On the mechanism of wogonin against acute monocytic leukemia using network pharmacology and experimental validation

Wogonin is a natural flavone compound from the plant Scutellaria baicalensis, which has a variety of pharmacological activities such as anti-cancer, anti-virus, anti-inflammatory, and immune regulation. However, the potential mechanism of wogonin remains unknown. This study was to confirm the molecular mechanism of wogonin for acute monocytic leukemia treatment, known as AML-M5. The potential action targets between wogonin and acute monocytic leukemia were predicted from databases. The compound-target-pathway network and protein-protein interaction network (PPI) were constructed. The enrichment analysis of related targets and molecular docking were performed. The network pharmacological results of wogonin for AML-M5 treatment were verified using the THP-1 cell line. 71 target genes of wogonin associated with AML-M5 were found. The key genes TP53, SRC, AKT1, RELA, HSP90AA1, JUN, PIK3R1, and CCND1 were preliminarily found to be the potential central targets of wogonin for AML-M5 treatment. The PPI network analysis, GO analysis and KEGG pathway enrichment analysis demonstrated that the PI3K/AKT signaling pathway was the significant pathway in the wogonin for AML-M5 treatment. The antiproliferative effects of wogonin on THP-1 cells of AML-M5 presented a dose-dependent and time-dependent manner, inducing apoptosis, blocking the cell cycle at the G2/M phase, decreasing the expressions of CCND1, CDK2, and CyclinA2 mRNA, as well as AKT and p-AKT proteins. The mechanisms of wogonin on AML-M5 treatment may be associated with inhibiting cell proliferation and regulating the cell cycle via the PI3K/AKT signaling pathway.

Multi-level bioinformatics resources support drug target discovery of protein-protein interactions

Drug discovery often begins with a new target. Protein-protein interactions (PPIs) are crucial to multitudinous cellular processes and offer a promising avenue for drug-target discovery. PPIs are characterized by multi-level complexity: at the protein level, interaction networks can be used to identify potential targets, whereas at the residue level, the details of the interactions of individual PPIs can be used to examine a target's druggability. Much great progress has been made in target discovery through multi-level PPI-related computational approaches, but these resources have not been fully discussed. Here, we systematically survey bioinformatics tools for identifying and assessing potential drug targets, examining their characteristics, limitations and applications. This work will aid the integration of the broader protein-to-network context with the analysis of detailed binding mechanisms to support the discovery of drug targets.

Molecular modelling, docking and network analysis of phytochemicals from Haritaki churna: role of protein cross-talks for their action

Phytochemicals are bioactive agents present in medicinal plants with therapeutic values. Phytochemicals isolated from plants target multiple cellular processes. In the current work, we have used fractionation techniques to identify 13 bioactive polyphenols in ayurvedic medicine Haritaki Churna. Employing the advanced spectroscopic and fractionation, structure of bioactive polyphenols was determined. Blasting the phytochemical structure allow us to identify a total of 469 protein targets from Drug bank and Binding DB. Phytochemicals with their protein targets from Drug bank was used to create a phytochemical-protein network comprising of 394 nodes and 1023 edges. It highlights the extensive cross-talk between protein target corresponding to different phytochemicals. Analysis of protein targets from Binding data bank gives a network comprised of 143 nodes and 275 edges. Taking the data together from Drug bank and binding data, seven most prominent drug targets (HSP90AA1, c-Src kinase, EGFR, Akt1, EGFR, AR, and ESR-α) were found to be target of the phytochemicals. Molecular modelling and docking experiment indicate that phytochemicals are fitting nicely into active site of the target proteins. The binding energy of the phytochemicals were better than the inhibitors of these protein targets. The strength and stability of the protein ligand complexes were further confirmed using molecular dynamic simulation studies. Further, the ADMET profiles of phytochemicals extracted from HCAE suggests that they can be potential drug targets. The phytochemical cross-talk was further proven by choosing c-Src as a model. HCAE down regulated c-Src and its downstream protein targets such as Akt1, cyclin D1 and vimentin. Hence, network analysis followed by molecular docking, molecular dynamics simulation and in-vitro studies clearly highlight the role of protein network and subsequent selection of drug candidate based on network pharmacology.Communicated by Ramaswamy H. Sarma.

Rheum palmatum L. and Salvia miltiorrhiza Bge. Alleviates Acute Pancreatitis by Regulating Th17 Cell Differentiation: An Integrated Network Pharmacology Analysis, Molecular Dynamics Simulation and Experimental Validation

OBJECTIVE

To identify the core targets of Rheum palmatum L. and Salvia miltiorrhiza Bge., (Dahuang-Danshen, DH-DS) and the mechanism underlying its therapeutic efficacy in acute pancreatitis (AP) using a network pharmacology approach and validate the findings in animal experiments.

METHODS

Network pharmacology analysis was used to elucidate the mechanisms underlying the therapeutic effects of DH-DS in AP. The reliability of the results was verified by molecular docking simulation and molecular dynamics simulation. Finally, the results of network pharmacology enrichment analysis were verified by immunohistochemistry, Western blot analysis and real-time quantitative PCR, respectively.

RESULTS

Sixty-seven common targets of DH-DS in AP were identified and mitogen-activated protein kinase 3 (MAPK3), Janus kinase 2 (JAK2), signal transducer and activator of transcription 3 (STAT3), protein c-Fos (FOS) were identified as core targets in the protein interaction (PPI) network analysis. Gene ontology analysis showed that cellular response to organic substance was the main functions of DH-DS in AP, and Kyoto Encyclopedia of Genes and Genomes analysis showed that the main pathway included Th17 cell differentiation. Molecular docking simulation confirmed that DH-DS binds with strong affinity to MAPK3, STAT3 and FOS. Molecular dynamics simulation revealed that FOS-isotanshinone II and STAT3-dan-shexinkum d had good binding capacity. Animal experiments indicated that compared with the AP model group, DH-DS treatment effectively alleviated AP by inhibiting the expression of interleukin-1β, interleukin-6 and tumor necrosis factor-α, and blocking the activation of Th17 cell differentiation (P<0.01).

