A network pharmacology study on main chemical compounds from Hibiscus cannabinus L. leaves

Luteolin is a potential inhibitor of COVID-19: An in silico analysis

The severe respiratory syndrome 2019 novel coronavirus disease (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread explosively, raising global health concerns. Luteolin shows antiviral properties, but its effect on SARS-CoV-2 and the associated mechanisms are not elucidated. We used network pharmacology, molecular docking and molecular dynamics to provide potential molecular support of luteolin (3,4,5,7-tetrahydroxyflavone) (LUT) against COVID-19. We employed network pharmacology, molecular docking, and molecular dynamics techniques to investigate how LUT affected COVID-19. Several databases were queried to determine potential target proteins related to LUT and COVID-19. Protein-protein interaction network was constructed, and core targets were filtered by degree value. Following that, functional enrichment was conducted. Molecular docking was utilized to ensure LUT was compatible with core target proteins. Finally, molecular dynamics was used to analyze the effects of the LUT on the optimal hub target. A total of 64 potential target genes for treating COVID-19 were identified, of which albumin, RAC-alpha serine/threonine-protein kinase, caspase-3, epidermal growth factor receptor, heat shock protein HSP 90-alpha, and mitogen-activated protein kinase 1 might be the most promising. In addition, molecular docking results showed that LUT could interact with SARS-CoV-2 major protease 3CL. LUT can bind to the active sites of 3CL protease and mitogen-activated protein kinase 1, showing an anti-SARS-CoV-2 potential.

Target-specificity of different amyrin subunits in impeding HCV influx mechanism inside the human cells considering the quantum tunnel profiles and molecular strings of the CD81 receptor: a combined in silico and in vivo study

HCV is a hepatotropic RNA virus recognized for its frequent virulence and fatality worldwide. Despite many vaccine development programs underway, researchers are on a quest for natural bioactive compounds due to their multivalent efficiencies against viral infections, considering which the current research aimed to figure out the target-specificity and therapeutic potentiality of α, β, and δ subunits of amyrin, as novel bioactive components against the HCV influx mechanism. Initially, the novelty of amyrin subunits was conducted from 203 pharmacophores, comparing their in-silico pharmacokinetic and pharmacodynamic profiles. Besides, the best active site of CD81 was determined following the quantum tunneling algorithm. The molecular dynamic simulation was conducted (100 ns) following the molecular docking steps to reveal the parameters- RMSD (Å); Cα; RMSF (Å); MolSA (Ų); Rg (nm); PSA (Å); SASA (Ų), and the MM-GBSA dG binding scores. Besides, molecular strings of CD81, along with the co-expressed genes, were classified, as responsible for encoding CD81-mediated protein clusters during HCV infection, resulting in the potentiality of amyrins as targeted prophylactics in HCV infection. Finally, in vivo profiling of the oxidative stress marker, liver-specific enzymes, and antioxidant markers was conducted in the DMN-induced mice model, where β-amyrin scored the most significant values in all aspects.

Network pharmacology-based analysis of signaling pathways of an anti-osteoporotic triterpenoid from Acyranthes bidentata Blume root

In Korea folk remedies, Acyranthes bidentata Blume is a functional food plant to treat bone diseases; especially, its roots have been used to alleviate osteoporosis (OP), but its key chemical compound(s) and mechanism of action against osteoporosis have not reported yet. This study suggests that Acyranthes bidentata Blume root (ABBR) has promising compound(s) against OP. We utilized network pharmacology to evaluate the therapeutic value. The chemical compounds from Acyranthes bidentata Blume root (ABBR) were identified by gas chromatography-mass spectrum (GC-MS); their physicochemical properties have been evaluated by SwissADME. Next, the target(s) related to a triterpenoid or OP-related targets were investigated by public databases. The signaling pathways from final targets were visualized, constructed, and analyzed by RPackage. Finally, we performed a molecular docking (MD) to explore key target(s) and compound(s) by employing AutoDockVina tools; the residues of amino acids interacted with ligands were identified by LigPlot + v.22. A total of 24 chemicals were accepted by the Lipinski's rules. We found a sole triterpenoid from ABBR via GC-MS, suggesting that might be a potent ligand to alleviate OP. Thereby, the 42 targets were associated with the triterpenoid; the 19 targets among them were connected to OP-targets (1426). The final 19 targets were related directly to 8 signaling pathways on STRING database. On Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, and a key signaling pathway (PPAR signaling pathway), four key targets (PPARA, PPARD, FABP3, and FABP4) and a key compound (Methyl 3β-hydroxyolean-18-en-28-oate) were selected via MD. Collectively, the triterpenoid from ABBR might have potent anti-osteoporotic efficacy by activating PPARA, PPARD, FABP3, and FABP4 on PPAR signaling pathway.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-022-03362-5.

