Systems Pharmacology Research Articles

The Potential Effects and Mechanisms of Rhododendron molle Against Rheumatoid Arthritis Based on Network Pharmacology and Molecular Docking

Background: Rheumatoid arthritis (RA) is a self-inflammatory disease with increasing global morbidity and high disability. The Chinese herbal medicine Rhododendron molle G. Dons has been conventionally used to control RA without side effects for hundreds of years, but its effect and mechanism for anti-RA are still unclear. Objective: The objective of this study is to study the potential effect and mechanism of R. molle against RA from the perspective of action targets and molecular pathways. Methods: In this study, systemic network pharmacology was used to explore the potential effect and mechanisms of R. molle against RA, including drug active components collection, target prediction, PPI network construction, and GO and KEGG pathway enrichment analyses. At last, molecular docking was carried out to estimate the pharmacological effects and mechanisms. Results: A total of 19 drug-active compounds from R. molle and 188 potential therapeutic targets for RA were screened. According to the results of molecular docking, the interaction between 4 key active compounds (rhodojaponin VI, quercetin, kaempferol, rhodojaponin VI) and 10 core target proteins (TNF, AKT1, ALB, IL-1β, TP53, EGFR, CASP3, MMP9, PTGS2, BCL2) is the closest. The results of enrichment analysis showed that the most enriched pathways were pathways related to inflammation, human T-cell leukemia virus type I infection, PI3K-Akt and IL-17. Conclusion: The Chinese herbal medicine R. molle may regulate multiple pathways by interacting with multiple drug-active compounds and core targets, and cause the patient's immune system to respond accordingly, reducing the release of inflammatory factors, and relieving joint pain.

Exploring the effect of Gouqi Nuzhen Liuhe decoction on the PI3K/mTOR signaling pathway for premature ovarian insufficiency based on system pharmacology

ObjectiveTo explore the effect of Gouqi Nuzhen Liuhe Decoction (GNLHD) on the PI3K/mTOR Signaling Pathway for Premature Ovarian Insufficiency (POI) based on system pharmacology. MethodsFirst, the system pharmacology approach was used to predict the mechanism of GNLHD. Then, mice were randomly divided into model group, positive group, GNLHD high-dose group, GNLHD medium-dose group, and GNLHD low-dose group. Hematoxylin-eosin (HE) staining was used to observe the pathological changes of ovarian tissue under light microscope. The expression levels of estradiol (E2), follicle-stimulating hormone (FSH) and luteinizing hormone (LH) were detected by enzyme-linked immunosorbent assay. The expressions of PI3K, AKT1 and mTOR proteins in ovarian tissue were detected by immunohistochemistry. ResultsThe results of system pharmacology showed that GNLHD may regulate biological processes and signaling pathways such as: reproductive structure development, reproductive system development, Oocyte meiosis and so on. Compared with the model group, the levels of E2 in the GNLHD group were increased, and the levels of FSH and LH were decreased (P < 0.05). Compared with the model group, the number of mature follicles in the GNLHD group was significantly increased, the number of atretic follicles was relatively decreased, and the expressions of PI3K, AKT1, and MTOR proteins in the GNLHD group were significantly increased (P < 0.05). ConclusionGNLHD may improve the ovarian function of POI mice by affecting the expression of PI3K, AKT1 and mTOR proteins, promote the growth and development of follicles, increase the E2 level, reduce FSH and LH level, and maintain the stability of the ovarian internal environment.

Exploring the multicomponent synergy mechanism of Zuogui Wan on postmenopausal osteoporosis by a systems pharmacology strategy.