CONCLUSION

DH-DS could inhibit the expression of inflammatory factors and protect pancreatic tissues, which would be functioned by regulating Th17 cell differentiation-related mRNA and protein expressions.

Identification of Genes Hub Associated with Triple-Negative Breast Cancer and Cannabidiol Analogs Potential Inhibitory Agents: An In-silico Study

OBJECTIVE

Triple-negative breast cancer presents a significant challenge in oncology due to its complex treatment and aggressive nature. This subtype lacks common cancer cell receptors like estrogen, progesterone, and human epidermal growth factor receptor 2 receptors. This study aimed to identify, through bioinformatic analysis, the key genes associated with triple-negative breast cancer. In addition, CBD analogs with potential inhibitory effects on these genes were evaluated through docking and molecular dynamics.

METHODS

Gene expression profiles from the GSE178748 dataset were analyzed, focusing on MDA-MB-231 breast cancer cell lines. Differentially expressed genes were determined through protein-protein interaction networks and subsequently validated. Additionally, the inhibitory effects of cannabidiol analogs on these hub genes were assessed using molecular docking and dynamics.

RESULTS

 Analysis of the hub highlighted RPL7A, NHP2L1, and PSMD11 as significant players in TNBC regulation. Ligand 44409296 showed the best affinity energy with RPL7A, while 166505341 exhibited the highest affinity with NHP2L1 and PSMD11, surpassing CBD. Analyses of RMSD, RMSF, SASA, and Gyration Radius indicated structural stability and interactions of the proteins with ligands over time. MMGBSA calculations showed favorable binding energies for the ligands with the target proteins.

CONCLUSION

In conclusion, this study identified key genes, namely RPL7A, NHP2L1, and PSMD11, associated with triple-negative breast cancer and demonstrated promising interactions with cannabidiol analogs, particularly 44409296 and 166505341. These findings suggest potential therapeutic targets and highlight the relevance of further clinical investigations. Additionally, the ligands exhibited favorable ADME properties and low toxicity, underscoring their potential in future drug development for TNBC treatment.

SRC family kinase inhibition rescues molecular and behavioral phenotypes, but not protein interaction network dynamics, in a mouse model of Fragile X syndrome

Glutamatergic synapses encode information from extracellular inputs using dynamic protein interaction networks (PINs) that undergo widespread reorganization following synaptic activity, allowing cells to distinguish between signaling inputs and generate coordinated cellular responses. Here, we investigate how Fragile X Messenger Ribonucleoprotein (FMRP) deficiency disrupts signal transduction through a glutamatergic synapse PIN downstream of NMDA receptor or metabotropic glutamate receptor (mGluR) stimulation. In cultured cortical neurons or acute cortical slices from P7, P17 and P60 FMR1-/y mice, the unstimulated protein interaction network state resembled that of wildtype littermates stimulated with mGluR agonists, demonstrating resting state pre-activation of mGluR signaling networks. In contrast, interactions downstream of NMDAR stimulation were similar to WT. We identified the Src family kinase (SFK) Fyn as a network hub, because many interactions involving Fyn were pre-activated in FMR1-/y animals. We tested whether targeting SFKs in FMR1-/y mice could modify disease phenotypes, and found that Saracatinib (SCB), an SFK inhibitor, normalized elevated basal protein synthesis, novel object recognition memory and social behavior in FMR1-/y mice. However, SCB treatment did not normalize the PIN to a wild-type-like state in vitro or in vivo, but rather induced extensive changes to protein complexes containing Shank3, NMDARs and Fyn. We conclude that targeting abnormal nodes of a PIN can identify potential disease-modifying drugs, but behavioral rescue does not correlate with PIN normalization.

In silico and network pharmacology analysis of fucosterol: a potent anticancer bioactive compound against HCC

The Fucaceae family of marine brown algae includes Ascophyllum nodosum. Fucosterol (FSL) is a unique bioactive component that was identified through GC-MS analysis of the hydroalcoholic extract of A. nodosum. Fucosterol's mechanism of action towards hepatocellular cancer was clarified using network pharmacology and docking study techniques. The probable target gene of FSL has been predicted using the TargetNet and SwissTargetPred databases. GeneCards and the DisGNet database were used to check the targeted genes of FSL. By using the web programme Venny 2.1, the overlaps of FSL and HCC disease demonstrated that 18 genes (1.3%) were obtained as targeted genes Via the STRING database, a protein-protein interaction (PPI) network with 18 common target genes was constructed. With the aid of CytoNCA, hub genes were screened using the Cytoscape software, and the targets' hub genes were exported into the ShinyGo online tool for study of KEGG and gene ontology enrichment. Using the software AutoDock, a hub gene molecular docking study was performed. Ten genes, including AR, CYP19A1, ESR1, ESR2, TNF, PPARA, PPARG, HMGCR, SRC, and IGF1R, were obtained. The 10 targeted hubs docked with FSL successfully. The active components FSL of ASD, the FSL, are engaged in fatty liver disease, cancer pathways, and other signalling pathways, which could prove beneficial for the management of HCC.

