HIT 2.0: an enhanced platform for Herbal Ingredients' Targets

TCMM: A unified database for traditional Chinese medicine modernization and therapeutic innovations

Mining the potential of traditional Chinese medicine (TCM) in treating modern diseases requires a profound understanding of its action mechanism and a comprehensive knowledge system that seamlessly bridges modern medical insights with traditional theories. However, existing databases for modernizing TCM are plagued by varying degrees of information loss, which impede the multidimensional dissection of pharmacological effects. To address this challenge, we introduce traditional Chinese medicine modernization (TCMM), the currently largest modernized TCM database that integrates pioneering intelligent pipelines. By aligning high-quality TCM and modern medicine data, TCMM boasts the most extensive TCM modernization knowledge, including 20 types of modernized TCM concepts such as prescription, ingredient, target and 46 biological relations among them, totaling 3,447,023 records. We demonstrate the efficacy and reliability of TCMM with two features, prescription generation and knowledge discovery, the outcomes show consistency with biological experimental results. A publicly available web interface is at https://www.tcmm.net.cn/.

Molecular mechanisms underlying Tao-Hong-Si-Wu decoction treating hyperpigmentation based on network pharmacology, Mendelian randomization analysis, and experimental verification

CONTEXT

Hyperpigmentation, a common skin condition marked by excessive melanin production, currently has limited effective treatment options.

OBJECTIVE

This study explores the effects of Tao-Hong-Si-Wu decoction (THSWD) on hyperpigmentation and to elucidate the underlying mechanisms.

MATERIALS AND METHODS

We employed network pharmacology, Mendelian randomization, and molecular docking to identify THSWD's hub targets and mechanisms against hyperpigmentation. The Cell Counting Kit-8 (CCK-8) assay determined suitable THSWD treatment concentrations for PIG1 cells. These cells were exposed to graded concentrations of THSWD-containing serum (2.5%, 5%, 10%, 15%, 20%, 30%, 40%, and 50%) and treated with α-MSH (100 nM) to induce an in vitro hyperpigmentation model. Assessments included melanin content, tyrosinase activity, and Western blotting.

RESULTS

ALB, IL6, and MAPK3 emerged as primary targets, while quercetin, apigenin, and luteolin were the core active ingredients. The CCK-8 assay indicated that concentrations between 2.5% and 20% were suitable for PIG1 cells, with a 50% cytotoxicity concentration (CC50) of 32.14%. THSWD treatment significantly reduced melanin content and tyrosinase activity in α-MSH-induced PIG1 cells, along with downregulating MC1R and MITF expression. THSWD increased ALB and p-MAPK3/MAPK3 levels and decreased IL6 expression in the model cells.

DISCUSSION AND CONCLUSION

THSWD mitigates hyperpigmentation by targeting ALB, IL6, and MAPK3. This study paves the way for clinical applications of THSWD as a novel treatment for hyperpigmentation and offers new targeted therapeutic strategies.

Elucidation of the anti-colorectal cancer mechanism of Atractylodes lancea by network pharmacology and experimental verification

Atractylodes lancea which was listed in "Shennong's Materia Medica" and could be used to treat gastrointestinal-associated diseases. However, its roles, core and active ingredients, and mechanisms in treatment of colorectal cancer (CRC) were still unknown. Therefore, network pharmacology and experimental validation were used to clarify the effects, core active ingredients and molecular mechanisms of Atractylodes lancea. We found that Atractylodes lancea has 28 effective active components and 213 potential targets. Seventy-three genes which demonstrate interaction between the Atractylodes lancea and CRC were confirmed. Enrichment analysis showed that 2033 GO biological process items and 144 KEGG pathways. Survival and molecular docking analysis revealed that luteolin as the core component interacted with these genes (Matrix metalloproteinase 3 (MMP3), Matrix metalloproteinase 9 (MMP9), Tissue inhibitor of metalloproteinases 1 (TIMP1), Vascular endothelial growth factor A (VEGFA)) with the lowest binding energy, and these genes were involved in building a prognostic model for CRC. Cellular phenotyping experiments showed that luteolin could inhibit the proliferation and migration of CRC cells and downregulate the expression of MMP3, MMP9, TIMP1, VEGFA probably by Phosphoinositide 3-kinase/ serine/threonine kinase Akt (PI3K/AKT) pathway. To conclude, Atractylodes lancea could inhibit proliferation and migration of CRC cells through its core active ingredient (luteolin) to suppress the expression of MMP3, MMP9, TIMP1, VEGFA probably by PI3K/AKT pathway.

Naoxintong capsule accelerates mitophagy in cerebral ischemia-reperfusion injury via TP53/PINK1/PRKN pathway based on network pharmacology analysis and experimental validation

ETHNOPHARMACOLOGICAL RELEVANCE

The incidence and mortality of cerebrovascular diseases are increasing year by year. Cerebral ischemia-reperfusion injury (CIRI) is common in patients with ischemic stroke. Naoxintong (NXT) is composed of a variety of Chinese medicines and has the ability to treat CIRI.

AIM OF THE STUDY

The aim of this study is to investigate whether NXT regulates mitophagy in CIRI based on network pharmacology analysis and experimental validation.

MATERIALS AND METHODS

Oxygen and glucose deprivation/re-oxygenation (OGD/R, 2/22 h) model of PC12 cells and transient middle cerebral artery occlusion (tMCAO, 2/22 h) model of rats were established. Pharmacodynamic indicators include neurological deficit score, 2,3,5-triphenyte-trazoliumchloride (TTC) staining, hematoxylin-eosin (HE) staining and cell viability. Network pharmacology was used to predict pharmacological mechanisms. Pharmacological mechanism indexes include transmission electron microscopy (TEM), drug affinity responsive target stability (DARTS), cellular thermal shift assay (CETSA), immunohistochemistry (IHC), western blot (WB) and immunofluorescence (IF). Kevetrin (an agonists of p53) and pifithrin-α (an inhibitor of p53) used to detect the key role of p53 in mitophagy of NXT.

RESULTS

NXT (1% serum containing NXT and 110 mg/kg) improved the damage of OGD/R PC12 cells and tMCAO rats, and this protective effect was related to the anti-oxidation and ability to promote mitophagy of NXT. NXT and pifithrin-α increased the expression of promoting-mitophagy targets (PINK1, PRKN and LC3B) and inhibited the expression of inhibiting-mitophagy targets (p52) via restraining p53, and finally accelerated mitophagy caused by CIRI.

CONCLUSION

This study demonstrates that NXT promotes mitophagy in CIRI through restraining p53 and promoting PINK1/PRKN in vivo and in vitro.

Overview and limitations of database in global traditional medicines: A narrative review

The study of traditional medicine has garnered significant interest, resulting in various research areas including chemical composition analysis, pharmacological research, clinical application, and quality control. The abundance of available data has made databases increasingly essential for researchers to manage the vast amount of information and explore new drugs. In this article we provide a comprehensive overview and summary of 182 databases that are relevant to traditional medicine research, including 73 databases for chemical component analysis, 70 for pharmacology research, and 39 for clinical application and quality control from published literature (2000-2023). The review categorizes the databases by functionality, offering detailed information on websites and capacities to facilitate easier access. Moreover, this article outlines the primary function of each database, supplemented by case studies to aid in database selection. A practical test was conducted on 68 frequently used databases using keywords and functionalities, resulting in the identification of highlighted databases. This review serves as a reference for traditional medicine researchers to choose appropriate databases and also provides insights and considerations for the function and content design of future databases.

Molecular insights into chronic atrophic gastritis treatment: Coptis chinensis Franch studied via network pharmacology, molecular dynamics simulation and experimental analysis

Chronic atrophic gastritis (CAG), characterized by inflammation and erosion of the gastric lining, is a prevalent digestive disorder and considered a precursor to gastric cancer (GC). Coptis chinensis France (CCF) is renowned for its potent heat-clearing, detoxification, and anti-inflammatory properties. Zuojin Pill (ZJP), a classic Chinese medicine primarily composed of CCF, has demonstrated effectiveness in CAG treatment. This study aims to elucidate the potential mechanism of CCF treatment for CAG through a multifaceted approach encompassing network pharmacology, molecular docking, molecular dynamics simulation and experimental verification. The study identified three major active compounds of CCF and elucidated key pathways, such as TNF signaling, PI3K-Akt signaling and p53 signaling. Molecular docking revealed interactions between these active compounds and pivotal targets like PTGS2, TNF, MTOR, and TP53. Additionally, molecular dynamics simulation validated berberine as the primary active compound of CCF, which was further confirmed through experimental verification. This study not only identified berberine as the primary active compound of CCF but also provided valuable insights into the molecular mechanisms underlying CCF's efficacy in treating CAG. Furthermore, it offers a reference for refining therapeutic strategies for CAG management.

Safflower Alleviates Pulmonary Arterial Hypertension by Inactivating NLRP3: A Combined Approach of Network Pharmacology and Experimental Verification

INTRODUCTION

Traditional Chinese medicinal plant, safflower, shows effective for treating pulmonary arterial hypertension (PAH), yet the underlying mechanisms remain largely unexplored. This study is aimed at exploring the potential molecular mechanisms of safflower in the treatment of PAH.

METHODS

Network pharmacology approach and molecular docking were applied to identify the core active compounds, therapeutic targets, and potential signaling pathways of safflower against PAH. Meanwhile, high-performance liquid chromatography (HPLC) assay was performed to determine the core compounds from safflower. Further, the mechanism of action of safflower on PAH was verified by in vivo and in vitro experiments.

RESULTS

A total of 15 active compounds and 177 targets were screened from safflower against PAH. Enrichment analysis indicated that these therapeutic targets were mainly involved in multiple key pathways, such as TNF signaling pathway and Th17 cell differentiation. Notably, molecular docking revealed that quercetin (core compound in safflower) displayed highest binding capacity with NLRP3. In vivo, safflower exerted therapeutic effects on PAH by inhibiting right ventricular hypertrophy, inflammatory factor release, and pulmonary vascular remodeling. Mechanistically, it significantly reduced the expression of proangiogenesis-related factors (MMP-2, MMP-9, Collagen 1, and Collagen 3) and NLRP3 inflammasome components (NLRP3, ASC, and Caspase-1) in PAH model. Similarly, these results were observed in vitro. Besides, we further confirmed that NLRP3 inhibitor had the same therapeutic effect as safflower in vitro.