To explore the multi-component synergistic mechanism of Zuogui Wan (, ZGW) in treating postmenopausal osteoporosis (PMOP). The main components and target genes of ZGW were screened via the Traditional Chinese Medicine Systems Pharmacology (TCMSP). In addition, the target gene sets of PMOP were derived from the GeneCards and Online Mendelian Inheritance in Man databases. The search tool for recurring instances of neighbouring genes (STRING) 11.0 software was used to analyze the interaction among intersecting genes. Cytoscape 3.6.1 software and the Matthews correlation coefficient (MCC) algorithm were used to screen the core genes. Fifty Sprague-Dawley female rats were randomly divided into the sham-operated (Sham) group and the four ovariectomized (OVX) subgroups. Rats subjected to Sham or OVX were administered with the vehicle (OVX, 1 mL water/100 g weight), 17β-estradiol (E2, 50 μg·kg-1·d-1), and lyophilized powder of ZGW at a low dose of 2.3 (ZGW-L) and high dose of 4.6 (ZGW-H) g·kg-1·d-1 for three months. The bone density and bone strength were assessed using dual-energy X-ray and three-point bending tests, respectively. Furthermore, enzyme-linked immun-osorbent assay, Hematoxylin-eosin staining, and western blot analysis were used to determine the potential pharmacological mechanisms of action of ZGW in PMOP. A total of 117 active compounds of ZGW were screened from the TCMSP. Furthermore, 108 intersecting genes of drugs and diseases were identified. Using STRING software and the MCC algorithm, ten core genes, including C-X-C chemokine living 8 (CXCL8), C-C chemokine receptor type 2 (CCR2), alpha-2a active receptor (ADRA2A), melatonin receptor type 1B (MTNR1B), and amyloid-beta A4 protein (APP), were identified. The anti-osteoporosis regulation network of ZGW was constructed using the Cytoscape software. The animal experiments demonstrated that ZGW groups significantly reduced the serum levels of β-C-terminal telopeptide of type I collagen (β-CTX) and increased serum levels of bone-specific alkaline phosphatase (BALP) (P < 0.05, P < 0.01). The OVX group exhibited a significant decrease in bone mineral density and bone strength compared with the Sham group (P < 0.01). Moreover, treatment with ZGW resulted in increased trabecular thickness, improved arrangement of trabecular structure, and reduced empty bone lacunae. Furthermore, treatment with ZGW significantly increased the protein expression of CXCL8, ADRA2A, and CCR2 (P < 0.05, P < 0.01), and significantly decreased the protein expression of Runx2 (P < 0.01). Furthermore, the ZGW and E2 groups demonstrated significantly increased BMD (P < 0.05, P < 0.01), improved bone strength (P < 0.05, P < 0.01), reduced expression of CXCL8, ADRA2A, and CCR2, and increased runt-related transcription factor 2 levels in bone tissue (P < 0.05, P < 0.01) compared with the OVX group. However, there were no significant differences in MTNR1B and APP expression among the groups. ZGW shows synergistic mechanisms in PMOP through multiple components, targets, and pathways.

Mechanistic study on the improvement of immune inflammation in ankylosing spondylitis through regulation of the PI3K/AKT signaling pathway by Huangqin Qingre Chubi capsules

AbstractObjectiveThis study aims to investigate the potential mechanisms by which the Hangqin Qingrechubi capsule (HQC) improves immunoinflammation in Ankylosing Spondylitis (AS).MethodsThe study combines systemic network pharmacology to predict, identify, and validate the core targets of HQC and AS. We conducted molecular docking to validate the interaction between the key active ingredients of HQC and the selected core targets associated with the PI3K/AKT signaling pathway, and employed data mining to delve deeper into the correlation between HQC usage and the improvement of clinical immunoinflammatory indicators. Additionally, AS‐PBMCs and FLS co‐culture cell models will be employed to further explore the mechanism of action of HQC in improving AS immune inflammation.ResultsBased on network pharmacology core target prediction, TNF‐α, IL‐17A, IL‐6, IL‐10, and AKT1 were identified as core targets, and KEGG enrichment analysis suggested that PI3K/AKT, IL‐17, and TNF might be key signaling pathways of HQC in improving immune inflammation in AS. The results of molecular docking demonstrated a favorable binding energy between the selected AKT1 core target and the key active components of HQC, including baicalin, baicalein, and quercetin. Clinical data mining revealed a significant correlation between HQC use and improvement in clinical immunoinflammatory indexes, such as ESR, CRP, IgA, IgM, IgG, C3, C4, patient perception scores (VAS, SAS, SDS), and (PF, SF) scores. In vitro cellular experiments further supported the significant ability of HQC to inhibit PI3K/AKT signaling pathway activation.ConclusionHQC, as an herbal compound preparation, exhibits anti‐inflammatory effects through multiple components and targets, making it a potential treatment option for AS. Furthermore, an underlying mechanism of action of HQC is its ability to ameliorate immune inflammation in AS patients by inhibiting the PI3K/AKT signaling pathway.

