. Targets related to filtered compounds were recognized by two public databases and the final overlapping targets were identified by Venn diagram. Then, protein-protein interaction (PPI) and pathway-target-compound (PTC) networks were built by RStudio. Ultimately, we recognized the key compounds and targets via molecular docking test (MDT). A total of 33 compounds from LE were accepted by Lipinski's rule were selected as DLCs. The 33 compounds were associated with 108 targets and a key target (cyclooxygenase2 [COX2]) was identified through PPI networks. Most significantly, inactivation of pathways in cancer and activation of peroxisome proliferator activated receptor signaling pathway were significant pathways of LE. On MDT, we identified a key compound (Indole, 2-methyl-3-phenyl) on COX2 related to inactivation of athways in cancer, additionally, the number of 6 ergostane steroids was associated with the two pathways might be dual efficacy to alleviate inflammation against cancer. Overall, 13 targets, 11 compounds, and 2 key pathways of LE were identified as the significant elements to treat cancer. Hence, this study shows therapeutic evidence to verify the promising clinical effect of LE on cancer, suggesting that LE might be an important mushroom against cancer. PRACTICAL APPLICATIONS: Lentinula edodes (LE) has been used widely in cuisine as well as alternative medicines, especially, for anticancer. The LE has rich nutritional compounds including proteins, vitamins, polyphenols, and glucans, however, most of which have a critical hurdle as poor bioavailability not to be applicable for pharmaceuticals. Its main cause is very hydrophilic property. Thus, we adopted GC-MS analysis to identify lipophilic compounds to enhance cell permeability involved in bioavailability. The compounds selected from LE were confirmed by Lipinski's rule for drug-like-compounds (DLCs). Then, we retrieved targets associated with DLCs, and multiple pathways, multiple targets, and multiple compounds against cancer on network-based analysis. In summary, our study reveals the medicinal value of LE on cancer based on the multicomponents. Overall, the aim of this work is to represent the pharmacological evidence to reveal the therapeutic efficacy of AC on cancer, suggesting that DLCs from AC might be alleviators to dampen cancer.

Network Pharmacology Study to Reveal the Potentiality of a Methanol Extract of Caesalpinia sappan L. Wood against Type-2 Diabetes Mellitus

Caesalpinia sappan L. (CS) is widely used to treat diabetic complications in south-east Asia, specifically in traditional Chinese medicine. This study intends to explain the molecular mechanism of how chemical constituents of CS interrelate with different signaling pathways and receptors involved in T2DM. GC-MS was employed to identify the chemical compounds from the methanol extract of CS wood (MECSW). Lipinski’s rule of five was applied, and 33 bioactive constituents have been screened from the CS extract. After that, 124 common targets and 26 compounds associated with T2DM were identified by mining several public databases. Protein–protein interactions and compound-target network were constructed using the STRING database and Cytoscape tool. Protein–protein interactions were identified in 121 interconnected nodes active in T2DM and peroxisome proliferator-activated receptor gamma (PPARG) as key target receptors. Furthermore, pathway compound target (PCT) analysis using the merger algorithm plugin of Cytoscape revealed 121 nodes from common T2DM targets, 33 nodes from MECSW compounds and 9 nodes of the KEGG pathway. Moreover, network topology analysis determined “Fisetin tetramethyl ether” as the key chemical compound. The DAVID online tool determined seven signaling receptors, among which PPARG was found most significant in T2DM progression. Gene ontology and KEGG pathway analysis implied the involvement of nine pathways, and the peroxisome proliferator-activated receptor (PPAR) pathway was selected as the hub signaling pathway. Finally, molecular docking and quantum chemistry analysis confirmed the strong binding affinity and reactive chemical nature of fisetin tetramethyl ether with target receptors exceeding that of the conventional drug (metformin), PPARs agonist (rosiglitazone) and co-crystallized ligands, indicating that fisetin could be a potential drug of choice in T2DM management. This study depicts the interrelationship of the bioactive compounds of MECSW with the T2DM-associated signaling pathways and target receptors. It also proposes a more pharmaceutically effective substance, fisetin tetramethyl ether, over the standard drug that activates PPARG protein in the PPAR signaling pathway of T2DM.