Mechanistic insights into targeting caspase-3 activation and alveolar macrophage pyroptosis by Ephedra and bitter almond compounds for treating pediatric pneumonia via network pharmacology and bioinformatics

This study investigates the molecular mechanism of Ma Huang-Ku Xing Ren, a traditional Chinese medicine formula, in treating pediatric pneumonia. The focus is on the regulation of caspase-3 activation and reduction of alveolar macrophage necrosis through network pharmacology and bioinformatics analyses of Ephedra and bitter almond components. Active compounds and targets from ephedrine and bitter almond were obtained using TCMSP, TCMID, and GeneCards databases, identifying pediatric pneumonia-related genes. A protein-protein interaction (PPI) network was constructed, and core targets were screened. GO and KEGG pathway enrichment analyses identified relevant genes and pathways. An acute pneumonia mouse model was created using the lipopolysaccharide (LPS) inhalation method, with caspase-3 overexpression induced by a lentivirus. The mice were treated with Ephedra and bitter almond through gastric lavage. Lung tissue damage, inflammatory markers (IL-18 and IL-1β), and cell death-related gene activation were assessed through H&E staining, ELISA, western blot, flow cytometry, and immunofluorescence. The study identified 128 active compounds and 121 gene targets from Ephedra and bitter almond. The PPI network revealed 13 core proteins, and pathway analysis indicated involvement in inflammation, apoptosis, and cell necrosis, particularly the caspase-3 pathway. In vivo results showed that Ephedra and bitter almond treatment significantly mitigated LPS-induced lung injury in mice, reducing lung injury scores and inflammatory marker levels. It also decreased caspase-3 activity and cell death in alveolar macrophages. In conclusion, the active ingredients of Ma Huang-Ku Xing Ren, particularly targeting caspase-3, may effectively treat pediatric pneumonia by reducing apoptosis in alveolar macrophages, as demonstrated by both network pharmacology, bioinformatics analyses, and experimental data.

Unravelling the anti-inflammatory mechanism of Allium cepa: an integration of network pharmacology and molecular docking approaches

Allium cepa, commonly known as onion, is a widely consumed spice that possesses numerous pharmacological properties. A. cepa bioactive components are often explored in the treatment of inflammation-related complications. However, the molecular mechanism via which they exert their anti-inflammatory effects remains unknown. Therefore, this study aimed to elucidate the anti-inflammatory mechanism of A. cepa bioactive components. Consequently, the bioactive compounds of A. cepa were obtained from a database, while the potential targets of the sixty-nine compounds with desirable pharmacokinetic properties were predicted. Subsequently, the targets of inflammation were acquired from the GeneCards database. The protein-protein interaction (PPI) between the sixty-six shared targets of the bioactive compounds and inflammation was retrieved from the String database and visualized using Cytoscape v3.9.1 software. Gene Ontology (GO) analysis of the ten core targets from the PPI network revealed that A. cepa bioactive compounds could be involved in regulating biological processes such as response to oxygen-containing compounds and response to inflammation while Kyoto Encyclopaedia of Genes and Genomes (KEGG) analysis revealed that A. cepa compounds might modulate pathways including AGE-RAGE signaling pathway, interleukin (IL)-17 signalling pathway, and tumor necrosis factor signaling pathway. Molecular docking analysis showed that 1-O-(4-Coumaroyl)-beta-D-glucose, stigmasterol, campesterol, and diosgenin have high binding affinities for core targets including EGFR, ALB, MMP9, CASP3, and CCL5. This study successfully elucidated the potential anti-inflammatory mechanism of A. cepa bioactive compounds, hence, providing new insights into the development of alternative anti-inflammatory drugs.

Network Pharmacology Prediction and Molecular Docking-Based Strategy to Explore the Potential Mechanism of Gualou Xiebai Banxia Decoction against Myocardial Infarction

The aim of this study was to investigate targets through which Gualou Xiebai Banxia decoction aids in treating myocardial infarction (MI) using network pharmacology in combination with molecular docking. The principal active ingredients of Gualou Xiebai Banxia decoction were identified from the TCMSP database using the criteria of drug-likeness ≥30% and oral bioavailability ≥0.18. Interactions and pathway enrichment were investigated using protein-protein interaction (PPI) networks and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, respectively. Active component structures were docked with those of potential protein targets using AutoDock molecular docking relative softwares. HIF1A was of particular interest as it was identified by the PPI network, GO and KEGG pathway enrichment analyses. In conclusion, the use of network pharmacology prediction and molecular docking assessments provides further information on the active components and mechanisms of action Gualou Xiebai Banxia decoction.

Network Pharmacology and Experimental Validation Explore the Pharmacological Mechanisms of Herb Pair for Treating Rheumatoid Arthritis

OBJECTIVE

This study aimed to elucidate the multitarget mechanism of the Mori Ramulus - Taxilli Herba (MT) herb pair in treating rheumatoid arthritis (RA).

METHODS

The targets of the herb pair and RA were predicted from databases and screened through cross-analysis. The core targets were obtained using protein-protein interaction (PPI) network analysis. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed. Finally, animal experiments were conducted to validate the anti-RA effect and mechanism of this herb pair.

RESULTS

This approach successfully identified 9 active compounds of MT that interacted with 6 core targets (AKT1, TNF, IL6, TP53, VEGFA, and IL1β). Pathway and functional enrichment analyses revealed that MT had significant effects on the TNF and IL-17 signaling pathways. The consistency of interactions between active components and targets in these pathways was confirmed through molecular docking. Moreover, the potential therapeutic effect of MT was verified in vivo, demonstrating its ability to effectively relieve inflammation by regulating these targeted genes and pathways.

CONCLUSION

The present work suggests that the therapeutic effect of MT herb pair on RA may be attributed to its ability to regulate the TNF signaling pathway and IL-17 signaling pathway.