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

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

Quantitative systems pharmacology (QSP) model to predict combination activity of CD19-targeted antibody drug conjugate (loncastuximab tesirine) co-dosed with a CD20/CD3 T-cell bispecific (epcoritamab) in patients with diffuse large B-cell lymphoma (DLBCL).

e19059 Background: Loncastuximab tesirine-lpy (Lonca) is an antibody-drug conjugate comprising an anti-CD19 antibody conjugated to a pyrrolobenzodiazepine dimer cytotoxin. Epcoritamab-bysp (Epco) is a CD20×CD3 T cell-engaging bispecific antibody (bsAb) that redirects T-cells to eliminate malignant B-cells. Epco and Lonca target different B-cell surface antigens and combining both is expected to have additive or synergistic efficacy. Previously, a novel QSP model for Lonca was developed (Utsey K et al. Clin Pharmacol Drug Dev. 2023;12:123-125) and validated with clinical data from patients with R/R DLBCL (Caimi P et al. Blood. 2022;140:9548-9550). A combination QSP model for Lonca with Epco in R/R DLBCL was described to predict potential anti-tumor synergies in proposed clinical trials. Methods: The model reduced previous Lonca model complexity while maintaining core functionality and was combined with a published QSP model for T-cell bsAbs (Hosseini I et al. Npj Syst Bio Appl. 2020;6(1):1-11) to predict tumor dynamics after Lonca and/or Epco treatment. Assumptions included: 1) Lonca or Epco induce healthy and malignant B-cell killing; 2) tumor comprises malignant B- &amp; T-cells; 3) tumor volume is based on malignant B-cell count; 4) T-cells can enter or leave tumor as with other tissues; 5) CD19-/low CD20+ B-cells account for tumor heterogeneity from cells insensitive to Lonca treatment. Results: Tumor growth inhibition (TGI) was predicted to plateau by Cycle (C) 2 with Epco monotherapy. By end of C3, however, predicted median normalized tumor volume reduction with co-dosing Lonca and Epco was approximately 1 log order greater than Epco alone. Maximum activity of Lonca and Epco therapy was not observed until C4 or later as depth of tumor regression increased with additional treatment cycles. Since patients with DLBCL may present with low T-cell counts (Hutchings et al. Lancet. 2021) the effect of T-cell count at baseline was evaluated. A 50% decrease at baseline from 2000-1000 T-cells/µL significantly reduced antitumor effect with Epco alone but made no difference with Lonca in combination. Conclusions: These results resemble predictions for Lonca in combination with other bsAbs (Lonca plus mosunetuzumab or glofitamab; abstract submitted to AACR 2024). By end of C3, Lonca plus Epco was predicted to promote substantially more TGI than Epco or Lonca alone. While increased doses of Lonca from 90-150 µg/kg in combination had limited additional therapeutic benefit, combination treatment beyond C3 was predicted to increase depth of tumor regression. Response from Lonca and Epco co-dosing was predicted to be less affected by suppressed T-cell counts at baseline compared to Epco alone; a feature that may enhance responsiveness when T-cell level is moderate.