Methodology of network pharmacology for research on Chinese herbal medicine against COVID-19: A review

Traditional Chinese medicine, as a complementary and alternative medicine, has been practiced for thousands of years in China and possesses remarkable clinical efficacy. Thus, systematic analysis and examination of the mechanistic links between Chinese herbal medicine (CHM) and the complex human body can benefit contemporary understandings by carrying out qualitative and quantitative analysis. With increasing attention, the approach of network pharmacology has begun to unveil the mystery of CHM by constructing the heterogeneous network relationship of "herb-compound-target-pathway," which corresponds to the holistic mechanisms of CHM. By integrating computational techniques into network pharmacology, the efficiency and accuracy of active compound screening and target fishing have been improved at an unprecedented pace. This review dissects the core innovations to the network pharmacology approach that were developed in the years since 2015 and highlights how this tool has been applied to understanding the coronavirus disease 2019 and refining the clinical use of CHM to combat it.

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.

Microwave-Assisted Synchronous Nanogold Synthesis Reinforced by Kenaf Seed and Decoding Their Biocompatibility and Anticancer Activity

The combination of green-nanotechnology and biology may contribute to anticancer therapy. In this regard, using gold nanoparticles (GNPs) as therapeutic molecules can be a promising strategy. Herein, we proposed a novel biocompatible nanogold constructed by simply microwave-heating (MWI) Au3+ ions and kenaf seed (KS) extract within a minute. The phytoconstituents of KS extract have been utilized for safe synthesis of gold nanoparticles (KS@GNPs). The biogenic KS@GNPs were characterized by UV-vis Spectra, TEM, HR-TEM, XRD, FTIR, DLS, EDX, and SEAD techniques. The legitimacy and toxicity concern of KS@GNPs were tested against RAW 264.7 and NIH3T3 cell lines. The anticancer efficacy was verified using LN-229 cells. The pathways of KS@GNPs synthesis were optimized by varying the KS concentration (λmax 528 nm), gold salt amount (λmax 524 nm), and MWI times (λmax 522 nm). TEM displayed spherical shape and narrow size distribution (5-19.5 nm) of KS@GNPs, whereas DLS recorded Z-average size of 121.7 d·nm with a zeta potential of -33.7 mV. XRD and SAED ring patterns confirmed the high crystallinity and crystalline face centered cubic structure of gold. FTIR explored OH functional group involved in Au3+ ions reduction followed by GNPs stabilization. KS@GNPs exposure to RAW 264.7 and NIH3T3 cell lines did not induce toxicity while dose-dependent overt cell toxicity and reduced cell viability (26.6%) was observed in LN-229 cells. Moreover, the IC50 (18.79 µg/mL) treatment to cancer cell triggered cellular damages, excessive ROS generation, and apoptosis. Overall, this research exploits a sustainable method of KS@GNPs synthesis and their anticancer therapy.

Elucidating Drug-Like Compounds and Potential Mechanisms of Corn Silk (Stigma Maydis) against Obesity: A Network Pharmacology Study

Corn silk (Stigma Maydis) has been utilized as an important herb against obesity by Chinese, Korean, and Native Americans, but its phytochemicals and mechanisms(s) against obesity have not been deciphered completely. This study aimed to identify promising bioactive constituents and mechanism of action(s) of corn silk (CS) against obesity via network pharmacology. The compounds from CS were identified using Gas Chromatography Mass Spectrometry (GC-MS) and were confirmed ultimately by Lipinski's rule via SwissADME. The relationships of the compound-targets or obesity-related targets were confirmed by public bioinformatics. The signaling pathways related to obesity, protein-protein interaction (PPI), and signaling pathways-targets-bioactives (STB) were constructed, visualized, and analyzed by RPackage. Lastly, Molecular Docking Test (MDT) was performed to validate affinity between ligand(s) and protein(s) on key signaling pathway(s). We identified a total of 36 compounds from CS via GC-MS, all accepted by Lipinski's rule. The number of 36 compounds linked to 154 targets, 85 among 154 targets related directly to obesity-targets (3028 targets). Of the final 85 targets, we showed that the PPI network (79 edges, 357 edges), 12 signaling pathways on a bubble chart, and STB network (67 edges, 239 edges) are considered as therapeutic components. The MDT confirmed that two key activators (β-Amyrone, β-Stigmasterol) bound most stably to PPARA, PPARD, PPARG, FABP3, FABP4, and NR1H3 on the PPAR signaling pathway, also, three key inhibitors (Neotocopherol, Xanthosine, and β-Amyrone) bound most tightly to AKT1, IL6, FGF2, and PHLPP1 on the PI3K-Akt signaling pathway. Overall, we provided promising key signaling pathways, targets, and bioactives of CS against obesity, suggesting crucial pharmacological evidence for further clinical testing.