CONCLUSION

Our findings suggest that safflower mitigates PAH primarily by inhibiting NLRP3 inflammasome activation. This provides novel insights into the potential use of safflower as an alternative therapeutic approach for PAH.

Integrating network pharmacology and experimental validation to explore the mitophagy-associated pharmacological mechanism of modified Shisiwei Jianzhong decoction against aplastic anemia

The aim of this work was to investigate the therapeutic effect of modified Shisiwei Jianzhong Decoction (SJD) on aplastic anemia (AA) and its potential pharmacological mechanism from the perspective of mitophagy. A comprehensive approach combining network pharmacology, mendelian randomization, molecular docking and animal experiments was applied to evaluate the properties of SJD against AA. By integrating multiple databases, it was determined that SJD exerted its therapeutic effect on AA by targeting three key targets [mammalian target of rapamycin (MTOR), poly(ADP-ribose) polymerase 1 (PARP1) and Sirtuin 1 (SIRT1)] through four core compounds (quercetin, resveratrol, genistein and curcumin). Mendelian randomization analysis identified MTOR as a risk factor for AA occurrence while PARP1 was a protective factor. Results of animal experiments showed that SJD improved peripheral blood counts and promoted the proliferation of hematopoietic stem cells. Mechanistically, SJD, especially at high dose, played a therapeutic role in AA by activating mitophagy-related proteins PTEN induced kinase 1 (PINK1)/Parkin and inhibiting the phosphatidylinositol 3-kinase (PI3K)/protein kinase (AKT)/MTOR pathway. This study revealed for the first time the core chemical composition of SJD and its pharmacological effects against AA, which can restore hematopoietic function by activating mitophagy. The results provide inspiration for the clinical application of traditional Chinese medicine in AA treatment.

Pharmacological mechanisms of Taohe Chengqi decoction in diabetic cardiovascular complications: A systematic review, network pharmacology and molecular docking

Background

Diabetic cardiovascular complications are the leading cause of diabetes-related deaths. These complications place an enormous and growing burden on global health systems and economies. The objective of this study was to conduct a systematic review on the therapeutic mechanisms of Taohe Chengqi Decoction (THCQD) in the treatment of diabetic cardiovascular complications. To predict the potential mechanisms of action of THCQD on diabetic cardiovascular complications using network pharmacology, and to validate these predictions through molecular docking analysis.

Methods

To collect relevant animal experiments, we searched a total of 6 databases. Eligibility for the study was determined based on inclusion and exclusion criteria. Data extraction was then performed on the literature. Methodological quality of animal studies was assessed using SYRCLE criteria. Based on network pharmacology, intersecting genes for THCQD and diabetic cardiovascular complications were obtained using Venny, PPI analysis and topology analysis of intersecting genes were performed; GO and KEGG were used for enrichment analysis and prediction of new targets of action. Molecular docking techniques were employed to model the interactions between drug components and target genes, thereby validating the results of network pharmacology predictions.

Results

A total of 16 studies were finally identified that fit the direction of this review. Included 6 studies of the myocardium, 1 study of the aortic arch, 5 studies of the femoral artery, 4 studies of the thoracic aorta. THCQD exhibited anti-inflammatory, anti-fibrotic and anti-atherosclerotic effects on cardiovascular complications in diabetic rats. Network pharmacology results showed that C0363 (Resveratrol), C0041 (Emodin), and C1114 (Baicalein) were the key components in the treatment of diabetic cardiovascular complications by THCQD. PPI results showed that INS, AKT1, TNF, ALB, IL6, IL1B as the genes that interact with the top 6. KEGG enrichment analysis identified the AGE-RAGE signaling pathway in diabetic complications as the most prominent pathway enriched by THCQD for diabetic cardiovascular complications genes. The results of molecular docking showed that the key active components demonstrated favorable interactions with their corresponding target genes.

Conclusion

In conclusion, the results of both basic and web-based pharmacological studies support the beneficial effects of the natural herbal formulation THCQD on diabetic cardiovascular complications. This decoction has anti-inflammatory and antifibrotic properties and is effective in ameliorating diabetic cardiovascular disease. The network pharmacology results further support these ideas and identify the AGE-RAGE signaling pathway in diabetic complications as possibly the most relevant pathway for THCQD in the treatment of diabetic cardiovascular complications. The extent of the therapeutic potential of all-natural herbal components in the treatment of diabetic cardiovascular disease merits further investigation.

Network Medicine: A Potential Approach for Virtual Drug Screening

Traditional drug screening methods typically focus on a single protein target and exhibit limited efficiency due to the multifactorial nature of most diseases, which result from disturbances within complex networks of protein-protein interactions rather than single gene abnormalities. Addressing this limitation requires a comprehensive drug screening strategy. Network medicine is rooted in systems biology and provides a comprehensive framework for understanding disease mechanisms, prevention, and therapeutic innovations. This approach not only explores the associations between various diseases but also quantifies the relationships between disease genes and drug targets within interactome networks, thus facilitating the prediction of drug-disease relationships and enabling the screening of therapeutic drugs for specific complex diseases. An increasing body of research supports the efficiency and utility of network-based strategies in drug screening. This review highlights the transformative potential of network medicine in virtual therapeutic screening for complex diseases, offering novel insights and a robust foundation for future drug discovery endeavors.

Network pharmacology: an efficient but underutilized approach in oral, head and neck cancer therapy-a review

The application of network pharmacology (NP) has advanced our understanding of the complex molecular mechanisms underlying diseases, including neck, head, and oral cancers, as well as thyroid carcinoma. This review aimed to explore the therapeutic potential of natural network pharmacology using compounds and traditional Chinese medicines for combating these malignancies. NP serves as a pivotal tool that provides a comprehensive view of the interactions among compounds, genes, and diseases, thereby contributing to the advancement of disease treatment and management. In parallel, this review discusses the significance of publicly accessible databases in the identification of oral, head, and neck cancer-specific genes. These databases, including those for head and neck oral cancer, head and neck cancer, oral cancer, and genomic variants of oral cancer, offer valuable insights into the genes, miRNAs, drugs, and genetic variations associated with these cancers. They serve as indispensable resources for researchers, clinicians, and drug developers, contributing to the pursuit of precision medicine and improved treatment of these challenging malignancies. In summary, advancements in NP could improve the globalization and modernization of traditional medicines and prognostic targets as well as aid in the development of innovative drugs. Furthermore, this review will be an eye-opener for researchers working on drug development from traditional medicines by applying NP approaches.

Systematic exploration of therapeutic effects and key mechanisms of Panax ginseng using network-based approaches

Background

Network pharmacology has emerged as a powerful tool to understand the therapeutic effects and mechanisms of natural products. However, there is a lack of comprehensive evaluations of network-based approaches for natural products on identifying therapeutic effects and key mechanisms.

Purpose

We systematically explore the capabilities of network-based approaches on natural products, using Panax ginseng as a case study. P. ginseng is a widely used herb with a variety of therapeutic benefits, but its active ingredients and mechanisms of action on chronic diseases are not yet fully understood.

Methods

Our study compiled and constructed a network focusing on P. ginseng by collecting and integrating data on ingredients, protein targets, and known indications. We then evaluated the performance of different network-based methods for summarizing known and unknown disease associations. The predicted results were validated in the hepatic stellate cell model.

Results

We find that our multiscale interaction-based approach achieved an AUROC of 0.697 and an AUPR of 0.026, which outperforms other network-based approaches. As a case study, we further tested the ability of multiscale interactome-based approaches to identify active ingredients and their plausible mechanisms for breast cancer and liver cirrhosis. We also validated the beneficial effects of unreported and top-predicted ingredients, in cases of liver cirrhosis and gastrointestinal neoplasms.

Conclusion

our study provides a promising framework to systematically explore the therapeutic effects and key mechanisms of natural products, and highlights the potential of network-based approaches in natural product research.

Integrating network pharmacology and Mendelian randomization to explore potential targets of matrine against ovarian cancer

BACKGROUND

Matrine has been reported inhibitory effects on ovarian cancer (OC) cell progression, development, and apoptosis. However, the molecular targets of matrine against OC and the underlying mechanisms of action remain elusive.

OBJECTIVE

This study endeavors to unveil the potential targets of matrine against OC and to explore the intricate relationships between these targets and the pathogenesis of OC.

METHODS

The effects of matrine on the OC cells (A2780 and AKOV3) viability, apoptosis, migration, and invasion was investigated through CCK-8, flow cytometry, wound healing, and Transwell analyses, respectively. Next, Matrine-related targets, OC-related genes, and ribonucleic acid (RNA) sequence data were harnessed from publicly available databases. Differentially expressed analyses, protein-protein interaction (PPI) network, and Venn diagram were involved to unravel the core targets of matrine against OC. Leveraging the GEPIA database, we further validated the expression levels of these core targets between OC cases and controls. Mendelian randomization (MR) study was implemented to delve into potential causal associations between core targets and OC. The AutoDock software was used for molecular docking, and its results were further validated using RT-qPCR in OC cell lines.

RESULTS

Matrine reduced the cell viability, migration, invasion and increased the cell apoptosis of A2780 and AKOV3 cells (P< 0.01). A PPI network with 578 interactions among 105 candidate targets was developed. Finally, six core targets (TP53, CCND1, STAT3, LI1B, VEGFA, and CCL2) were derived, among which five core targets (TP53, CCND1, LI1B, VEGFA, and CCL2) differential expressed in OC and control samples were further picked for MR analysis. The results revealed that CCND1 and TP53 were risk factors for OC. Molecular docking analysis demonstrated that matrine had good potential to bind to TP53, CCND1, and IL1B. Moreover, matrine reduced the expression of CCND1 and IL1B while elevating P53 expression in OC cell lines.