Prediction of Treatment Mechanisms of Scutellariae Radix on Viral Pneumonia Through Network Pharmacology: Focus on Hypoxic State Regulation Through HIF-1α and HSP90

Objectives: In this study, we used network-based systems pharmacology analysis and molecular docking methods to predict the therapeutic mechanism of Scutellariae Radix on viral pneumonia.Methods: We screened active components of Scutellariae Radix and its’ genes by TCMSP. Also, we extracted viral pneumonia related target genes through Gene Cards, CTD and DisGeNet. To construct Protein-protein Interaction, STRING database was used. For functional enrichment, using SRplot platform, genes were classified by 3 categories: cellular component (CC), molecular function (MF) and biological process (BP). Molecular docking was conducted by AutoDockTools (version 4.2.6).Results: 32 Network-based systematic pharmacology analysis identified 37 target genes associated with baicalein. Based on the network and gene ontology analysis of the active ingredient's target genes and disease target genes, we identified nine core genes (AKT1, BAX, BCL2, CASP3, HIF1A, PTGS2, RELA, TP53, VEGFA) and HSP90 as involved. Notably, HIF1A showed the highest relevance, overlapping with two or more utilized programs. Hypoxia-inducible factor 1-alpha (HIF-1α) has been implicated in the expression of inflammatory cytokines, the induction of hypoxia, and the triggering of cytokine storms. Baicalein, a major component of SR, binds to both HIF-1 α and HSP90, suggesting that it may be a possible targeted treatment for viral pneumonia.Conclusions: Baicalein may bind to HIF-1α to control inflammation caused by viral infectious diseases and may also regulate hypoxic conditions to prevent impairment of lung function caused by an overactive immune system. These findings suggest further research into the molecular mechanisms involved in hypoxia and provide a scientific basis for improving the treatment of viral infectious diseases.

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

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. 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. 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. 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. 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 and molecular docking to explore the treatment potential and molecular mechanism of Si-Miao decoction against gouty arthritis.

Gouty arthritis (GA) is a common metabolic rheumatological disease. Si-Miao decoction has therapeutic effects on GA. In our study, we investigated the mechanism of Si-Miao decoction against GA using network pharmacology and molecular docking analytical methods. The Traditional Chinese Medicine Systems Pharmacology Database was used as the basis for screening the main targets and agents of the Si-Miao decoction, and the Genecards, OMIM, and Drugbank databases were used to screen GA-related targets. They were analyzed using Venn with the drug targets to obtain the intersection targets. We used Cytoscape 3.9.1 to draw the "Drugs-Compounds-Targets" network and the String database for creative protein-protein interaction networks of target genes and filtered core targets. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes were used to analyze the core targets. Molecular docking was performed using AutoDockTools to predict the binding capacity between nuclear targets and active components in the Si-Miao decoction. A total of 50 chemically active components containing 53 common targets of Si-Miao decoction anti-GA and 53 potential drug target proteins were identified. Core targets, namely, TNF, STAT3, SRC, PPARG, TLR4, PTGS2, MMP9, RELA, TGFB1, and SIRT1, were obtained through PPI network analysis. GO and KEGG analyses showed that the mechanism of anti-GA in Si-Miao decoction may proceed by regulating biological processes such as inflammatory factor levels, cell proliferation, apoptosis, and lipid and glucose metabolism, and modulating the NOD-like receptor signaling pathway, IL-17 signaling pathway, TNF signaling pathway, NF-kappa B signaling pathway, and Toll-like receptor signaling pathway. We further screened the core targets, including PTGS2, MMP9, and PPAGR, as receptor proteins based on their degree value and molecular docking with the main active compounds in Si-Miao decoction, and found that baicalein had high affinity. In conclusion, Si-Miao decoction, through anti-inflammatory, apoptosis-regulating, and anti-oxidative stress action mechanisms in the treatment of GA.

Quantitative Proteomics for Translational Pharmacology and Precision Medicine: State of The Art and Future Outlook.

Over the past 20 years, quantitative proteomics has contributed a wealth of protein expression data, which are currently used for a variety of systems pharmacology applications, as a complement or a surrogate for activity of the corresponding proteins. A symposium at the 25th North American International Society for the Study of Xenobiotics meeting, in Boston, in September 2023, was held to explore current and emerging applications of quantitative proteomics in translational pharmacology and strategies for improved integration into model-informed drug development based on practical experience of each of the presenters. A summary of the talks and discussions is presented in this perspective alongside future outlook that was outlined for future meetings. SIGNIFICANCE STATEMENT: This perspective explores current and emerging applications of quantitative proteomics in translational pharmacology and precision medicine and outlines the outlook for improved integration into model-informed drug development.