Exploration of the Potential Mechanism of Yujin Powder Treating Dampness-heat Diarrhea by Integrating UPLC-MS/MS and Network Pharmacology Prediction

BACKGROUND

Yujin powder (YJP) is a classic prescription for treating dampness-heat diarrhea (DHD) in Traditional Chinese Medicine (TCM), but the main functional active ingredients and the exact mechanisms have not been systematically studied.

OBJECTIVES

This study aimed to preliminarily explore the potential mechanisms of YJP for treating DHD by integrating UPLC-MS/MS and network pharmacology methods.

METHODS

Ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) technology was used to determine the ingredients of YJP. And then, the targets of these components were predicted and screened from TCMSP, SwissTargetPrediction databases. The disease targets related to DHD were obtained by using the databases of GeneCards, OMIM, DisGeNET, TTD, and DrugBank. The protein-protein interaction networks (PPI) of YJP-DHD were constructed using the STRING database and Origin 2022 software to identify the cross-targets by screening the core-acting targets and a network diagram by Cytoscape 3.8.2 software was also constructed. Metascape database was used for performing GO and KEGG enrichment anlysis on the core genes. Finally, molecular docking was used to verify the results with AutoDock 4.2.6, AutoDock Tools 1.5.6, PyMOL 2.4.0, and Open Babel 2.3.2 software.

RESULTS

597 components in YJP were detected, and 153 active components were obtained through database screening, among them the key active ingredients include coptisine, berberine, baicalein, etc. There were 362 targets treating DHD, among them the core targets included TNF, IL-6, ALB, etc. The enriched KEGG pathways mainly involve PI3K-Akt, TNF, MAPK, etc. Molecular docking results showed that coptisine, berberine, baicalein, etc., had a strong affinity with TNF, IL-6, and MAPK14. Therefore, TNF, IL-6, MAPK14, ALB, etc., are the key targets of the active ingredients of YJP coptisine, baicalein, and berberine, etc. They have the potential to regulate PI3K-Akt, MAPK, and TNF signalling pathways. The component-target-disease network diagram revealed that YJP treated DHD through the effects of anti-inflammation, anti-diarrhea, immunoregulation, and improving intestinal mucosal injury.

CONCLUSION

It is demonstrated that YJP treats DHD mainly through the main active ingredients coptisine, berberine, baicalein, etc. comprehensively exerting the effects of anti-inflammation, anti-diarrhea, immunoregulation, and improving intestinal mucosal injury, which will provide evidence for further in-depth studying the mechanism of YJP treating DHD.

Comprehensive Genomic Analysis of Puerarin in Inhibiting Bladder Urothelial Carcinoma Cell Proliferation and Migration

BACKGROUND

Bladder urothelial carcinoma (BUC) ranks second in the incidence of urogenital system tumors, and the treatment of BUC needs to be improved. Puerarin, a traditional Chinese medicine (TCM), has been shown to have various effects such as anti-cancer effects, the promotion of angiogenesis, and anti-inflammation. This study investigates the effects of puerarin on BUC and its molecular mechanisms.

METHODS

Through GeneChip experiments, we obtained differentially expressed genes (DEGs) and analyzed these DEGs using the Ingenuity® Pathway Analysis (IPA®), Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) pathway enrichment analyses. The Cell Counting Kit 8 (CCK8) assay was used to verify the inhibitory effect of puerarin on the proliferation of BUC T24 cells. String combined with Cytoscape® was used to create the Protein-Protein Interaction (PPI) network, and the MCC algorithm in cytoHubba plugin was used to screen key genes. Gene Set Enrichment Analysis (GSEA®) was used to verify the correlation between key genes and cell proliferation.

RESULTS

A total of 1617 DEGs were obtained by GeneChip. Based on the DEGs, the IPA® and pathway enrichment analysis showed they were mainly enriched in cancer cell proliferation and migration. CCK8 experiments proved that puerarin inhibited the proliferation of BUC T24 cells, and its IC50 at 48 hours was 218μmol/L. Through PPI and related algorithms, 7 key genes were obtained: ITGA1, LAMA3, LAMB3, LAMA4, PAK2, DMD, and UTRN. GSEA showed that these key genes were highly correlated with BUC cell proliferation. Survival curves showed that ITGA1 upregulation was associated with poor prognosis of BUC patients.

CONCLUSION

Our findings support the potential antitumor activity of puerarin in BUC. To the best of our knowledge, bioinformatics investigation suggests that puerarin demonstrates anticancer mechanisms via the upregulation of ITGA1, LAMA3 and 4, LAMB3, PAK2, DMD, and UTRN, all of which are involved in the proliferation and migration of bladder urothelial cancer cells.

Network Pharmacology Study on Herb Pair Bletilla striata-Galla chinensis in the Treatment of Chronic Skin Ulcers

BACKGROUND

Herb pair Bletilla striata-Galla chinensis (BS-GC) is a classic combination of topical traditional Chinese medicine formulae in the treatment of chronic skin ulcers (CSUs).

OBJECTIVE

The aim of this study is to explore the effective active ingredients of BS-GC, as well as the core targets and signal transduction pathways of its action on CSUs.

METHODS

The ingredients of BS-GC were obtained from TCMSP and HERB databases. The targets of all active ingredients were retrieved from the SwissTargetPrediction database. The targets of CSUs were obtained from OMIM, GeneCards, Drugbank, and DisGeNET databases. A drug-disease target protein-protein interaction (PPI) network was constructed to select the most core targets, and an herb-ingredient-target network was built by utilizing Cytoscape 3.7.2. Furthermore, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes database (KEGG) analysis and verified the results of network pharmacology through molecular docking.