The Promising Mechanisms of Low Molecular Weight Compounds of Panax Ginseng C.A. Meyer in Alleviating COVID-19: A Network Pharmacology Analysis

Panax Ginseng C.A. Meyer (PGCAM) is a well-known phytomedicine, but most of its compounds, such as ginsenoside derivatives, have poor absorption and bioavailability profile due to high molecular weight (≥500 Daltons), which is the major hurdle for their clinical application. Hence, this research explored the efficiency of low molecular weight compounds (LMWCs) (<500 Daltons) screened from PGCAM and their anti-COVID-19 mechanisms through network pharmacology. Molecular compounds from PGCAM were identified using public databases and filtered out by the drug-likeness evaluation. Genes interacted with these filtered compounds, and COVID-19-related genes were extracted from public databases. In addition, overlapping genes between compounds and interactive genes were identified using the Venn diagram. In parallel, the networking between compounds and overlapping genes was analyzed by RStudio. The pathway enrichment analysis of overlapping genes was determined by STRING. Finally, the key bioactive compounds were documented through virtual screening. The bubble chart suggested that the mechanisms of PGCAM against COVID-19 were related to 28 signaling pathways. The key molecular anti-COVID-19 mechanisms might be the anti-inflammation, anti-permeability, and pro-apoptosis by inactivating the PI3K-Akt signaling pathway. The six key genes and the five compounds related to the PI3K-Akt signaling pathway were RELA-paeonol, NFKB1-frutinone A, IL6-nepetin, MCL1-ramalic acid, VEGFA-trifolirhizin, and IL2-trifolirhizin. The docking between these key genes and compounds demonstrated promising binding affinity with a good binding score. Overall, our proposed LMWCs from PGCAM provide a fundamental basis with noteworthy pharmacological evidence to support the therapeutic efficacy of PGCAM in relieving the main symptoms of COVID-19.

A network pharmacology study to investigate bioactive compounds and signaling pathways of garlic (Allium sativum L.) husk against type 2 diabetes mellitus

During garlic harvest, much husk has been generated, nearly all husk is discarded as unnecessary by-products. However, in Korean folk remedies, Allium sativum L. husk (ASLH) extracts have been used as a reliever against type 2 diabetes mellitus (T2DM). Currently, its significant mechanisms against T2DM remain unclear. Thus, the aim of this study is to investigate the characteristics of its key signaling pathways, targets, and compounds. The compounds in ASLH were analyzed by gas chromatography-mass spectrum (GC-MS) and confirmed drug-like compounds (DLCs) in silico. Then, protein-protein interaction (PPI) networks and signaling pathways, targets, compounds are constructed, visualized by using RStudio. Finally, we performed a molecular docking test (MDT) to identify the key mechanism(s), target(s), and compound(s) of ASLH on T2DM. A total of 23 compounds in ASLH were identified by GC-MS, and all compounds were accepted by Lipinski's rule. The 23 compounds were associated with 521 targets and retrieved 4,736 T2DM-related targets by Online Mendelian Inheritance in Man (OMIM) and DisGeNET. The final overlapping 87 targets were obtained between compounds-targets and T2DM-related targets. The number of 13 signaling pathways, 33 targets, and 19 compounds of ASLH were associated with T2DM. In parallel, MDT revealed four potential compounds: (1) 9-hexacosene, (2) 2-(([2-ethylhexyl]oxy)carbonyl)benzoic acid, (3) clionasterol, (4) 4-methyl-2-phenylpyrimidine on PPAR signaling pathway. Overall, the four compounds from ASLH might show an anti-T2DM synergistic effect by activating the PPAR signaling pathway or inactivating the phospholipase D signaling pathway. In this study, we suggest that ASLH might be considered a health-promising resource from both nutraceutical and pharmaceutical perspectives. PRACTICAL APPLICATIONS: Allium sativum L. husk (ASLH) has been regarded as wastes that come from garlic (Allium sativum L.). During the harvesting period of garlic, a considerable amount of ASLH is a severe problem in farm communities. Particularly, garlic bioactive compounds are well documented including organosulfur compounds. Conversely, at present, no information is available on chemical compounds of ASLH to use in health industries. Taking this matter into consideration, our analysis approach was to select drug-like compounds (DLCs) from ASLH via GC-MS, thereby we can explore the compounds with high cell permeability. The screened compounds can be used as nutraceutical or medicinal or even cosmetical resources. In this study, we described the significant compounds via the network pharmacology concept to uncover the pharmaceutical mechanism(s) of ASLH against T2DM. Eventually, this work provides nutraceutical or medicinal value of ASLH and suggests that ASLH might be used as an upcycling resource to relieve T2DM.