Quantitative systems pharmacology modeling of macrophage-targeted therapy combined with PD-L1 inhibition in advanced NSCLC.

Immune checkpoint inhibitors remained the standard-of-care treatment for advanced non-small cell lung cancer (NSCLC) for the past decade. In unselected patients, anti-PD-(L)1 monotherapy achieved an overall response rate of about 20%. In this analysis, we developed a pharmacokinetic and pharmacodynamic module for our previously calibrated quantitative systems pharmacology model (QSP) to simulate the effectiveness of macrophage-targeted therapies in combination with PD-L1 inhibition in advanced NSCLC. By conducting in silico clinical trials, the model confirmed that anti-CD47 treatment is not an optimal option of second- and later-line treatment for advanced NSCLC resistant to PD-(L)1 blockade. Furthermore, the model predicted that inhibition of macrophage recruitment, such as using CCR2 inhibitors, can potentially improve tumor size reduction when combined with anti-PD-(L)1 therapy, especially in patients who are likely to respond to anti-PD-(L)1 monotherapy and those with a high level of tumor-associated macrophages. Here, we demonstrate the application of the QSP platform on predicting the effectiveness of novel drug combinations involving immune checkpoint inhibitors based on preclinical or early-stage clinical trial data.

Mechanism of Cnidii Fructus in the Treatment of Infertility Based on Network Pharmacology and Molecular Docking Analysis Technology.

Infertility is a condition characterized by a low fertility rate, which significantly affects the physical and mental health of women of reproductive age. Typically, the treatment duration is prolonged, and the therapeutic outcomes are often unsatisfactory. Professor Cheng-yao He, a renowned expert in traditional Chinese medicine, commonly uses the herb Cnidii Fructus (SCZ) for the treatment of infertility. However, the exact mechanism remains unclear, and there is limited research available on this topic. The active ingredients of SCZ were obtained from the traditional chinese medicine system pharmacology (TCMSP) database and screened for pharmacokinetics (PK), involving absorption, distribution, metabolism, and excretion (ADME). Target prediction was performed by SwissTargetPrediction database, and infertility-related disease targets were searched in GeneCards, TTD, DrugBank, and OMIM database. The protein-protein interaction (PPI) network was constructed using the STRING database (Version 11.5) and analyzed by Cytoscape software (Version 3.9.1). Additionally, the target genes were subjected to biological enrichment analysis in the Metascape database, including gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis, and the "Disease-Ingredient-pathway-target" network was constructed using Cytoscape software. With the assistance of AutoDockVina, Ligplot, and PyMOL software, a validation of Molecular docking results and a visualization of the results were performed. This study identified 11 retained active ingredients of SCZ, 447 drug targets, 233 of which were related to infertility, and 5393 disease targets. GO enrichment analysis mainly involved 221 biological processes such as cellular response to chemical stress and gland development. KEGG enrichment analysis mainly involved 68 pathways such as thyroid hormone signaling pathway, estrogen signaling pathway, FOXO signaling pathway, and PI3K/Akt signaling pathway. Molecular docking showed that the core active ingredients of SCZ, including Ammidin, Diosmetin, Xanthoxylin N, and Prangenidin, had strong binding abilities with core targets such as MDM2, MTOR, CCND1, EGFR, and AKT1. This study preliminarily demonstrated that SCZ may act on the PI3K/Akt signaling pathway, exerting its therapeutic effects on infertility by improving energy metabolism disorders and endometrial receptivity, inducing primordial follicle activation, regulating oocyte proliferation, differentiation, and apoptosis, and promoting the release of dominant follicles.

Mechanism-based organization of neural networks to emulate systems biology and pharmacology models.