RESULTS

A total of 40 active ingredients from the herb pair BS-GC were initially screened, and a total of 528 targets were retrieved. Meanwhile, the total number of CSU targets was 1032. Then, the number of common targets between BS-GC and CSUs was 107. The 13 core targets of herb pair BS-GC with CSUs were filtered out according to the PPI network, including AKT1, TNF, EGFR, BCL2, HIF1A, MMP-9, etc. The 5 main core active ingredients were 1-(4-Hydroxybenzyl)-2-methoxy-9,10-dihydrophenanthrene-4,7-diol, 1-(4- Hydroxybenzyl)-4-methoxy-9,10-dihydrophenanthrene-2,7-diol, physcion, dihydromyricetin, and myricetin. The main biological processes were inflammation, oxidative stress, and immune response, involving the AGE-RAGE signaling pathway in diabetic complications, HIF-1 signaling pathway, NF-κB signaling pathway, and calcium signaling pathway. Molecular docking results showed good binding activity between the 5 main core active ingredients and 13 core targets.

CONCLUSION

This study predicted the core targets and signal transduction pathways in the treatment of CSUs to provide a reference for further molecular mechanism research.

Searching for Essential Genes and Targeted Drugs Common to Breast Cancer and Osteoarthritis

BACKGROUND

It is documented that osteoarthritis can promote the progression of breast cancer (BC).

OBJECTIVE

This study aims to search for the essential genes associated with breast cancer (BC) and osteoarthritis (OA), explore the relationship between epithelial-mesenchymal transition (EMT)- related genes and the two diseases, and identify the candidate drugs.

METHODS

The genes related to both BC and OA were determined by text mining. Protein-protein Interaction (PPI) analysis was carried out, and as a result, the exported genes were found to be related to EMT. PPI and the correlation of mRNA of these genes were also analyzed. Different kinds of enrichment analyses were performed on these genes. A prognostic analysis was performed on these genes for examining their expression levels at different pathological stages, in different tissues, and in different immune cells. Drug-gene interaction database was employed for potential drug discovery.

RESULTS

A total number of 1422 genes were identified as common to BC and OA and 58 genes were found to be related to EMT. We found that HDAC2 and TGFBR1 were significantly poor in overall survival. High expression of HDAC2 plays a vital role in the increase of pathological stages. Four immune cells might play a role in this process. Fifty-seven drugs were identified that could potentially have therapeutic effects.

CONCLUSION

EMT may be one of the mechanisms by which OA affects BC. Using the drugs can have potential therapeutic effects, which may benefit patients with both diseases and broaden the indications for drug use.

Exploring the Potential Molecular Mechanism of the Shugan Jieyu Capsule in the Treatment of Depression through Network Pharmacology, Molecular Docking, and Molecular Dynamics Simulation

BACKGROUND

Shugan Jieyu Capsule (SJC) is a pure Chinese medicine compound prepared with Hypericum perforatum and Acanthopanacis senticosi. SJC has been approved for the clinical treatment of depression, but the mechanism of action is still unclear.

OBJECTIVES

Network pharmacology, molecular docking, and molecular dynamics simulation (MDS) were applied in the present study to explore the potential mechanism of SJC in the treatment of depression.

METHODS

TCMSP, BATMAN-TCM, and HERB databases were used, and related literature was reviewed to screen the effective active ingredients of Hypericum perforatum and Acanthopanacis senticosi. TCMSP, BATMAN-TCM, HERB, and STITCH databases were used to predict the potential targets of effective active ingredients. GeneCards database, DisGeNET database, and GEO data set were used to obtain depression targets and clarify the intersection targets of SJC and depression. STRING database and Cytoscape software were used to build a protein-protein interaction (PPI) network of intersection targets and screen the core targets. The enrichment analysis on the intersection targets was conducted. Then the receiver operator characteristic (ROC) curve was constructed to verify the core targets. The pharmacokinetic characteristics of core active ingredients were predicted by SwissADME and pkCSM. Molecular docking was performed to verify the docking activity of the core active ingredients and core targets, and molecular dynamics simulations were performed to evaluate the accuracy of the docking complex.

RESULTS

We obtained 15 active ingredients and 308 potential drug targets with quercetin, kaempferol, luteolin, and hyperforin as the core active ingredients. We obtained 3598 targets of depression and 193 intersection targets of SJC and depression. A total of 9 core targets (AKT1, TNF, IL6, IL1B, VEGFA, JUN, CASP3, MAPK3, PTGS2) were screened with Cytoscape 3.8.2 software. A total of 442 GO entries and 165 KEGG pathways (p <0.01) were obtained from the enrichment analysis of the intersection targets, mainly enriched in IL-17, TNF, and MAPK signaling pathways. The pharmacokinetic characteristics of the 4 core active ingredients indicated that they could play a role in SJC antidepressants with fewer side effects. Molecular docking showed that the 4 core active components could effectively bind to the 8 core targets (AKT1, TNF, IL6, IL1B, VEGFA, JUN, CASP3, MAPK3, PTGS2), which were related to depression by the ROC curve. MDS showed that the docking complex was stable.

CONCLUSION

SJC may treat depression by using active ingredients such as quercetin, kaempferol, luteolin, and hyperforin to regulate targets such as PTGS2 and CASP3 and signaling pathways such as IL-17, TNF, and MAPK, and participate in immune inflammation, oxidative stress, apoptosis, neurogenesis, etc.

A Network Pharmacology-based Study on the Anti-aging Properties of Traditional Chinese Medicine Sisheng Bulao Elixir

BACKGROUND

Traditional Chinese Medicine (TCM) has a rich history of use in preventing senescence for millennia in China. Nonetheless, a systematic method to study the antiaging properties and the underlying molecular mechanism of TCM remains absent.