Network Pharmacology-Based Study to Uncover Potential Pharmacological Mechanisms of Korean Thistle (Cirsium japonicum var. maackii (Maxim.) Matsum.) Flower against Cancer

Cirsium japonicum var. maackii (Maxim.) Matsum. or Korean thistle flower is a herbal plant used to treat tumors in Korean folk remedies, but its essential bioactives and pharmacological mechanisms against cancer have remained unexplored. This study identified the main compounds(s) and mechanism(s) of the C. maackii flower against cancer via network pharmacology. The bioactives from the C. maackii flower were revealed by gas chromatography-mass spectrum (GC-MS), and SwissADME evaluated their physicochemical properties. Next, target(s) associated with the obtained bioactives or cancer-related targets were retrieved by public databases, and the Venn diagram selected the overlapping targets. The networks between overlapping targets and bioactives were visualized, constructed, and analyzed by RPackage. Finally, we implemented a molecular docking test (MDT) to explore key target(s) and compound(s) on AutoDockVina and LigPlot+. GC-MS detected a total of 34 bioactives and all were accepted by Lipinski's rules and therefore classified as drug-like compounds (DLCs). A total of 597 bioactive-related targets and 4245 cancer-related targets were identified from public databases. The final 51 overlapping targets were selected between the bioactive targets network and cancer-related targets. With Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, a total of 20 signaling pathways were manifested, and a hub signaling pathway (PI3K-Akt signaling pathway), a key target (Akt1), and a key compound (Urs-12-en-24-oic acid, 3-oxo, methyl ester) were selected among the 20 signaling pathways via MDT. Overall, Urs-12-en-24-oic acid, 3-oxo, methyl ester from the C. maackii flower has potent anti-cancer efficacy by inactivating Akt1 on the PI3K-Akt signaling pathway.

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.

A network pharmacology analysis on drug-like compounds from Ganoderma lucidum for alleviation of atherosclerosis

Ganoderma lucidum (GL) is known as a potent alleviator against chronic inflammatory disease like atherosclerosis (AS), but its mechanisms against AS have not been unveiled. This research aimed to identify the key compounds(s) and mechanism(s) of GL against AS through network pharmacology. The compounds from GL were identified by gas chromatography-mass spectrum (GC-MS), and SwissADME screened their physicochemical properties. Then, the target(s) associated with the screened compound(s) or AS related targets were identified by public databases, and we selected the overlapping targets using a Venn diagram. The networks between overlapping targets and compounds were visualized, constructed, and analyzed by RStudio. Finally, we performed a molecular docking test (MDT) to explore key target(s), compound(s), on AutoDockVina. A total of 35 compounds in GL were detected via GC-MS, and 34 compounds (accepted by Lipinski's rule) were selected as drug-like compounds (DLCs). A total of 34 compounds were connected to the number of 785 targets, and DisGeNET and Online Mendelian Inheritance in Man (OMIM) identified 2,606 AS-related targets. The final 98 overlapping targets were extracted between the compounds-targets and AS-related targets. On Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, the number of 27 signaling pathways were sorted out, and a hub signaling pathway (MAPK signaling pathway), a core gene (PRKCA), and a key compound (Benzamide, 4-acetyl-N-[2,6-dimethylphenyl]) were selected among the 27 signaling pathways via MDT. Overall, we found that the identified 3 DLCs from GL have potent anti-inflammatory efficacy, improving AS by inactivating the MAPK signaling pathway. PRACTICAL APPLICATIONS: Ganoderma lucidum (GL) has been used as a medicinal or edible mushroom for chronic inflammatory patients: diabetes mellitus and dyslipidemia, especially atherosclerosis (AS). Until now, the majority of mushroom research has been implemented regarding β-glucan derivatives with very hydrophilic physicochemical properties. It implies that β-glucan or its derivatives have poor bioavailability. Hence, we have involved GC-MS in identifying lipophilic compounds from GL, which filtered them in silico to sort drug-like compounds (DLCs). Then, we retrieved targets associated with the DLCs, and identified a key signaling pathway, key targets, and key compounds against AS. In this paper, we utilized bioinformatics and network pharmacology theory to understand the uncovered pharmacological mechanism of GL on AS. To sum things up, our analysis elucidates the relationships between signaling pathways, targets, and compounds in GL. Ultimately, this work provides biochemical evidence to identify the therapeutic effect of GL on AS, and a scientific basis for deciphering the key mechanism on DLCs of GL against AS.