Deep learning neural networks are often described as black boxes, as it is difficult to trace model outputs back to model inputs due to a lack of clarity over the internal mechanisms. This is even true for those neural networks designed to emulate mechanistic models, which simply learn a mapping between the inputs and outputs of mechanistic models, ignoring the underlying processes. Using a mechanistic model studying the pharmacological interaction between opioids and naloxone as a proof-of-concept example, we demonstrated that by reorganizing the neural networks' layers to mimic the structure of the mechanistic model, it is possible to achieve better training rates and prediction accuracy relative to the previously proposed black-box neural networks, while maintaining the interpretability of the mechanistic simulations. Our framework can be used to emulate mechanistic models in a large parameter space and offers an example on the utility of increasing the interpretability of deep learning networks.

Network pharmacology and transcriptomics analysis reveal the mechanism of BushenHuoxue formula attenuates premature ovarian failure via modulation PI3K/AKT pathway.

This study aims to analyze the active components and mechanism of Bushen Huoxue (BSHX) formula on the autoimmune premature ovarian insufficiency (POI) by combining network pharmacology and Transcriptomics. The active components and targets of BSHXF were screened through Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). POI-related targets were identified through Therapeutic Targets Database (TTD), DisGeNET and drugbank database. The Veen diagram was performed to obtain the action targets. The active compound-target network and Protein-Protein Interaction (PPI) network were built by using STRING database and Cytoscape software. Key targets and active compounds were further identified by topological analysis. Molecular docking shows that Kaempferol, Isorhamnetin and Anhydroicaritin have strong binding to AKT. Finally, a zp3-induced autoimmune ovarian function deficiency mouse model was used to explore the potential mechanism of POI. The potential pathways of BSHXF for the treatment of POI were identified by Transcriptomic analysis. PI3K-AKT and NF-kb pathways were the common pathways between network pharmacology and transcriptomics. Our results revealed that BSHXF could reduce the FSH expression levels and raise the E2, and AMH levels in the serum. Western bloting demonstrates that BSHXF could upregulate the expression of p-PI3K and p-AKT.

Computer-aided pattern scoring – A multitarget dataset-driven workflow to predict ligands of orphan targets

The identification of lead molecules and the exploration of novel pharmacological drug targets are major challenges of medical life sciences today. Genome‐wide association studies, multi-omics, and systems pharmacology steadily reveal new protein networks, extending the known and relevant disease-modifying proteome. Unfortunately, the vast majority of the disease-modifying proteome consists of ‘orphan targets’ of which intrinsic ligands/substrates, (patho)physiological roles, and/or modulators are unknown. Undruggability is a major challenge in drug development today, and medicinal chemistry efforts cannot keep up with hit identification and hit-to-lead optimization studies. New ‘thinking-outside-the-box’ approaches are necessary to identify structurally novel and functionally distinctive ligands for orphan targets. Here we present a unique dataset that includes critical information on the orphan target ABCA1, from which a novel cheminformatic workflow – computer-aided pattern scoring (C@PS) – for the identification of novel ligands was developed. Providing a hit rate of 95.5% and molecules with high potency and molecular-structural diversity, this dataset represents a suitable template for general deorphanization studies.

Activation of GABA type A receptor is involved in the anti-insomnia effect of Huanglian Wendan Decoction