CONCLUSIONS

We identified six matrine-related targets against OC, offering novel insights into the molecular mechanisms underlying the therapeutic effects of matrine against OC. These findings provide valuable guidance for developing more efficient and targeted therapeutic approaches for treating OC.

Network-based analysis identifies potential therapeutic ingredients of Chinese medicines and their mechanisms toward lung cancer

Lung cancer is one of the most common malignant tumors around the world, which has the highest mortality rate among all cancers. Traditional Chinese medicine (TCM) has attracted increased attention in the field of lung cancer treatment. However, the abundance of ingredients in Chinese medicines presents a challenge in identifying promising ingredient candidates and exploring their mechanisms for lung cancer treatment. In this work, two network-based algorithms were combined to calculate the network relationships between ingredient targets and lung cancer targets in the human interactome. Based on the enrichment analysis of the constructed disease module, key targets of lung cancer were identified. In addition, molecular docking and enrichment analysis of the overlapping targets between lung cancer and ingredients were performed to investigate the potential mechanisms of ingredient candidates against lung cancer. Ten potential ingredients against lung cancer were identified and they may have similar effect on the development of lung cancer. The results obtained from this study offered valuable insights and provided potential avenues for the development of novel drugs aimed at treating lung cancer.

Unveiling Anti-Diabetic Potential of Baicalin and Baicalein from Baikal Skullcap: LC-MS, In Silico, and In Vitro Studies

Type 2 diabetes mellitus (T2DM) is marked by persistent hyperglycemia, insulin resistance, and pancreatic β-cell dysfunction, imposing substantial health burdens and elevating the risk of systemic complications and cardiovascular diseases. While the pathogenesis of diabetes remains elusive, a cyclical relationship between insulin resistance and inflammation is acknowledged, wherein inflammation exacerbates insulin resistance, perpetuating a deleterious cycle. Consequently, anti-inflammatory interventions offer a therapeutic avenue for T2DM management. In this study, a herb called Baikal skullcap, renowned for its repertoire of bioactive compounds with anti-inflammatory potential, is posited as a promising source for novel T2DM therapeutic strategies. Our study probed the anti-diabetic properties of compounds from Baikal skullcap via network pharmacology, molecular docking, and cellular assays, concentrating on their dual modulatory effects on diabetes through Protein Tyrosine Phosphatase 1B (PTP1B) enzyme inhibition and anti-inflammatory actions. We identified the major compounds in Baikal skullcap using liquid chromatography-mass spectrometry (LC-MS), highlighting six flavonoids, including the well-studied baicalein, as potent inhibitors of PTP1B. Furthermore, cellular experiments revealed that baicalin and baicalein exhibited enhanced anti-inflammatory responses compared to the active constituents of licorice, a known anti-inflammatory agent in TCM. Our findings confirmed that baicalin and baicalein mitigate diabetes via two distinct pathways: PTP1B inhibition and anti-inflammatory effects. Additionally, we have identified six flavonoid molecules with substantial potential for drug development, thereby augmenting the T2DM pharmacotherapeutic arsenal and promoting the integration of herb-derived treatments into modern pharmacology.

Golden bile powder prevents drunkenness and alcohol-induced liver injury in mice via the gut microbiota and metabolic modulation

BACKGROUND

Drunkenness and alcoholic liver disease (ALD) are critical public health issues associated with significant morbidity and mortality due to chronic overconsumption of alcohol. Traditional remedies, such as bear bile powder, have been historically acclaimed for their hepatoprotective properties. This study assessed the efficacy of a biotransformed bear bile powder known as golden bile powder (GBP) in alleviating alcohol-induced drunkenness and ALD.

METHODS

A murine model was engineered to simulate alcohol drunkenness and acute hepatic injury through the administration of a 50% ethanol solution. Intervention with GBP and its effects on alcohol-related symptoms were scrutinized, by employing an integrative approach that encompasses serum metabolomics, network medicine, and gut microbiota profiling to elucidate the protective mechanisms of GBP.

RESULTS

GBP administration significantly delayed the onset of drunkenness and decreased the duration of ethanol-induced inebriation in mice. Enhanced liver cell recovery was indicated by increased hepatic aldehyde dehydrogenase levels and superoxide dismutase activity, along with significant decreases in the serum alanine aminotransferase, aspartate aminotransferase, alkaline phosphatase, triglyceride, and total cholesterol levels (P < 0.05). These biochemical alterations suggest diminished hepatic damage and enhanced lipid homeostasis. Microbiota analysis via 16S rDNA sequencing revealed significant changes in gut microbial diversity and composition following alcohol exposure, and these changes were effectively reversed by GBP treatment. Metabolomic analyses demonstrated that GBP normalized the alcohol-induced perturbations in phospholipids, fatty acids, and bile acids. Correlation assessments linked distinct microbial genera to serum bile acid profiles, indicating that the protective efficacy of GBP may be attributable to modulatory effects on metabolism and the gut microbiota composition. Network medicine insights suggest the prominence of two active agents in GBP as critical for addressing drunkenness and ALD.

CONCLUSION

GBP is a potent intervention for alcohol-induced pathology and offers hepatoprotective benefits, at least in part, through the modulation of the gut microbiota and related metabolic cascades.

Protective effect and mechanism of Qingfei Paidu decoction on myocardial damage mediated by influenza viruses

Introduction: Significant attention has been paid to myocardial damage mediated by the single-stranded RNA virus. Qingfei Paidu decoction (QFPDD) has been proved to protect the damage caused by the influenza virus A/PR/8/1934 (PR8), but its specific mechanism is unclear. Methods: Molecular biological methods, together with network pharmacology, were used to analyze the effects and underlying mechanism of QFPDD treatment on PR8-induced myocardial damage to obtain insights into the treatment of COVID-19-mediated myocardial damage. Results: Increased apoptosis and subcellular damage were observed in myocardial cells of mice infected by PR8. QFPDD treatment significantly inhibited the apoptosis and subcellular damage induced by the PR8 virus. The inflammatory factors IFN-β, TNF-α, and IL-18 were statistically increased in the myocardia of the mice infected by PR8, and the increase in inflammatory factors was prevented by QFPDD treatment. Furthermore, the expression levels or phosphorylation of necroptosis-related proteins RIPK1, RIPK3, and MLKL were abnormally elevated in the group of infected mice, while QFPDD restored the levels or phosphorylation of these proteins. Our study demonstrated that HIF-1α is a key target of QFPDD in the treatment of influenza virus-mediated injury. The HIF-α level was significantly increased by PR8 infection. Both the knockdown of HIF-1α and treatment of the myocardial cell with QFPDD significantly reversed the increased inflammatory factors during infection. Overexpression of HIF-1α reversed the inhibition effects of QFPDD on cytokine expression. Meanwhile, seven compounds from QFPDD may target HIF-1α. Conclusion: QFPDD can ameliorate influenza virus-mediated myocardial damage by reducing the degree of cell necroptosis and apoptosis, inhibiting inflammatory response and the expression of HIF-1α. Thus, our results provide new insights into the treatment of respiratory virus-mediated myocardial damage.

Multi-target meridians classification based on the topological structure of anti-cancer phytochemicals using deep learning

ETHNOPHARMACOLOGICAL RELEVANCE

Traditional Chinese medicine (TCM) meridian is the key theoretical guidance of prescription against tumor in clinical practice. However, there is no scientific and systematic verification of therapeutic action of herbs under meridians context. Several studies have determined the Chinese herbal medicine (CHM) phytochemicals for intrinsic attribute or meridians classification based on artificial intelligence (AI) tools. However, it is challenging to represent the complex molecular structures with large heterogeneity through the current technologies. In addition, the multiple correspondence between herbs and meridians has not been paid much attention.

AIM OF THE STUDY

We aim to develop an AI framework to classify multi-target meridians through the topological structure of phytochemicals.

MATERIALS AND METHODS

A total of 354 anti-cancer herbs, their corresponding TCM meridians and 5471 ingredient compounds were collected from public databases of CancerHSP, ETCM, and Hit 2.0. The statistical analysis of herbal and compound datasets, clustering analysis of the associated cancers, and correlational analysis of meridian tropism were preliminary conducted. Then a deep learning (DL) hybrid model named GRMC consisting of graph convolutional network (GCN) and recurrent neural network (RNN) was employed to generate the meridian multi-label sequences based on molecular graph.

RESULTS

The curing herbs against tumors have tight relationships to lung, liver, stomach, and spleen meridians. These herbs behave different properties in curing certain cancer. Certain cancer types have co-occurrence such as ovarian, bladder and cervical cancer. Compounds have multitarget meridians with characteristics of higher-order correlations. Compared with the other state-of-the-art algorithms on the datasets and previous methods dealing with conventional fixed fingerprints of herbal compounds, the proposed GRMC has superior overall performance on testing dataset with the one error of 0.183, hamming loss of 0.112, mean averaged accuracy (MAA) of 0.855, mean averaged precision (MAP) of 0.891, mean averaged recall (MAR) of 0.812, and mean averaged F1 score (MAF) of 0.849.

CONCLUSIONS

The proposed method can predict multi-targeted meridians through neural graph features in herbal compounds and outperforms several comparison methods. It could provide a basis for understanding the molecular scientific evidence of TCM meridians.

TM-MC 2.0: an enhanced chemical database of medicinal materials in Northeast Asian traditional medicine

BACKGROUND

As chromatographic techniques have advanced, many articles that analyze the constituting compounds of medicinal materials have been published in relation to Northeast Asian traditional medicine, including traditional Chinese medicine (TCM). TM-MC was launched in 2015, providing information about the chemical compounds in medicinal materials from chromatographic articles in PubMed. Since 2015, through continuous curation efforts, we have now released TM-MC 2.0 with significant improvements to the quantity and quality of the data ( https://tm-mc.kr ).

DESCRIPTION

TM-MC 2.0 contains 635 medicinal materials, 34,107 chemical compounds (21,306 identified and de-duplicated), 13,992 targets, 27,997 diseases, and 5,075 prescriptions (2,393 de-duplicated by name). The database provides the largest number of identified compounds for medicinal materials listed in the pharmacopoeia compared to all TCM databases. In particular, marker compounds of medicinal materials and many newly discovered compounds were added through the manual curation of recent chromatographic articles.