OBJECTIVE

The objective of this study is to decipher the anti-aging targets and mechanisms of Sisheng Bulao Elixir (SBE) using a systematic approach based on a novel aging database and network pharmacology.

METHODS

Bioactive compounds and target proteins in SBE were identified via the Traditional Chinese Medicine System Pharmacology (TCMSP) database. Aging-related proteins were uncovered through alignment with the Ageing Alta database. A compound-target (CT) protein network analysis highlighted key flavonoids targeting aging. Core aging-related proteins were extracted through protein-protein interaction (PPI) network analysis. Molecular docking validated binding activities between core compounds and aging-related proteins. The antioxidant activity of SBE was confirmed using an in vitro senescent cells model.

RESULTS

A total of 39 active compounds were extracted from a pool of 639 compounds in SBE. Through a matching process with the Aging Alta, 88 target proteins associated with the aging process were identified. Impressively, 80 out of these 88 proteins were found to be targeted by flavonoids. Subsequently, an analysis using CT methodology highlighted 11 top bioactive flavonoids. Notably, core aging-related proteins, including AKT1, MAPK3, TP53, VEGFA, IL6, and HSP90AA1, emerged through the PPI network analysis. Moreover, three flavonoids, namely quercetin, kaempferol, and luteolin, exhibited interactions with over 100 aging-related proteins. Molecular docking studies were conducted on these flavonoids with their shared three target proteins, namely AKT1, HSP90AA1, and IL6, to assess their binding activities. Finally, the antioxidant properties of SBE were validated using an in vitro model of senescent cells.

CONCLUSION

This study offers novel insights into SBE's anti-aging attributes, providing evidence of its molecular mechanisms. It enhances our understanding of traditional remedies in anti-aging research.

Evaluation of Therapeutic Mechanism of Hedyotis Diffusa Willd (HDW)‒ Scutellaria Barbata (SB) in Clear Cell Renal Cell Carcinoma via Singlecell RNA Sequencing and Network Pharmacology

OBJECTIVE

The present study aimed to investigate the therapeutic mechanism of Hedyotis diffusa Willd (HDW) and Scutellaria barbata (SB) in ccRCC using a combination of single-cell RNA sequencing (scRNA-seq) and network pharmacology.

METHODS

The active ingredients and potential molecular targets of HDW-SB were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform. Gene expression data (GSE53757) were obtained from the Gene Expression Omnibus database. The hub genes of HDW-SB against ccRCC were identified via the protein-protein interaction network, and further analyzed by molecular complex detection. The roles of these genes in the diagnosis and immune infiltration of ccRCC were analyzed. The clinical significance of hub genes was verified using scRNA-seq data (GSE121638) and molecular docking.

RESULTS

Following the PPI network analysis, 29 hub genes of HDW-SB against ccRCC were identified. All hub genes, except for CENPE, had significantly different expressions in tumor tissue and a more accurate diagnosis of ccRCC. Fifteen cell clusters were defined based on the scRNA-seq dataset, and the clusters were annotated as six cell types using marker genes. TYMS and KIAA0101 from hub genes were highly expressed in NK cells. Three active compounds, quercetin, luteolin, and baicalein, were found to target TYMS and KIAA0101 from the compound-target interaction network.

CONCLUSION

29 hub genes of HDW-SB against ccRCC were identified and showed good performance in terms of diagnosis and prognosis. Moreover, among these hub genes docking with the main ingredients of HDW-SB, TYMS and KIAA0101 exerted anti-ccRCC effects through NK cells.

Molecular Targets and Mechanisms of Hedyotis diffusa Willd. for Esophageal Adenocarcinoma Treatment Based on Network Pharmacology and Weighted Gene Co-expression Network Analysis

BACKGROUND

Hedyotis diffusa Willd. (HDW) is a common anticancer herbal medicine in China, and its therapeutic effectiveness has been demonstrated in a range of cancer patients. There is no consensus about the therapeutic targets and molecular mechanisms of HDW, which contains many active ingredients.

AIM

To clarify the mechanism of HDW for esophageal adenocarcinoma (EAC), we utilized network pharmacology and weighted gene co-expression network analysis methods (WGCNA).

METHODS

The gene modules that were linked with the clinical features of EAC were obtained through the WGCNA method. Then, the potential target genes were retrieved through the network pharmacology method in order to determine the targets of the active components. After enrichment analysis, a variety of signaling pathways with significant ratios of target genes were found, including regulation of trans-synaptic signaling, neuroactive ligand-receptor interaction and modulation of chemical synaptic transmission. By means of protein-protein interaction (PPI) network analysis, we have successfully identified the hub genes, which were AR, CNR1, GRIK1, MAPK10, MAPT, PGR and PIK3R1.

RESULT

Our study employed molecular docking simulations to evaluate the binding affinity of the active components with the hub gene. The identified active anticancer constituents in HDW are scopoletol, quercetin, ferulic acid, coumarin, and trans-4-methoxycinnamyl alcohol.

CONCLUSION

Our findings shed light on the molecular underpinnings of HDW in the treatment of EAC and hold great promise for the identification of potential HDW compounds and biomarkers for EAC therapy.

Network Pharmacology and Experimental Validation of Qingwen Baidu Decoction Therapeutic Potential in COVID-19-related Lung Injury

BACKGROUND AND PURPOSE

Coronavirus disease 2019 (COVID-19) is a lifethreatening disease worldwide due to its high infection and serious outcomes resulting from acute lung injury. Qingwen Baidu decoction (QBD), a well-known herbal prescription, has shown significant efficacy in patients with Coronavirus disease 2019. Hence, this study aims to uncover the molecular mechanism of QBD in treating COVID-19-related lung injury.