Huanglian Wendan Decoction (HWD) is a traditional Chinese medicine (TCM) prescribed to patients diagnosed with insomnia, which can achieve excellent therapeutic outcomes. As positively modulating the γ-aminobutyric acid (GABA) type A receptors (GABAARs) is the most effective strategy to manage insomnia, this study aimed to investigate whether the activation of GABAARs is involved in the anti-insomnia effect of HWD. We assessed the metabolites of HWD using LC/MS and the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database and tested the pharmacological activity in vitro and in vivo using whole-cell patch clamp and insomnia zebrafish model. In HEK293 cells expressing α1β3γ2L GABAARs, HWD effectively increased the GABA-induced currents and could induce GABAAR-mediated currents independent of the application of GABA. In the LC-MS (QToF) assay, 31 metabolites were discovered in negative ion modes and 37 metabolites were found in positive ion modes, but neither three selected active metabolites, Danshensu, Coptisine, or Dihydromyricetin, showed potentiating effects on GABA currents. 62 active metabolites of the seven botanical drugs were collected based on the TCMSP database and 19 of them were selected for patch-clamp verification according to the virtual docking simulations and other parameters. At a concentration of 100 μM, GABA-induced currents were increased by (+)-Cuparene (278.80% ± 19.13%), Ethyl glucoside (225.40% ± 21.77%), and β-Caryophyllene (290.11% ± 17.71%). In addition, (+)-Cuparene, Ethyl glucoside, and β-Caryophyllene could also serve as positive allosteric modulators (PAMs) and shifted the GABA dose-response curve (DRC) leftward significantly. In the PCPA-induced zebrafish model, Ethyl glucoside showed anti-insomnia effects at concentrations of 100 μM. In this research, we demonstrated that the activation of GABAARs was involved in the anti-insomnia effect of HWD, and Ethyl glucoside might be a key metabolite in treating insomnia.

Widely targeted metabolomics analysis of Sanghuangporus vaninii mycelia and fruiting bodies at different harvest stages

Sanghuangprous vaninii is a medicinal macrofungus cultivated extensively in China. Both the mycelia and fruiting bodies of S. vaninii have remarkable therapeutic properties, but it remains unclear whether the mycelia may serve as a substitute for the fruiting bodies. Furthermore, S. vaninii is a perennial fungus with therapeutic components that vary significantly depending on the growing year of the fruiting bodies. Hence, it is critical to select an appropriate harvest stage for S. vaninii fruiting bodies for a specific purpose. With the aid of Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), metabolomics based on ultra-high performance liquid chromatography coupled to triple quadrupole mass spectrometry (UHPLC-QQQ-MS) was used to preliminarily determine 81 key active metabolites and 157 active pharmaceutical metabolites in S. vaninii responsible for resistance to the six major diseases. To evaluate the substitutability of the mycelia and fruiting bodies of S. vaninii and to select an appropriate harvest stage for the fruiting bodies of S. vaninii, we analyzed the metabolite differences, especially active metabolite differences, among the mycelia and fruiting bodies during three different harvest stages (1-year-old, 2-year-old, and 3-year-old). Moreover, we also determined the most prominent and crucial metabolites in each sample of S. vaninii. These results suggested that the mycelia show promise as a substitute for the fruiting bodies of S. vaninii and that extending the growth year does not necessarily lead to higher accumulation levels of active metabolites in the S. vaninii fruiting bodies. This study provided a theoretical basis for developing and using S. vaninii.

Bioinformatics study of the potential therapeutic effects of ginsenoside Rh3 in reversing insulin resistance

BackgroundIn recent years, the incidence of insulin resistance is increasing, and it can cause a variety of Metabolic syndrome. Ginsenosides have been clinically proven to improve fat metabolism and reduce insulin resistance, but their components and mechanism of action are still unclear.ObjectiveGinsenoside, a bioactive compound derived from ginseng, exhibits significant potential in treating obesity, diabetes, and metabolic disorders. Despite evidence supporting its efficacy in ameliorating insulin resistance (IR) in obesity, the specific bioactive components and underlying mechanisms remain obscure. In this study, we endeavored to elucidate the potential molecular targets and pathways influenced by ginsenoside Rh3 (GRh3) to ameliorate IR in liver tissue. We employed a comprehensive approach that integrates system pharmacology and bioinformatics analysis.Materials and methodsOur methodology involved the identification of candidate targets for GRh3 and the profiling of differentially expressed genes (DEGs) related to IR in individuals with insulin resistance. The coalescence of candidate targets and DEGs facilitated the construction of a “GRh3-targets-disease” network for each tissue type, ultimately yielding 38 shared target genes. Subsequently, we conducted pathway enrichment analysis, established protein-protein interaction (PPI) networks, and identified hub targets among the GRh3 targets and IR-related DEGs. Additionally, we conducted animal experiments to corroborate the role of these hub targets in the context of GRh3.ResultsOur investigation identified a total of 38 overlapping targets as potential candidates. Notably, our analysis revealed crucial hub targets such as EGFR, SRC, ESR1, MAPK1, and CASP3, alongside implicated signaling pathways, including those related to insulin resistance, the FoxO signaling pathway, the PPAR signaling pathway, and the IL-17 signaling pathway. This study establishes a robust foundation for the mechanisms underlying GRh3’s efficacy in mitigating IR. Furthermore, these results suggest that GRh3 may serve as a representative compound within the ginsenoside family.ConclusionThis study elucidates the potential molecular targets and associated pathways through which GRh3 ameliorates IR, showcasing its multifaceted nature, spanning multiple targets, pathways, and mechanisms. These findings establish a robust foundation for subsequent experimental inquiries and clinical applications.