CONCLUSION

TM-MC 2.0 provides the largest collection of information about the chemical compounds of the medicinal materials listed in the Korean, Chinese, and Japanese pharmacopoeias. Our database can be utilized for network pharmacology in traditional medicine and for the compound screening of medicinal materials for modern drug discovery.

CMAUP database update 2024: extended functional and association information of useful plants for biomedical research

Knowledge of the collective activities of individual plants together with the derived clinical effects and targeted disease associations is useful for plant-based biomedical research. To provide the information in complement to the established databases, we introduced a major update of CMAUP database, previously featured in NAR. This update includes (i) human transcriptomic changes overlapping with 1152 targets of 5765 individual plants, covering 74 diseases from 20 027 patient samples; (ii) clinical information for 185 individual plants in 691 clinical trials; (iii) drug development information for 4694 drug-producing plants with metabolites developed into approved or clinical trial drugs; (iv) plant and human disease associations (428 737 associations by target, 220 935 reversion of transcriptomic changes, 764 and 154121 associations by clinical trials of individual plants and plant ingredients); (v) the location of individual plants in the phylogenetic tree for navigating taxonomic neighbors, (vi) DNA barcodes of 3949 plants, (vii) predicted human oral bioavailability of plant ingredients by the established SwissADME and HobPre algorithm, (viii) 21-107% increase of CMAUP data over the previous version to cover 60 222 chemical ingredients, 7865 plants, 758 targets, 1399 diseases, 238 KEGG human pathways, 3013 gene ontologies and 1203 disease ontologies. CMAUP update version is freely accessible at https://bidd.group/CMAUP/index.html.

MACC: a visual interactive knowledgebase of metabolite-associated cell communications

Metabolite-associated cell communications play critical roles in maintaining the normal biological function of human through coordinating cells, organs and physiological systems. Though substantial information of MACCs has been continuously reported, no relevant database has become available so far. To address this gap, we here developed the first knowledgebase (MACC), to comprehensively describe human metabolite-associated cell communications through curation of experimental literatures. MACC currently contains: (a) 4206 carefully curated metabolite-associated cell communications pairs involving 244 human endogenous metabolites and reported biological effects in vivo and in vitro; (b) 226 comprehensive cell subtypes and 296 disease states, such as cancers, autoimmune diseases, and pathogenic infections; (c) 4508 metabolite-related enzymes and transporters, involving 542 pathways; (d) an interactive tool with user-friendly interface to visualize networks of multiple metabolite-cell interactions. (e) overall expression landscape of metabolite-associated gene sets derived from over 1500 single-cell expression profiles to infer metabolites variations across different cells in the sample. Also, MACC enables cross-links to well-known databases, such as HMDB, DrugBank, TTD and PubMed etc. In complement to ligand-receptor databases, MACC may give new perspectives of alternative communication between cells via metabolite secretion and adsorption, together with the resulting biological functions. MACC is publicly accessible at: http://macc.badd-cao.net/.

BATMAN-TCM 2.0: an enhanced integrative database for known and predicted interactions between traditional Chinese medicine ingredients and target proteins

Traditional Chinese medicine (TCM) is increasingly recognized and utilized worldwide. However, the complex ingredients of TCM and their interactions with the human body make elucidating molecular mechanisms challenging, which greatly hinders the modernization of TCM. In 2016, we developed BATMAN-TCM 1.0, which is an integrated database of TCM ingredient-target protein interaction (TTI) for pharmacology research. Here, to address the growing need for a higher coverage TTI dataset, and using omics data to screen active TCM ingredients or herbs for complex disease treatment, we updated BATMAN-TCM to version 2.0 (http://bionet.ncpsb.org.cn/batman-tcm/). Using the same protocol as version 1.0, we collected 17 068 known TTIs by manual curation (with a 62.3-fold increase), and predicted ∼2.3 million high-confidence TTIs. In addition, we incorporated three new features into the updated version: (i) it enables simultaneous exploration of the target of TCM ingredient for pharmacology research and TCM ingredients binding to target proteins for drug discovery; (ii) it has significantly expanded TTI coverage; and (iii) the website was redesigned for better user experience and higher speed. We believe that BATMAN-TCM 2.0, as a discovery repository, will contribute to the study of TCM molecular mechanisms and the development of new drugs for complex diseases.

Study of Therapeutic Mechanisms of Bupi Yichang Formula against Colon Cancer Based on Network Pharmacology, Machine Learning, and Experimental Verification

Bupi Yichang formula (BPYCF) has shown the anti-cancer potential; however, its effects on colon cancer and the mechanisms remain unknown. This study intended to explore the effects of BPYC on colon cancer and its underlying mechanisms. BPYCF-related and colon cancer-related targets were acquired from public databases, followed by differentially expressed genes (DEG) identification. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed using clusterProfiler. A protein-protein interaction (PPI) network was constructed using STRING database. CytoHubba and MCODE to screen the hub targets. A diagnostic model was built using random forest algorithm. Molecular docking was conducted using PyMOL and AutoDock. High-performance liquid chromatograph-mass spectrometry (HPLC-MS) analysis and in vitro validation were performed. Forty-six overlapping targets of BPYCF-related, colon cancer-related targets, and DEGs were obtained. GO and KEGG analyses showed that the targets were mainly enriched in response to lipopolysaccharide, neuronal cell body, protein serine/threonine/tyrosine, as well as C-type lectin receptor, NOD-like receptor, and TNF signaling pathways. Five targets were identified as the pivotal targets, among which, NOS3, CASP8, RIPK3, and TNFRSF10B were stably docked with the core active component, naringenin. Naringenin was also identified from the BPYCF sample through HPLC-MS analysis. In vitro experiments showed that BPYCF inhibited cell viability, reduced NOS3 expression, and elevated CASP8, RIPK3, and TNFRSF10B expression in colon cancer cells. BPYCF might treat colon cancer mainly by regulating NOS3, CASP8, RIPK3, and TN-FRSF10B. This study first revealed the therapeutic effects and mechanisms of BPYCF against colon cancer, paving the path for the development of targeted therapeutic strategies for this cancer in the clinic.

Exploration of the Mechanisms Underlying Yu's Enema Formula in Treating Ulcerative Colitis by Blocking the RhoA/ROCK Pathway based on Network Pharmacology, High-performance Liquid Chromatography Analysis, and Experimental Verification

BACKGROUND

The traditional Chinese medicine formula, Yu's Enema Formula (YEF), has demonstrated potential in the treatment of Ulcerative Colitis (UC).

OBJECTIVE

This study aimed to unveil the anti-UC mechanisms of YEF.

METHODS

Utilizing public databases, we obtained YEF and UC-related targets. GO and KEGG analyses were conducted via clusterProfiler and Reactome. The STRING database facilitated the construction of the PPI network, and hub targets were selected using cytoHubba. We used R software for differential expression and correlation analyses, and molecular docking was performed with PyMOL and AutoDock. HPLC analysis identified the compounds in YEF. For in vivo validation, a UC rat model was employed.

RESULTS AND DISCUSSION

495 YEF-UC overlapping targets were identified. GO and KEGG analyses indicated enrichment in exogenous stimuli response, peptide response, positive MAPK cascade regulation, interleukin- related signaling, and the TLR4 cascade. Hub targets included CTNNB1, JUN, MAPK1, MAPK3, SRC, STAT3, TLR4, TP53, and RELA, which were often interconnected. Molecular docking revealed quercetin's strong binding affinity with CTNNB1, MAPK1, MAPK3, SRC, STAT3, TLR4, and TP53, consistent with HPLC analysis. In vivo experiments suggested that YEF has the potential to alleviate UC symptoms and protect the intestinal mucosal barrier by inhibiting the RhoA/ROCK pathway.

CONCLUSION

YEF may safeguard the intestinal mucosal barrier in UC by targeting CTNNB1, MAPK1, MAPK3, SRC, STAT3, TLR4, and TP53, while blocking the RhoA/ROCK pathway.

Exploring the Mechanism of Zilongjin in Treating Lung Adenocarcinoma Based on Network Pharmacology Combined with Experimental Verification

Zilongjin (ZLJ) is a common traditional Chinese medicine for lung adenocarcinoma (LUAD) treatment. However, its mechanisms of action remain to be elucidated. Network pharmacology was used to explore the underlying mechanisms of ZLJ on LUAD treatment. The disease-related targets were determined from the Gene-Cards and DisGeNET databases. Active compounds and targets of ZLJ were obtained from the HIT, TCMSP, and TCMID databases. Then the protein-protein interaction (PPI) network was built by the STRING database to identify core-hub targets of ZLJ in LUAD. Next, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were employed to analyze the enriched regulatory pathways of targets. Molecular docking analysis was used to evaluate interactions between potential targets and active compounds. Finally, qRT-PCR was used to further verify the results of network pharmacology. A total of 124 LUAD-related targets of ZLJ and 5 active compounds of ZLJ from the relevant databases were screened out. Among these target proteins, JUN, CDH1, PPARG, and FOS were core hub-genes in the PPI network. GO and KEGG pathway enrichment analysis indicated that these targets might regulate the PPAR signaling pathway in LUAD. JUN, PPARG, and FOS levels were upregulated, while CDH1 level was downregulated in LUAD cells. This study discerned that ZLJ may target genes such as JUN, FOS, PPARG, and CDH1 via the PPAR signaling pathway in LUAD, offering foundational insights for further exploration of ZLJ in clinical applications.