METHODS

Traditional Chinese Medicine Systems Pharmacology database (TCMSP), DrugBanks database, and Chinese Knowledge Infrastructure Project (CNKI) were used to retrieve the active ingredients of QBD. Drug and disease targets were collected using UniProt and Online Mendelian Inheritance in Man databases (OMIM). The core targets of QBD for pneumonia were analyzed by the Protein-Protein Interaction Network (PPI), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) to reveal the underlying molecular mechanisms. The analysis of key targets using molecular docking and animal experiments was also validated.

RESULTS

A compound-direct-acting target network mainly containing 171 compounds and 110 corresponding direct targets was constructed. The key targets included STAT3, c-JUN, TNF-α, MAPK3, MAPK1, FOS, PPARG, MAPK8, IFNG, NFκB1, etc. Moreover, 117 signaling pathways mainly involved in cytokine storm, inflammatory response, immune stress, oxidative stress and glucose metabolism were found by KEGG. The molecular docking results showed that the quercetin, alanine, and kaempferol in QBD demonstrated the strongest affinity to STAT3, c- JUN, and TNF-α. Experimental results displayed that QBD could effectively reduce the pathological damage to lung tissue by LPS and significantly alleviate the expression levels of the three key targets, thus playing a potential therapeutic role in COVID-19.

CONCLUSION

QBD might be a promising therapeutic agent for COVID-19 via ameliorating STAT3-related signals.

Effect and Mechanisms of Huangqi-Shanzhuyu in the Treatment of Diabetic Nephropathy based on Network Pharmacology and In Vitro Experiments

BACKGROUND

Huangqi-Shanzhuyu (HS), a classic combination of Chinese herbal formulae, has been widely used for the treatment of diabetic nephropathy (DN). However, its pharmacological mechanism of action is still unclear.

METHODS

The active ingredients of HS and their potential targets were identified through the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and the DN-related targets were determined from GeneCards, Online Mendelian Inheritance in Man (OMIM), PharmGkb, and Therapeutic Target Database (TTD). The Cytoscape software was used to construct a herb-disease-target network and screen core genes. STRING was employed to generate a protein-protein interaction (PPI) network. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to predict the mechanism of action of HS in DN. Animal experiments and molecular docking were used to verify the potential mechanism.

RESULTS

In total, 40 active ingredients and 180 effective targets of HS in DN were identified and 1115 DN-related targets were retrieved. From the PPI network, VEGFA, AKT1, IL6, IL1B, TP53, MMP9, PTGS2, CASP3, EGF and EGFR were identified as core genes. The anti-DN mechanism mainly involved multiple signaling pathways such as AGEs-RAGE. Animal experiments and molecular docking analysis confirmed that HS downregulated the expression of IL-1 and IL-6 via kaempferol-mediated inhibition of JNK1 phosphorylation.

CONCLUSION

HS exhibits a therapeutic effect in DN through its multiple ingredients that act on several targets and multiple signaling pathways, including AGEs-RAGE.

Exploring the Potential Mechanisms of Action of Gentiana Veitchiorum Hemsl. Extract in the Treatment of Cholestasis using UPLC-MS/MS, Systematic Network Pharmacology, and Molecular Docking

INTRODUCTION

Gentiana veitchiorum Hemsl. (GV) has a long history in Tibetan medicine for treating hepatobiliary disease cholestasis. However, the mechanisms mediating its efficacy in treating cholestasis have yet to be determined.

AIM

To elucidate the mechanisms of action of GV in the treatment of cholestasis, an integrated approach combining ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) analysis with network pharmacology was established.

MATERIALS AND METHODS

A comprehensive analysis of the chemical composition of GV was achieved by UPLC-MS/MS. Subsequently, a network pharmacology method that integrated target prediction, a protein-protein interaction (PPI) network, gene set enrichment analysis, and a component- target-pathway network was established, and finally, molecular docking and experiments in vitro were conducted to verify the predicted results.

RESULTS

Twenty compounds that were extracted from GV were identified by UPLC-MS/MS analysis. Core proteins such as AKT1, TNF, and IL6 were obtained through screening in the Network pharmacology PPI network. The Kyoto Encyclopedia of the Genome (KEGG) pathway predicted that GV could treat cholestasis by acting on signaling pathways such as TNF/IL-17 / PI3K-Akt. Network pharmacology suggested that GV might exert a therapeutic effect on cholestasis by regulating the expression levels of inflammatory mediators, and the results were further confirmed by the subsequent construction of an LPS-induced RAW 264.7 cell model.

CONCLUSIONS

In this study, UPLC-MS/MS analysis, network pharmacology, and experiment validation were used to explore potential mechanisms of action of GV in the treatment of cholestasis.

Exploring active ingredients and mechanisms of Coptidis Rhizoma-ginger against colon cancer using network pharmacology and molecular docking

BACKGROUND

Colon cancer is the most prevalent and rapidly increasing malignancy globally. It has been suggested that some of the ingredients in the herb pair of Coptidis Rhizoma and ginger (Zingiber officinale), a traditional Chinese medicine, have potential anti-colon cancer properties.

OBJECTIVE

This study aimed to investigate the molecular mechanisms underlying the effects of the Coptidis Rhizoma-ginger herb pair in treating colon cancer, using an integrated approach combining network pharmacology and molecular docking.