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

Zanthoxylum piperitum fruits (ZPFs) have been demonstrated favorable clinical efficacy on rheumatoid arthritis (RA), but its compounds and mechanisms against RA have not been elucidated. This study was to investigate the compounds and mechanisms of ZPFs to alleviate RA via network pharmacology. The compounds from ZPFs were detected by gas chromatography-mass spectrometry (GC-MS) and screened to select drug-likeness compounds through SwissADME. Targets associated with bioactive compounds or RA were identified utilizing bioinformatics databases. The signaling pathways related to RA were constructed; interactions among targets; and signaling pathways-targets-compounds (STC) were analyzed by RPackage. Finally, a molecular docking test (MDT) was performed to validate affinity between targets and compounds on key signaling pathway(s). GC-MS detected a total of 85 compounds from ZPFs, and drug-likeness properties accepted all compounds. A total of 216 targets associated with compounds 3377 RA targets and 101 targets between them were finally identified. Then, a bubble chart exhibited that inactivation of MAPK (mitogen-activated protein kinase) and activation of PPAR (peroxisome proliferator-activated receptor) signaling pathway might be key pathways against RA. Overall, this work suggests that seven compounds from ZPFs and eight targets might be multiple targets on RA and provide integrated pharmacological evidence to support the clinical efficacy of ZPFs on RA.

Network Pharmacology Study to Interpret Signaling Pathways of Ilex cornuta Leaves against Obesity

Ilex cornuta Leaves (ICLs) are a representative and traditional prescription for controlling obesity. Nevertheless, the corresponding therapeutic compounds and related pharmacological mechanisms of such medication remain undocumented. The compounds from ICLs were identified by gas chromatography-mass spectrum (GC-MS), and SwissADME confirmed their physicochemical properties. Next, the target proteins related to compounds or obesity-associated proteins were retrieved from public databases. RPackage constructed the protein–protein interaction (PPI) network, a bubble chart, and signaling pathways–target proteins–compounds (STC) network. Lastly, a molecular docking test (MDT) was performed to evaluate the affinity between target proteins and ligands from ICLs. GC-MS detected a total of 51 compounds from ICLs. The public databases identified 219 target proteins associated with selective compounds, 3028 obesity-related target proteins, and 118 overlapping target proteins. Moreover, the STC network revealed 42 target proteins, 22 signaling pathways, and 39 compounds, which were viewed to be remedially significant. The NOD-like receptor (NLR) signaling pathway was considered a key signaling pathway from the bubble chart. In parallel, the MDT identified three target proteins (IL6, MAPK1, and CASP1) on the NLR signaling pathway and four compounds against obesity. Overall, four compounds from ICLs might show anti-obesity synergistic efficacy by inactivating the NLR signaling pathway.

Network pharmacology approach to decipher signaling pathways associated with target proteins of NSAIDs against COVID-19

Non-steroidal anti-inflammatory drugs (NSAIDs) showed promising clinical efficacy toward COVID-19 (Coronavirus disease 2019) patients as potent painkillers and anti-inflammatory agents. However, the prospective anti-COVID-19 mechanisms of NSAIDs are not evidently exposed. Therefore, we intended to decipher the most influential NSAIDs candidate(s) and its novel mechanism(s) against COVID-19 by network pharmacology. FDA (U.S. Food & Drug Administration) approved NSAIDs (19 active drugs and one prodrug) were used for this study. Target proteins related to selected NSAIDs and COVID-19 related target proteins were identified by the Similarity Ensemble Approach, Swiss Target Prediction, and PubChem databases, respectively. Venn diagram identified overlapping target proteins between NSAIDs and COVID-19 related target proteins. The interactive networking between NSAIDs and overlapping target proteins was analyzed by STRING. RStudio plotted the bubble chart of the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analysis of overlapping target proteins. Finally, the binding affinity of NSAIDs against target proteins was determined through molecular docking test (MDT). Geneset enrichment analysis exhibited 26 signaling pathways against COVID-19. Inhibition of proinflammatory stimuli of tissues and/or cells by inactivating the RAS signaling pathway was identified as the key anti-COVID-19 mechanism of NSAIDs. Besides, MAPK8, MAPK10, and BAD target proteins were explored as the associated target proteins of the RAS. Among twenty NSAIDs, 6MNA, Rofecoxib, and Indomethacin revealed promising binding affinity with the highest docking score against three identified target proteins, respectively. Overall, our proposed three NSAIDs (6MNA, Rofecoxib, and Indomethacin) might block the RAS by inactivating its associated target proteins, thus may alleviate excessive inflammation induced by SARS-CoV-2.