The Potential Mechanisms of Qufeng Zhitong Capsule against Rheumatoid Arthritis Based on Network Pharmacology and In Vitro Experiments

Qufeng Zhitong capsule (QFZTC) is a traditional Chinese herbal formula with potential therapeutic efficacy in rheumatoid arthritis (RA). This study seeks to clarify the potential effects and mechanisms of QFZTC against RA. Active compounds and targets of QFZTC were retrieved from the Herbal Ingredients' Targets (HIT), Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), and Traditional Chinese Medicine Integrated Database (TCMID) databases. RA-related targets were searched on GeneCards and DisGeNET databases. Protein-protein interaction (PPI) network was established using the STRING database. Gene ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) enrichment analyses were performed on hub targets. Molecular docking was conducted on hub targets and active compounds. High-performance liquid chromatography (HPLC) was applied to characterize the active compounds in QFZTC. RA-fibroblast like synoviocytes (RA-FLSs) were cultured and treated by QFZTC-containing serum, in which proinflammatory cytokines and hub targets were detected. Cell viability was determined by cell counting kit-8 (CCK-8) assay. A total of 360 active compounds and 445 potential targets are identified for QFZTC against RA. Protein-protein interaction (PPI) network determined five hub targets, interleukin 6 (IL6), IL1B, VEGFA, JUN, and tumor necrosis factor (TNF). GO and KEGG analyses revealed that the MAPK pathway may be a critical signaling in QFZTC treating RA. Molecular docking showed that luteolin, kaempferol, and myricetin has good affinity with TNF, and they were identified by HPLC. In vitro experiments confirmed that QFZTC restrained the cell viability and inflammation in RA. This study revealed the active compounds and molecular targets for QFZTC treating RA. QFZTC is a promising drug and ameliorates RA by inhibiting inflammatory response.

Mechanism Study of Polydatin in Treating Spinal Cord Injury by Modulating Mitochondrial Membrane Potential Based on Network Pharmacology and Molecular Docking

Spinal cord injury (SCI) is one of the most devastating central lesions, and mitochondrial function plays an important role in secondary injury after SCI. Polydatin (PD) is a natural glycosylated precursor of resveratrol, showing mitochondrial preservation effects in the central nervous system. This study aimed to identify the hub target genes of PD on mitochondrial membrane potential (MMP) in SCI. A comprehensive analysis was performed on SCI-related genes, MMP-related genes, and PD targets screening from public databases. Differential expression analysis was conducted to identify differentially expressed genes (DEGs) in SCI. Gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were employed to assess pathway enrichment. Protein-protein interaction (PPI) network analysis and molecular docking were conducted to identify key genes and evaluate the binding affinity between PD and hub genes. A total of 16,958 SCI-related genes, 2,786 MMP-related genes, 318 PD-related target genes, and 7229 DEGs were identified. Intersection analysis revealed 46 genes common to all four categories. GSEA and GSVA analysis identified significant enrichment of pathways associated with suppressed and activated SCI biological processes. The PPI network analysis identified seven core hub genes: EGFR, SRC, VEGFA, STAT3, ERBB2, TP53, and RHOA. Molecular docking revealed strong binding affinities between PD and ERBB2, EGFR, and RHOA. The findings based on computational investigation from public databases suggest that PD may have therapeutic potential for SCI by modulating MMP. These results contribute to the understanding of SCI pathogenesis and the development of novel therapeutic strategies.

Molecular Mechanisms of Medicinal Plant Securinega suffruticosa-derived Compound Securinine against Spinal Muscular Atrophy based on Network Pharmacology and Experimental Verification

BACKGROUND

Spinal Muscular Atrophy (SMA) is a severe motor neuronal disorder with high morbidity and mortality. Securinine has shown the potential to treat SMA; however, its anti-SMA role remains unclear.

OBJECTIVE

This study aims to reveal the anti-SMA mechanisms of securinine.

METHODS

Securinine-associated targets were acquired from Herbal Ingredients' Targets (HIT), Similarity Ensemble Approach (SEA), and SuperPred. SMA-associated targets were obtained from GeneCards and Dis- GeNET. Protein-protein Interaction (PPI) network was constructed using GeneMANIA, and hug targets were screened using cytoHubba. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed using ClusterProfifiler. Molecular docking was conducted using Pymol and Auto- Dock. In vitro assays were used to verify the anti-SMA effects of securinine.

RESULTS

Twenty-six intersection targets of securinine and SMA were obtained. HDAC1, HDAC2, TOP2A, PIK3R1, PRMT5, JAK2, HSP90AB1, TERT, PTGS2, and PAX8 were the core targets in PPI network. GO analysis demonstrated that the intersecting targets were implicated in the regulation of proteins, steroid hormones, histone deacetylases, and DNA transcription. KEGG analysis, pathway-pathway, and hub target-pathway networks revealed that securinine might treat SMA through TNF, JAK-STAT, Ras, and PI3K-Akt pathways. Securinine had a favorable binding affinity with HDAC1, HSP90AB, JAK2, PRMT5, PTGS2, and TERT. Securinine rescued viability suppression, mitochondria damage, and SMN loss in the SMA cell model. Furthermore, securinine increased HDAC1 and PRMT5 expression, decreased PTGS2 expression, suppressed the JAK2-STAT3 pathway, and promoted the PI3K-Akt pathway.

CONCLUSION

Securinine might alleviate SMA by elevating HDAC1 and PRMT5 expression and reducing PTGS2 via JAK2-STAT3 suppression and PI3K-Akt activation.

Compound-composed Chinese medicine of Huachansu triggers apoptosis of gastric cancer cells through increase of reactive oxygen species levels and suppression of proteasome activities

BACKGROUND

Huachansu (HCS), a known Chinese patent drug extracted from the Chinese toad skin, is frequently used for the treatment of various advanced cancers, especially gastric cancer, due to the good therapeutic effect. However, it is rather difficult to clarify the active substances and molecular mechanisms involved owing to the lack of appropriate research strategies. We recently proposed the concept and research ideas of compound-composed Chinese medicine formula.

PURPOSE

To discover compound-composed Chinese medicine from Huachansu and to explore its mechanism of action in inducing apoptosis of gastric cancer cells.

METHOD

Network pharmacology combined with serum pharmacochemistry was utilized to screen the predominant active constituents from HCS against gastric cancer. Then, the compound-composed Chinese medicine of HCS (CCMH) was prepared according to their relative contents in serum. The pharmacological effects and potential mechanisms for CCMH were investigated by assays for cell viability, cell cycle, apoptosis, mitochondrial membrane potential (MMP), proteomics, reactive oxygen species (ROS), N-Acetylcysteine (NAC) antagonism, proteasome activity, and western blot.

RESULTS

CCMH was comprised of arenobufagin (11.14%), bufalin (18.67%), bufotalin (7.33%), cinobufagin (16.67%), cinobufotalin (16.74%), gamabufotalin (8.45%), resibufogenin (12.03%), and telocinobufagin (8.97%). CCMH evidently induced proliferation inhibition, cell cycle arrest, apoptosis, and MMP collapse in gastric cancer cells, possessing the better activities than HCS. Proteomic analysis showed that CCMH influenced ROS pathway, ubiquitin proteasome system, and PI3K/Akt and MAPK signaling pathways. CCMH markedly enhanced intracellular ROS levels in gastric cancer cells, which was reversed by NAC. Accordingly, NAC antagonized the apoptosis-inducing effect of CCMH. Significantly decreased proteasome 20S activity by CCMH was observed in gastric cancer cells. CCMH also regulated the expression of key proteins in PI3K/Akt and MAPK signaling pathways.

CONCLUSION

CCMH possesses more significant apoptotic induction effects on gastric cancer cells than HCS, which is achieved primarily through suppression of proteasome activities and increase of ROS levels, followed by regulating PI3K/Akt and MAPK signaling pathways. Network pharmacology combined with serum pharmacochemistry is an effective strategy for discovering compound-composed Chinese medicine from traditional Chinese medicine, which can help clarify the pharmacological substances and mechanisms of action for traditional Chinese medicine.

Network Proximity Analysis Deciphers the Pharmacological Mechanism of Osthole against D-Galactose Induced Cognitive Disorder in Rats

Osthole, a natural coumarin found in various medicinal plants, has been previously reported to have neuroprotective effects. However, the specific mechanism by which Osthole alleviates dysmnesia associated with Alzheimer's disease (AD) remains unclear. This study aimed to investigate the neuroprotective properties of Osthole against cognitive impairment in rats induced by D-galactose and elucidate its pharmacological mechanism. The rat model was established by subcutaneously injecting D-galactose at a dose of 150 mg/kg/day for 56 days. The effect of Osthole on cognitive impairment was evaluated by behavior and biochemical analysis. Subsequently, a combination of in silico prediction and experimental validation was performed to verify the network-based predictions, using western blot, Nissl staining, and immunofluorescence. The results demonstrate that Osthole could improve memory dysfunction induced by D-galactose in Sprague Dawley male rats. A network proximity-based approach and integrated pathways analysis highlight two key AD-related pathological processes that may be regulated by Osthole, including neuronal apoptosis, i.e., neuroinflammation. Among them, the pro-apoptotic markers (Bax), anti-apoptotic protein (Bcl-2), the microgliosis (Iba-1), Astro-cytosis (GFAP), and inflammatory cytokines (TNF-R1) were evaluated in both hippocampus and cortex. The results indicated that Osthole significantly ameliorated neuronal apoptosis and neuroinflammation in D-galactose-induced cognitive impairment rats. In conclusion, this study sheds light on the pharmacological mechanism of Osthole in mitigating D-galactose-induced memory impairment and identifies Osthole as a potential drug candidate for AD treatment, targeting multiple signaling pathways through network proximity and integrated pathways analysis.

Identifying the natural products in the treatment of atherosclerosis by increasing HDL-C level based on bioinformatics analysis, molecular docking, and in vitro experiment

BACKGROUND

Previous studies have demonstrated that high-density lipoprotein cholesterol (HDL-C) plays an anti-atherosclerosis role through reverse cholesterol transport. Several studies have validated the efficacy and safety of natural products in treating atherosclerosis (AS). However, the study of raising HDL-C levels through natural products to treat AS still needs to be explored.

METHODS

The gene sets associated with AS were collected and identified by differential gene analysis and database query. By constructing a protein-protein interaction (PPI) network, the core submodules in the network are screened out. At the same time, by calculating node importance (Nim) in the PPI network of AS disease and combining it with Kyoto Encyclopedia of genes and genomes (KEGG) pathways enrichment analysis, the key target proteins of AS were obtained. Molecular docking is used to screen out small natural drug molecules with potential therapeutic effects. By constructing an in vitro foam cell model, the effects of small molecules on lipid metabolism and key target expression of foam cells were investigated.