Comparison between Heat-Clearing Medicine and Antirheumatic Medicine in Treatment of Gastric Cancer Based on Network Pharmacology, Molecular Docking, and Tumor Immune Infiltration Analysis

Background

Clinical research found that TCM is therapeutic in treating gastric cancer. Clearing heat is the most common method, while some antirheumatic medicines are widely used in treatment as well. To explore the pharmacological mechanism, we researched the comparison between heat-clearing medicine and antirheumatic medicine in treating gastric cancer.

Methods

First, related ingredients and targets were searched, respectively, and are shown in an active ingredient-target network. Combining the relevant targets of gastric cancer, we constructed a PPI network and MCODE network. Then, GO and KEGG enrichment analyses were conducted. Molecular docking experiments were performed to verify the affinity of targets and ligands. Finally, we analyzed the tumor immune infiltration on gene expression, somatic CNA, and clinical outcome.

Results

A total of 31 ingredients and 90 targets of heat-clearing medicine, 31 ingredients and 186 targets of antirheumatic medicine, and 12,155 targets of gastric cancer were collected. Antirheumatic medicine ranked the top in all the enrichment analyses. In the KEGG pathway, both types of medicines were related to pathways in cancer. In the KEGG map, AR, MMP2, ERBB2, and TP53 were the most crucial targets. Key targets and ligands were docked with low binding energy. Analysis of tumor immune infiltration showed that the expressions of AR and ERBB2 were correlated with the abundance of immune infiltration and made a difference in clinical outcomes.

Conclusions

Quercetin is an important ingredient in both heat-clearing medicine and antirheumatic medicine. AR signaling pathway exists in both types of medicines. The mechanism of the antitumor effect in antirheumatic medicine was similar to trastuzumab, a targeted drug aimed at ERBB2. Both types of medicines were significant in tumor immune infiltration. The immunology of gastric tumor deserves further research.

Network Pharmacology Study on Morus alba L. Leaves: Pivotal Functions of Bioactives on RAS Signaling Pathway and Its Associated Target Proteins against Gout

M. alba L. is a valuable nutraceutical plant rich in potential bioactive compounds with promising anti-gouty arthritis. Here, we have explored bioactives, signaling pathways, and key proteins underlying the anti-gout activity of M. alba L. leaves for the first-time utilizing network pharmacology. Bioactives in M. alba L. leaves were detected through GC-MS (Gas Chromatography-Mass Spectrum) analysis and filtered by Lipinski's rule. Target proteins connected to the filtered compounds and gout were selected from public databases. The overlapping target proteins between bioactives-interacted target proteins and gout-targeted proteins were identified using a Venn diagram. Bioactives-Proteins interactive networking for gout was analyzed to identify potential ligand-target and visualized the rich factor on the R package via the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway on STRING. Finally, a molecular docking test (MDT) between bioactives and target proteins was analyzed via AutoDock Vina. Gene Set Enrichment Analysis (GSEA) demonstrated that mechanisms of M. alba L. leaves against gout were connected to 17 signaling pathways on 26 compounds. AKT1 (AKT Serine/Threonine Kinase 1), γ-Tocopherol, and RAS signaling pathway were selected as a hub target, a key bioactive, and a hub signaling pathway, respectively. Furthermore, three main compounds (γ-Tocopherol, 4-Dehydroxy-N-(4,5-methylenedioxy-2-nitrobenzylidene) tyramine, and Lanosterol acetate) and three key target proteins-AKT1, PRKCA, and PLA2G2A associated with the RAS signaling pathway were noted for their highest affinity on MDT. The identified three key bioactives in M. alba L. leaves might contribute to recovering gouty condition by inactivating the RAS signaling pathway.