METHODS

The ingredients of the herb pair Coptidis Rhizoma-ginger, along with their corresponding protein targets, were obtained from the Traditional Chinese Medicine System Pharmacology and Swiss Target Prediction databases. Target genes associated with colon cancer were retrieved from the GeneCards and OMIM databases. Then, the protein targets of the active ingredients in the herb pair were identified, and the disease-related overlapping targets were determined using the Venn online tool. The protein-protein interaction (PPI) network was constructed using STRING database and analyzed using Cytoscape 3.9.1 to identify key targets. Then, a compound-target-disease-pathway network map was constructed. The intersecting target genes were subjected to Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses for colon cancer treatment. Molecular docking was performed using the Molecular Operating Environment (MOE) software to predict the binding affinity between the key targets and active compounds.

RESULTS

Besides 1922 disease-related targets, 630 targets associated with 20 potential active compounds of the herb pair Coptidis Rhizoma-ginger were collected. Of these, 229 intersection targets were obtained. Forty key targets, including STAT3, Akt1, SRC, and HSP90AA1, were further analyzed using the ClueGO plugin in Cytoscape. These targets are involved in biological processes such as miRNA-mediated gene silencing, phosphatidylinositol 3-kinase (PI3K) signaling, and telomerase activity. KEGG enrichment analysis showed that PI3K-Akt and hypoxia-inducible factor 1 (HIF-1) signaling pathways were closely related to colon cancer prevention by the herb pair Coptidis Rhizoma-ginger. Ten genes (Akt1, TP53, STAT3, SRC, HSP90AA1, JAK2, CASP3, PTGS2, BCl2, and ESR1) were identified as key genes for validation through molecular docking simulation.

CONCLUSIONS

This study demonstrated that the herb pair Coptidis Rhizoma-ginger exerted preventive effects against colon cancer by targeting multiple genes, utilizing various active compounds, and modulating multiple pathways. These findings might provide the basis for further investigations into the molecular mechanisms underlying the therapeutic effects of Coptidis Rhizoma-ginger in colon cancer treatment, potentially leading to the development of novel drugs for combating this disease.

Network Pharmacology, Molecular Docking and Experimental Verification Revealing the Mechanism of Fule Cream against Childhood Atopic Dermatitis

BACKGROUND

The Fule Cream (FLC) is an herbal formula widely used for the treatment of pediatric atopic dermatitis (AD), however, the main active components and functional mechanisms of FLC remain unclear. This study performed an initial exploration of the potential acting mechanisms of FLC in childhood AD treatment through analyses of an AD mouse model using network pharmacology, molecular docking technology, and RNA-seq analysis.

MATERIALS AND METHODS

The main bioactive ingredients and potential targets of FLC were collected from the Traditional Chinese Medicine Systems Pharmacology Database (TCMSP) and SwissTargetPrediction databases. An herb-compound-target network was built using Cytoscape 3.7.2. The disease targets of pediatric AD were searched in the DisGeNET, Therapeutic Target Database (TTD), OMIM, DrugBank and GeneCards databases. The overlapping targets between the active compounds and the disease were imported into the STRING database for the construction of the protein-protein interaction (PPI) network. Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of the intersection targets were performed, and molecular docking verification of the core compounds and targets was then performed using AutoDock Vina 1.1.2. The AD mouse model for experimental verification was induced by MC903.

RESULTS

The herb-compound-target network included 415 nodes and 1990 edges. Quercetin, luteolin, beta-sitosterol, wogonin, ursolic acid, apigenin, stigmasterol, kaempferol, sitogluside and myricetin were key nodes. The targets with higher degree values were IL-4, IL-10, IL-1α, IL-1β, TNFα, CXCL8, CCL2, CXCL10, CSF2, and IL-6. GO enrichment and KEGG analyses illustrated that important biological functions involved response to extracellular stimulus, regulation of cell adhesion and migration, inflammatory response, cellular response to cytokine stimulus, and cytokine receptor binding. The signaling pathways in the FLC treatment of pediatric AD mainly involve the PI3K-Akt signaling pathway, cytokine‒cytokine receptor interaction, chemokine signaling pathway, TNF signaling pathway, and NF-κB signaling pathway. The binding energy scores of the compounds and targets indicate a good binding activity. Luteolin, quercetin, and kaempferol showed a strong binding activity with TNFα and IL-4.

CONCLUSION

This study illustrates the main bioactive components and potential mechanisms of FLC in the treatment of childhood AD, and provides a basis and reference for subsequent exploration.

Proximity interactome analysis of Lassa polymerase reveals eRF3a/GSPT1 as a druggable target for host-directed antivirals

Completion of the Lassa virus (LASV) life cycle critically depends on the activities of the virally encoded, RNA-dependent RNA polymerase in replication and transcription of the viral RNA genome in the cytoplasm of infected cells. The contribution of cellular proteins to these processes remains unclear. Here, we applied proximity proteomics to define the interactome of LASV polymerase in cells under conditions that recreate LASV RNA synthesis. We engineered a LASV polymerase-biotin ligase (TurboID) fusion protein that retained polymerase activity and successfully biotinylated the proximal proteome, which allowed the identification of 42 high-confidence LASV polymerase interactors. We subsequently performed a small interfering RNA (siRNA) screen to identify those interactors that have functional roles in authentic LASV infection. As proof of principle, we characterized eukaryotic peptide chain release factor subunit 3a (eRF3a/GSPT1), which we found to be a proviral factor that physically associates with LASV polymerase. Targeted degradation of GSPT1 by a small-molecule drug candidate, CC-90009, resulted in strong inhibition of LASV infection in cultured cells. Our work demonstrates the feasibility of using proximity proteomics to illuminate and characterize yet-to-be-defined host-pathogen interactome, which can reveal new biology and uncover novel targets for the development of antivirals against highly pathogenic RNA viruses.