RESULTS

By differential gene analysis, 451 differential genes were obtained, and a total of 313 disease genes were obtained from 6 kind of databases, then 758 AS-related genes were obtained. The enrichment analysis of the KEGG pathway showed that the enhancement of HDL-C level against AS was related to Lipid and atherosclerosis, Cholesterol metabolism, Fluid shear stress and atherosclerosis, PPAR signaling pathway, and other pathways. Then we intersected 31 genes in the core module of the PPI network, the top 30 genes in Nims, and 32 genes in the cholesterol metabolism pathway, and finally found 3 genes. After the above analysis and literature collection, we focused on the following three related gene targets: APOA1, LIPC, and CETP. Molecular docking showed that Genistein has a good binding affinity for APOA1, CETP, and LIPC. In vitro, experiments showed that Genistein can up-regulated APOA1, LIPC, and CETP levels.

CONCLUSIONS

Based on our research, Genistein may have the effects of regulating HDL-C and anti-atherosclerosis. Its mechanism of action may be related to the regulation of LIPC, CETP, and APOA1 to improve lipid metabolism.

ccTCM: A quantitative component and compound platform for promoting the research of traditional Chinese medicine

Traditional Chinese medicine (TCM) databases play a vital role in bridging the gap between TCM and modern medicine, as well as in promoting the popularity of TCM. Elucidating the bioactive ingredients of Chinese medicinal materials is key to TCM modernization and new drug discovery. However, one drawback of current TCM databases is the lack of quantitative data on the constituents of Chinese medicinal materials. Herein, we present ccTCM, a web-based platform designed to provide a component and compound-content-based resource on TCM and analysis services for medical experts. In terms of design features, ccTCM combines resource distribution, similarity analysis, and molecular-mechanism analysis to accelerate the discovery of bioactive ingredients in TCM. ccTCM contains 273 Chinese medicinal materials commonly used in clinical settings, covering 29 functional classifications. By searching and comparing, we finally adopted 2043 studies, from which we collected the compounds contained in each TCM with content greater than 0.001 %, and a total of 1449 were extracted. Subsequently, we collected 40,767 compound-target pairs by integrating multiple databases. Taken together, ccTCM is a versatile platform that can be used by TCM scientists to perform scientific and clinical TCM studies based on quantified ingredients of Chinese medicinal materials. ccTCM is freely accessible at http://www.cctcm.org.cn.

Multi-level advances in databases related to systems pharmacology in traditional Chinese medicine: a 60-year review

The therapeutic effects of traditional Chinese medicine (TCM) involve intricate interactions among multiple components and targets. Currently, computational approaches play a pivotal role in simulating various pharmacological processes of TCM. The application of network analysis in TCM research has provided an effective means to explain the pharmacological mechanisms underlying the actions of herbs or formulas through the lens of biological network analysis. Along with the advances of network analysis, computational science has coalesced around the core chain of TCM research: formula-herb-component-target-phenotype-ZHENG, facilitating the accumulation and organization of the extensive TCM-related data and the establishment of relevant databases. Nonetheless, recent years have witnessed a tendency toward homogeneity in the development and application of these databases. Advancements in computational technologies, including deep learning and foundation model, have propelled the exploration and modeling of intricate systems into a new phase, potentially heralding a new era. This review aims to delves into the progress made in databases related to six key entities: formula, herb, component, target, phenotype, and ZHENG. Systematically discussions on the commonalities and disparities among various database types were presented. In addition, the review raised the issue of research bottleneck in TCM computational pharmacology and envisions the forthcoming directions of computational research within the realm of TCM.

Network pharmacology combined with molecular docking and experimental verification to elucidate functional mechanism of Fufang Zhenzhu Tiaozhi against type 2 diabetes mellitus

Fufang Zhenzhu Tiaozhi (FTZ) capsules have been prescribed for treating glucose and lipid metabolism disorders such as type 2 diabetes mellitus (T2DM). However, the underlying mechanism remains unknown. In this study, network pharmacology and experimental verification were combined to investigate the mechanisms of FTZ in treating T2DM. A total of 176 active ingredients and 1169 corresponding targets were screened using biological databases. 598 potential targets of T2DM were retrieved from GeneCards, PharmGKB, OMIM, Drugbank, and TTD. The Venn diagram was employed to identify the 194 intersection targets, which were employed to construct the "Herb-Compound-Target" interacting networks. These common targets were also used to prepare a protein-protein interaction (PPI) network to uncover potential targets. The four core targets were docked to their corresponding targets for binding analysis. Additionally, the top-ranked poses of ingredients and the positive compounds from each protein were evaluated for stability using molecular dynamics. Our results suggest that core active ingredients such as kaempferol, luteolin, and baicalein have high binding affinity and stability with AKT1, PTGS2 (also known as COX-2), DPP4, and PAPRG. GO and KEGG analyses indicated that the treatment T2DM by FTZ might be related to different pathway like AMPK and EGFR pathways. The experimental validation results proved that kaempferol, luteolin, and baicalein could significantly inhibit the activity of DPP4 and COX-2, kaempferol and luteolin were also able to activate AKT and AMPK signaling pathway. This study further validated previous findings and enhanced our understanding of the potential effects of FTZ on T2DM.Communicated by Ramaswamy H. Sarma.

Network medicine framework reveals generic herb-symptom effectiveness of traditional Chinese medicine

Understanding natural and traditional medicine can lead to world-changing drug discoveries. Despite the therapeutic effectiveness of individual herbs, traditional Chinese medicine (TCM) lacks a scientific foundation and is often considered a myth. In this study, we establish a network medicine framework and reveal the general TCM treatment principle as the topological relationship between disease symptoms and TCM herb targets on the human protein interactome. We find that proteins associated with a symptom form a network module, and the network proximity of an herb's targets to a symptom module is predictive of the herb's effectiveness in treating the symptom. These findings are validated using patient data from a hospital. We highlight the translational value of our framework by predicting herb-symptom treatments with therapeutic potential. Our network medicine framework reveals the scientific foundation of TCM and establishes a paradigm for understanding the molecular basis of natural medicine and predicting disease treatments.

Effect of Shan Zha (Hawthorn or Crataegus) on gastrointestinal cancer: A network pharmacology and molecular docking study

Background

Shan Zha (Hawthorn or Crataegus) is a traditional Chinese medicine (TCM) most commonly used for the treatment of hyperlipidemia. Gastrointestinal cancer is closely correlated with blood lipid levels. This study illustrates the potential anticancer effects of Shan Zha on gastrointestinal tumors based on network pharmacology and molecular docking.

Methods

Hawthorn's bioactive ingredients and drug targets were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), Integrative Pharmacology-based Research Platform of Traditional Chinese Medicine version 2.0 (TCMIP v2.0), and Herbal Ingredients' Targets Platform (HIT 2.0) databases. Validated disease targets of gastrointestinal cancer were obtained from the Therapeutic Targets Database (TTD) and HIT 2.0 databases. Protein-protein interaction analysis of intersecting genes was performed using the Search Tool for the Retrieval of Interacting Genes (STRING) database. The functions of these genes were further analyzed by performing gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Molecular docking verification was performed using Molecular Operating Environment (MOE) software.

Results

Four main bioactive components were identified in Shan Zha. A total of 271 potential drug targets were identified, and 393 gastrointestinal-tumor targets were obtained. Through protein interaction analysis of intersecting targets, the main components of Shan Zha were found to interact more closely with proteins such as tumor protein p53 (TP53), AKT serine/threonine kinase 1 (AKT1), JUN proto-oncogene (JUN), interleukin 6 (IL6), epidermal growth factor receptor (EGFR), and vascular endothelial growth factor A (VEGFA). KEGG pathway enrichment analysis showed a total of 127 pathways, mainly involving pathways in multiple types of cancer, the Phosphatidylinositol 3-kinase-Akt (PI3K-Akt) signaling pathway, and EGFR tyrosine kinase inhibitor resistance. Combined with The Cancer Genome Atlas (TCGA) differential analysis, key targets, including TP53, cyclin D1 (CCND1), EGFR, and VEGFA, were screened. Molecular docking results showed that quercetin and kaempferol had the good binding potential for TP53, CCND1, EGFR, and VEGFA.

Conclusion

These findings suggest that Shan Zha exerts its effects on gastrointestinal cancers through a multitarget, multi-component, and a multi-pathway mechanism.

Integrated network pharmacology, bioinformatics, and molecular docking to explore the mechanisms of berberine regulating autophagy in breast cancer

Berberine exhibits anticancer efficacy against a variety of malignancies, including breast cancer (BRCA). However, the underlying mechanism is ambiguous. This study sought to explore the targets and the probable mechanism of berberine regulating autophagy in BRCA through network pharmacology, bioinformatics, and molecular docking. The targets of berberine and autophagy-modulated genes were derived from online databases, and the Cancer Genome Atlas database was used to identify the differentially expressed genes of BRCA. Then, through intersections, the autophagy-modulated genes regulated by berberine (AMGRBs) in BRCA were obtained. Next, we established a protein-protein interaction network using the Search Tool for the Retrieval of Interacting Genes database. Afterward, gene ontology and Kyoto encyclopedia of genes and genomes enrichment analyses were employed to explore the targets' biological functions. Additionally, molecular docking was conducted to verify the binding ability of berberine to the targets. Finally, to determine the prognostic value of AMGRBs in BRCA, we performed overall survival analyses. We identified 29 AMGRBs in BRCA, including CASP3, MTOR, AKT1, GSK3B, PIK3CA, and others. Gene ontology enrichment analysis showed that the AMGRBs in BRCA were associated with autophagy regulation, negative regulation of catabolic process, macroautophagy, and other biological processes. Kyoto encyclopedia of genes and genomes enrichment analyses indicated that AMGRBs in BRCA were involved in epidermal growth factor receptor tyrosine kinase inhibitor resistance, PI3K/Akt signaling pathway, JAK-STAT signaling pathway, and others. Molecular docking results proved that berberine had strong binding affinities with AMGRBs in BRCA. Survival analyses indicated that ATM, HTR2B, LRRK2, PIK3CA, CDK5, and IFNG were associated with the prognosis of BRCA. This study identified the targets and pathways of berberine for regulating autophagy in BRCA, which contributed to a better understanding of berberine's function in BRCA and serve as a foundation and reference for further study and therapeutic application of berberine.