Pharmacometabolomics applied to low-dose interleukin-2 treatment in amyotrophic lateral sclerosis.

Amyotrophic lateral sclerosis (ALS) is a devastating motor neuron disease. The immunosuppressive functions of regulatory T lymphocytes (Tregs) are impaired in ALS, and correlate to disease progression. The phase 2a IMODALS trial reported an increase in Treg number in ALS patients following the administration of low-dose (ld) interleukin-2 (IL-2). We propose a pharmacometabolomics approach to decipher metabolic modifications occurring in patients treated with ld-IL-2 and its relationship with Treg response. Blood metabolomic profiles were determined on days D1, D64, and D85 from patients receiving 2 MIU of IL-2 (n = 12) and patients receiving a placebo (n = 12). We discriminated the three time points for the treatment group (average error rate of 42%). Among the important metabolites, kynurenine increased between D1 and D64, followed by a reduction at D85. The percentage increase of Treg number from D1 to D64, as predicted by the metabolome at D1, was highly correlated with the observed value. This study provided a proof of concept for metabolic characterization of the effect of ld-IL-2 in ALS. These data could present advances toward a personalized medicine approach and present pharmacometabolomics as a key tool to complement genomic and transcriptional data for drug characterization, leading to systems pharmacology.

Investigating the molecular mechanism of Mori Cortex against osteosarcoma by bioinformatics analysis and in vitro experimental.

To explore the therapeutic mechanism of Mori Cortex against osteosarcoma (OS), we conducted bioinformatics prediction followed by in vitro experimental validation. Gene expression data from normal and OS tissues were obtained from the GEO database and underwent differential analysis. Active Mori Cortex components and target genes were extracted from the Traditional Chinese Medicine System Pharmacology database. By intersecting these targets with differentially expressed genes in OS, we identified potential drug action targets. Using the STRING database, a protein-protein interaction network was constructed. Subsequent analyses of these intersected genes, including Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway enrichment, were performed using R software to elucidate biological processes, molecular functions, and cellular components, resulting in the simulation of signaling pathways. Molecular docking assessed the binding capacity of small molecules to signaling pathway targets. In vitro validations were conducted on U-2 OS cells. The CCK8 assay was used to determine drug-induced cytotoxicity in OS cells, and Western Blotting was employed to validate the expression of AKT, extracellular signal-regulated kinases (ERK), Survivin, and Cyclin D1 proteins. Through differential gene expression analysis between normal and OS tissues, we identified 12,364 differentially expressed genes. From the TCSMP database, 39 active components and 185 therapeutic targets related to OS were derived. The protein-protein interaction network indicated that AKT1, IL-6, JUN, VEGFA, and CASP3 might be central targets of Mori Cortex for OS. Molecular docking revealed that the active compound Morusin in Mori Cortex exhibits strong binding affinity to AKT and ERK. The CCK8 assay showed that Morusin significantly inhibits the viability of U-2 OS cells. Western Blot demonstrated a reduction in the p-AKT/AKT ratio, the p-ERK/ERK ratio, Survivin, and Cyclin D1. Mori Cortex may exert its therapeutic effects on OS through multiple cellular signaling pathways. Morusin, the active component of Mori Cortex, can inhibit cell cycle regulation and promote cell death in OS cells by targeting AKT/ERK pathway.