Integrating animal experiments, mass spectrometry and network-based approach to reveal the sleep-improving effects of Ziziphi Spinosae Semen and γ-aminobutyric acid mixture

BACKGROUND

Ziziphi Spinosae Semen (ZSS) is a plant widely used as medicine and food in Asian countries due to its numerous health benefits. γ-aminobutyric acid (GABA), a non-proteinaceous amino acid, is one of the major inhibitory neurotransmitters with a relaxant function. In this study, a system pharmacology approach was employed to assess the effects of a mixture composed of ZSS and GABA (ZSSG) on sleep improvement.

METHODS

Mice were divided into five groups (n = 10) and received either no treatment, sodium pentobarbital, or sodium barbital with diazepam or ZSSG. The effects of ZSSG on sleep quality were evaluated in mice, and differential metabolites associated with sleep were identified among the control, ZSS, GABA, and ZSSG groups. Additionally, network-based ingredient-insomnia proximity analysis was applied to explore the major ingredients.

RESULTS

ZSSG significantly improved sleep quality by decreasing sleep latency and prolonging sleep duration in sodium pentobarbital-induced sleeping mouse model (P < 0.05). ZSSG significantly enhanced the brain content of GABA in mice. Furthermore, ZSSG also significantly decreased sleep latency-induced by sodium barbital in mice (P < 0.05). Metabolic analysis revealed significant differences in 10 metabolites between ZSSG group and the groups administering ZSS or GABA. Lastly, using the network-based ingredient screening model, we discovered potential four active ingredients and three pairwise ingredient combinations with synergistic effect on insomnia from ZSSG among 85 ingredients identified by UPLC-Q/TOF-MS. Also, we have constructed an online computation platform.

CONCLUSION

Our data demonstrated that ZSSG improved the sleeping quality of mice and helped to balance metabolic disorders-associated with sleep disorders. Moreover, based on the network-based prediction method, the four potential active ingredients in ZSSG could serve as quality markers-associated with insomnia. The network-based framework may open up a new avenue for the discovery of active ingredients of herbal medicine for treating complex chronic diseases or symptoms, such as insomnia.

Identifying target organ location of Radix Achyranthis Bidentatae: a bioinformatics approach on active compounds and genes

Background: Herbal medicines traditionally target organs for treatment based on medicinal properties, and this theory is widely used for prescriptions. However, the scientific evidence explaining how herbs act on specific organs by biological methods has been still limited. This study used bioinformatic tools to identify the target organ locations of Radix Achyranthis Bidentatae (RAB), a blood-activating herb that nourishes the liver and kidney, strengthens bones, and directs prescription to the lower body. Methods: RAB's active compounds and targets were collected and predicted using databases such as TCMSP, HIT2.0, and BATMAN-TCM. Next, the RAB's target list was analyzed based on two approaches to obtain target organ locations. DAVID and Gene ORGANizer enrichment-based approaches were used to enrich an entire gene list, and the BioGPS and HPA gene expression-based approaches were used to analyze the expression of core genes. Results: RAB's targets were found to be involved in whole blood, blood components, and lymphatic organs across all four tools. Each tool indicated a particular aspect of RAB's target organ locations: DAVID-enriched genes showed a predominance in blood, liver, and kidneys; Gene ORGANizer showed the effect on low body parts as well as bones and joints; BioGPS and HPA showed high gene expression in bone marrow, lymphoid tissue, and smooth muscle. Conclusion: Our bioinformatics-based target organ location prediction can serve as a modern interpretation tool for the target organ location theory of traditional medicine. Future studies should predict therapeutic target organ locations in complex prescriptions rather than single herbs and conduct experiments to verify predictions.

Comprehensive survey of target prediction web servers for Traditional Chinese Medicine

Traditional Chinese medicine (TCM) is characterized by multi-components, multiple targets, and complex mechanisms of action and therefore has significant advantages in treating diseases. However, the clinical application of TCM prescriptions is limited due to the difficulty in elucidating the effective substances and the lack of current scientific evidence on the mechanisms of action. In recent years, the development of network pharmacology based on drug systems research has provided a new approach for understanding the complex systems represented by TCM. The determination of drug targets is the core of TCM network pharmacology research. Over the past years, many web tools for drug targets with various features have been developed to facilitate target prediction, significantly promoting drug discovery. Therefore, this review introduces the widely used web tools for compound-target interaction prediction databases and web resources in TCM pharmacology research, and it compares and analyzes each web tool based on their basic properties, including the underlying theory, algorithms, datasets, and search results. Finally, we present the remaining challenges for the promising future of compound-target interaction prediction in TCM pharmacology research. This work may guide researchers in choosing web tools for target prediction and may also help develop more TCM tools based on these existing resources.

Systems pharmacology-based mechanism exploration of Acanthopanax senticosusin for Alzheimer's disease using UPLC-Q-TOF-MS, network analysis, and experimental validation

BACKGROUND

Alzheimer's disease (AD) is a neurodegenerative disease, characterized by progressive cognitive dysfunction and memory loss. However, the disease-modifying treatments for AD are still lacking. Traditional Chinese herbs, have shown their potentials as novel treatments for complex diseases, such as AD.

PURPOSE

This study was aimed at investigating the mechanism of action (MOA) of Acanthopanax senticosusin (AS) for treatment of AD.

METHODS

In this study, we firstly identified the chemical constituents in Acanthopanax senticosusin (AS) utilizing ultra-high performance liquid chromatography coupled with Q-TOF-mass spectrometry (UPLC-Q-TOF-MS), and next built the drug-target network of these compounds. We next performed the systems pharmacology-based analysis to preliminary explore the MOA of AS against AD. Moreover, we applied the network proximity approach to identify the potential anti-AD components in AS. Finally, experimental validations, including animal behavior test, ELISA and TUNEL staining, were conducted to verify our systems pharmacology-based analysis.

RESULTS

60 chemical constituents in AS were identified via the UPLC-Q-TOF-MS approach. The systems pharmacology-based analysis indicated that AS might exert its therapeutic effects on AD via acetylcholinesterase and apoptosis signaling pathway. To explore the material basis of AS against AD, we further identified 15 potential anti-AD components in AS. Consistently, in vivo experiments demonstrated that AS could protect cholinergic nervous system damage and decrease neuronal apoptosis caused by scopolamine.

CONCLUSION

Overall, this study applied systems pharmacology approach, via UPLC-Q-TOF-MS, network analysis, and experimental validation to decipher the potential molecular mechanism of AS against AD.

Network pharmacology, a promising approach to reveal the pharmacology mechanism of Chinese medicine formula

ETHNOPHARMACOLOGICAL RELEVANCE

Network pharmacology is a new discipline based on systems biology theory, biological system network analysis, and multi-target drug molecule design specific signal node selection. The mechanism of action of TCM formula has the characteristics of multiple targets and levels. The mechanism is similar to the integrity, systematization and comprehensiveness of network pharmacology, so network pharmacology is suitable for the study of the pharmacological mechanism of Chinese medicine compounds.

AIM OF THE STUDY

The paper summarizes the present application status and existing problems of network pharmacology in the field of Chinese medicine formula, and formulates the research ideas, up-to-date key technology and application method and strategy of network pharmacology. Its purpose is to provide guidance and reference for using network pharmacology to reveal the modern scientific connotation of Chinese medicine.

MATERIALS AND METHODS

Literatures in this review were searched in PubMed, China National Knowledge Infrastructure (CNKI), Web of Science, ScienceDirect and Google Scholar using the keywords "traditional Chinese medicine", "Chinese herb medicine" and "network pharmacology". The literature cited in this review dates from 2002 to 2022.

RESULTS

Using network pharmacology methods to predict the basis and mechanism of pharmacodynamic substances of traditional Chinese medicines has become a trend.

CONCLUSION

Network pharmacology is a promising approach to reveal the pharmacology mechanism of Chinese medicine formula.

Discovering Potential Anti-Oral Squamous Cell Carcinoma Mechanisms from Kochiae Fructus Using Network-Based Pharmacology Analysis and Experimental Validation

The natural product Kochiae Fructus (KF) is the ripe fruit of Kochia scoparia (L.) Schrad and is renowned for its anti-inflammatory, anticancer, anti-fungal, and anti-pruritic effects. This study examined the anticancer effect of components of KF to assess its potential as an adjuvant for cancer treatment. Network-based pharmacological and docking analyses of KF found associations with oral squamous cell carcinoma. The molecular docking of oleanolic acid (OA) with LC3 and SQSTM1 had high binding scores, and hydrogen binding with amino acids of the receptors suggests that OA is involved in autophagy, rather than the apoptosis pathway. For experimental validation, we exposed SCC-15 squamous carcinoma cells derived from a human tongue lesion to KF extract (KFE), OA, and cisplatin. The KFE caused SCC-15 cell death, and induced an accumulation of the autophagy marker proteins LC3 and p62/SQSTM1. The novelty of this study lies in the discovery that the change in autophagy protein levels can be related to the regulatory death of SCC-15 cells. These findings suggest that KF is a promising candidate for future studies to provide insight into the role of autophagy in cancer cells and advance our understanding of cancer prevention and treatment.

Therapeutic effects and mechanisms of Ku-Gan formula on atopic dermatitis: A pilot clinical study and modular pharmacology analysis with animal validation

ETHNOPHARMACOLOGICAL RELEVANCE

Atopic dermatitis (AD) is a persistent, recurrent inflammatory skin disorder with a rapid upward trend worldwide. The first-line treatment for AD consists of topical medicines such as topical corticosteroids (TCSs). However, long-term use of conventional topical medicine results in side effects and recurrence, presenting therapeutic challenges for the management of AD. Ku-Gan formula (KG) has been extensively used to treat skin diseases since the Song dynasty. In particular, topical administration of the KG alleviates the cutaneous symptoms of AD and reduces recurrence rates with a good safety profile; however, the mechanisms of the KG's action remain unknown.

AIM OF THE STUDY

The current study aimed to evaluate the efficacy and safety of KG in AD patients and to investigate the molecular mechanisms that underlie the efficacy of KG in the treatment of AD.

MATERIALS AND METHODS

A single-arm prospective pilot study with historical controls was conducted. This study evaluated 11 patients with mild to moderate AD, who underwent topical KG treatment. The primary outcome was the change in local eczema area and severity index (EASI) scores. The secondary outcomes included the recurrence rate and safety. The recurrence rate were compared to those of a matched historical control group. Secondly, modular pharmacology analysis was used to elucidate the therapeutic mechanism of KG in AD treatment by identifying the hub genes and kernel pathways. Moreover, we evaluated treatment effects and verified modular pharmacology-based findings using the calcipotriol (MC903)-induced mouse model and bioinformatics analysis.

RESULTS

Our clinical pilot study demonstrated that the KG wet wrapping could effectively ameliorate skin lesions in AD patients with a significant drop from 4.18 to 1.63 in local EASI. Compared to the historical controls, KG had a reduced recurrence rate (36%) and a longer median time to relapse (>12 weeks). Modular pharmacology analysis identified the hub genes including IL6, IL1B, VEGFA, STAT3, JUN, TIMP1 and ARG1, and kernel pathway including IL-17 signaling pathway of KG. Pharmacodynamic results suggested that KG ameliorated skin symptoms and demonstrated no less efficacy than halcinonide (HC) in MC903-induced AD-like mice. In addition, KG regulated the mRNA expression of hub genes as well as the related genes involved in IL-17 signaling pathway including Il25, Il17a,Traf3ip2, and Traf6, in skin lesions of AD-like mice.

CONCLUSION

These results showed that KG is a safe and effective topical treatment for AD with low recurrence. In addition, our study identified potential molecular pathways and therapeutic candidate targets of the KG formula, providing evidence for its clinical applicability in AD.

Network pharmacology approaches for research of Traditional Chinese Medicines

Pharmacodynamics material basis and effective mechanisms are the two main issues to decipher the mechnisms of action of Traditional Chinese medicines (TCMs) for the treatment of diseases. TCMs, in "multi-component, multi-target, multi-pathway" paradigm, show satisfactory clinical results in complex diseases. New ideas and methods are urgently needed to explain the complex interactions between TCMs and diseases. Network pharmacology (NP) provides a novel paradigm to uncover and visualize the underlying interaction networks of TCMs against multifactorial diseases. The development and application of NP has promoted the safety, efficacy, and mechanism investigations of TCMs, which then reinforces the credibility and popularity of TCMs. The current organ-centricity of medicine and the "one disease-one target-one drug" dogma obstruct the understanding of complex diseases and the development of effective drugs. Therefore, more attentions should be paid to shift from "phenotype and symptom" to "endotype and cause" in understanding and redefining current diseases. In the past two decades, with the advent of advanced and intelligent technologies (such as metabolomics, proteomics, transcriptomics, single-cell omics, and artificial intelligence), NP has been improved and deeply implemented, and presented its great value and potential as the next drug-discovery paradigm. NP is developed to cure causal mechanisms instead of treating symptoms. This review briefly summarizes the recent research progress on NP application in TCMs for efficacy research, mechanism elucidation, target prediction, safety evaluation, drug repurposing, and drug design.

Systematic Description of the Content Variation of Natural Products (NPs): To Prompt the Yield of High-Value NPs and the Discovery of New Therapeutics

Natural products (NPs) have long been associated with human production and play a key role in the survival of species. Significant variations in NP content may severely affect the "return on investment" of NP-based industries and render ecological systems vulnerable. Thus, it is crucial to construct a platform that relates variations in NP content to their corresponding mechanisms. In this study, a publicly accessible online platform, NPcVar (http://npcvar.idrblab.net/), was developed, which systematically described the variations of NP contents and their corresponding mechanisms. The platform comprises 2201 NPs and 694 biological resources, including plants, bacteria, and fungi, curated using 126 diverse factors with 26,425 records. Each record contains information about the species, NP, and factors involved, as well as NP content data, parts of the plant that produce NPs, the location of the experiment, and reference information. All factors were manually curated and categorized into 42 classes which belong to four mechanisms (molecular regulation, species factor, environmental condition, and combined factor). Additionally, the cross-links of species and NP to well-established databases and the visualization of NP content under various experimental conditions were provided. In conclusion, NPcVar is a valuable resource for understanding the relationship between species, factors, and NP contents and is anticipated to serve as a promising tool for improving the yield of high-value NPs and facilitating the development of new therapeutics.

A Network Pharmacology Method Combined with Molecular Docking Verification to Explore the Therapeutic Mechanisms Underlying Simiao Pill Herbal Medicine against Hyperuricemia

Objective

Hyperuricemia (HUA) is a common metabolic disease caused by disordered purine metabolism. We aim to reveal the mechanisms underlying the anti-HUA function of Simiao pill and provide therapeutic targets.

Methods

Simiao pill-related targets were obtained using Herbal Ingredients' Targets (HIT), Traditional Chinese Medicine Systems Pharmacology (TCMSP), and Traditional Chinese Medicine Integrated Database (TCMID). HUA-associated targets were retrieved from GeneCards, DisGeNET, and Therapeutic Targets Database (TTD). Protein-protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database, ggraph and igraph R packages. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed using ClusterProfiler. The top 10 core targets were identified through cytoHubba. Molecular docking was conducted using PyMOL and AutoDock high-performance liquid chromatograph (HPLC) analysis was performed to identify effective compounds of Simiao pill.

Results

Simiao pill-HUA target network contained 80 targets. The key targets were mainly involved in inflammatory responses. Insulin (INS), tumor necrosis factor (TNF), interleukin-6 (IL6), interleukin 1 beta (IL1B), vascular endothelial growth factor A (VEGFA), leptin (LEP), signal transducer and activator of transcription 3 (STAT3), C-C motif chemokine ligand 2 (CCL2), interleukin-10 (IL10), and toll like receptor 4 (TLR4) were the top 10 targets in the PPI network. GO analysis demonstrated the main implication of the targets in molecular responses, production, and metabolism. KEGG analysis revealed that Simiao pill might mitigate HUA through advanced glycation end-product- (AGE-) receptor for AGE- (RAGE-) and hypoxia-inducible factor-1- (HIF-1-) associated pathways. IL1B, IL6, IL10, TLR4, and TNF were finally determined as the promising targets of Simiao pill treating HUA. Through molecular docking and HPLC analysis, luteolin, quercetin, rutaecarpine, baicalin, and atractylenolide I were the main active compounds.

Conclusions

Simiao pill can mitigate HUA by restraining inflammation, mediating AGE-RAGE- and HIF-1-related pathways, and targeting IL1B, IL6, IL10, TLR4, and TNF.

Study of Therapeutic Mechanisms of Puerarin against Sepsis-Induced Myocardial Injury by Integrating Network Pharmacology, Bioinformatics Analysis, and Experimental Validation

Myocardial injury is the most prevalent and serious complication of sepsis. The potential of puerarin (Pue) to treat sepsis-induced myocardial injury (SIMI) has been recently reported. Nevertheless, the specific anti-SIMI mechanisms of Pue remain largely unclear. Integrating network pharmacology, bioinformatics analysis, and experimental validation, we aimed to clarify the anti-SIMI mechanisms of Pue, thereby furnishing novel therapeutic targets. Pue-associated targets were collected from HIT, GeneCards, SwissTargetPrediction, SuperPred, and CTD databases. SIMI-associated targets were acquired from GeneCards and DisGeNET. Differentially expressed genes (DEGs) were identified from GEO database. Potential anti-SIMI targets of Pue were determined using VennDiagram. ClusterProfiler was employed for GO and KEGG analyses. STRING database and Cytoscape were used for protein-protein interaction (PPI) network construction, and cytoHubba was used for hub target screening. PyMOL and AutoDock were utilized for molecular docking. An in vitro SIMI model was built to further verify the therapeutic mechanisms of Pue. Seventy-three Pue-SIMI-DEG intersecting target genes were obtained. GO and KEGG analyses revealed that the targets were principally concentrated in cellular response to chemical stress, response to oxidative stress (OS), and insulin and neurotrophin signaling pathways. Through PPI analysis and molecular docking, AKT1, CASP3, TP53, and MAPK3 were identified as the pivotal targets. In vivo experiments indicated that Pue promoted cell proliferation, downregulated AKT1, CASP3, TP53, and MAPK3, and inhibited inflammation, myocardial injury, OS, and apoptosis in the cell model. Pue might inhibit inflammation, myocardial injury, OS, and apoptosis to treat SIMI by reducing AKT1, CASP3, TP53, and MAPK3.

Identification of Potential Targets and Mechanisms of Sinomenine in Allergic Rhinitis Treatment Based on Network Pharmacology and Molecular Docking

This study aimed to investigate the potential targets and molecular mechanism of sinomenine in treating allergic rhinitis (AR) using network pharmacology and molecular docking. Relevant targets of sinomenine and AR were obtained from public databases, and differentially expressed genes (DEGs) for AR were identified in the Gene Expression Omnibus database. Using VennDiagram, we identified 22 potential targets of sinomenine against AR by crossing disease targets, drug targets, and DEGs. Functional analysis revealed that sinomenine may act via its anti-inflammatory and immunosuppressive effects, and its action pathways may include the MAPK, HIF-1, and JAK-STAT pathways. Furthermore, hub targets were identified using EPC, MCC, and MNC algorithms, and six hub targets (STAT3, EGFR, NFKB1, HIF1A, PTGS2, and JAK1) were selected by integrating the top 10 hub genes and 22 potential targets. Molecular docking analysis indicated that STAT3, EGFR, PTGS2, and JAK1 may be key targets of sinomenine against AR. Overall, our results suggest that sinomenine has potential therapeutic effects against AR, and its mechanism of action may involve the regulation of key targets and pathways related to inflammation and immunity.