The organisational structure of protein networks: revisiting the centrality-lethality hypothesis

Screening study on significant Chinese herb for anti-idiopathic pulmonary fibrosis by combining clinical experience prescriptions and molecular dynamics simulation technologies

Various techniques such as data mining, network pharmacology, molecular docking and molecular dynamics simulation were used in this study to screen and validate effective herbal medicines for the treatment of idiopathic pulmonary fibrosis (IPF) and to reveal their mechanisms of action at the molecular level. The use of this approach will provide new tools and ideas for future drug screening, especially for the application of herbal medicines in the treatment of complex diseases. Among them, the five identified core targets, including IL6, TP53, AKT1, VEGFA, and TNF, as well as a series of major active compounds, will be important references for future anti-IPF drug development. This information will accelerate the discovery and development of relevant drugs. Meanwhile, this study further confirmed the potential value of four Chinese herbal medicines, including Gancao, Danshen, Huangqin, and Sanqi, in the treatment of IPF. This will promote more clinical trials and practices to confirm and optimise the application of these herbs. Finally, this study is an important theoretical guide to enhance the advantages of Chinese herbal medicines in the prevention and treatment of major and difficult diseases, as well as to understand and utilise the potential efficacy of Chinese herbal medicines. This will further promote the scientific research and clinical application of herbal medicines and provide more possibilities for future disease treatmentCommunicated by Ramaswamy H. Sarma.

To Investigate the Mechanism of Qinpi Tongfeng Formula in Treating Acute Gouty Arthritis by UHPLC-Q-Orbitrap-MS, Network Pharmacology and Experimental Validation

Background

Acute gouty arthritis (AGA) is characterized by the accumulation of monosodium urate crystals within the joints, leading to inflammation and severe pain. Western medicine treatments have limitations in addressing this condition. Previous studies have shown the efficacy of Qinpi Tongfeng formula (QPTFF) in treating AGA, but further investigation is needed to understand its mechanism of action.

Methods

We used ultra-high-performance liquid chromatography tandem Q-Exactive Orbitrap high-resolution mass spectrometry (UHPLC-Q-Orbitrap-MS) to identify compounds in QPTFF. Target proteins regulated by these compounds were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform, Chemistry Database, and Swiss Target Prediction Database. AGA-related targets were searched and screened from various databases, including Genecards, PharmGKB, Drugbank, etc. Intersection targets of QPTFF and AGA were analyzed for protein-protein interaction networks, GO function enrichment, and KEGG pathway enrichment. We then verified QPTFF's mechanism of action using an AGA rat model, assessing pathological changes via H&E staining and target expression via ELISA, RT-qPCR, and Western blot.

Results

UHPLC-Q-Orbitrap-MS identified 207 compounds in QPTFF, with 55 selected through network pharmacology. Of 589 compound-regulated targets and 1204 AGA-related targets, 183 potential targets were implicated in QPTFF's treatment of AGA. Main target proteins included IL-1β, NFKBIA, IL-6, TNF, CXCL8, and MMP9, with the IL-17 signaling pathway primarily regulated by QPTFF. Experimental results showed that medium and high doses of QPTFF significantly reduced serum inflammatory factors and MMP-9 expression, and inhibited IL-17A, IL-6, IKK-β, and NF-κB p65 mRNA and protein expression in AGA rats compared to the model group.

Conclusion

Key targets of QPTFF include IL-1β, NFKBIA, IL-6, TNF-α, CXCL8, and MMP9. QPTFF effectively alleviates joint inflammation in AGA rats, with high doses demonstrating no liver or kidney toxicity. Its anti-inflammatory mechanism in treating AGA involves the IL-17A/NF-κB p65 signaling pathway.

Network pharmacology analysis of Chandraprabha Vati: A new hope for the treatment of Metabolic Syndrome

BACKGROUND

Drug research is increasingly using Network Pharmacology (NP) to tackle complex conditions like Metabolic Syndrome (MetS), which is characterized by obesity, hyperglycemia, and dyslipidemia. Single-action drugs are inadequate to treat MetS, which is marked by a range of complications including glucose intolerance, hyperlipidemia, mitochondrial dysfunction, and inflammation.

OBJECTIVES

To analyze Chandraprabha vati using Network Pharmacology to assess its potential in alleviating MetS-related complications.

MATERIAL AND METHODS

The genes related to MetS, inflammation, and the target genes of the CPV components were identified using network pharmacology tools like DisgNET and BindingDB. Followed by mapping of the CPV target genes with the genes implicated in MetS and inflammation to identify putative potential targets. Gene ontology, pathway enrichment analysis, and STRING database were employed for further exploration. Furthermore, drug-target-protein interactions network were visualized using Cytoscape 3.9.1.

RESULTS

The results showed that out of the 225 target genes of the CPV components, 33 overlapping and 19 non-overlapping genes could be potential targets for MetS. Similarly, 14 overlapping and 7 non-overlapping genes could be potential targets for inflammation. The CPV bioactives target genes were found to be involved in lipid and insulin homeostasis via several pathways revealed by the pathway analysis. The importance of CPV in treating MetS was supported by GO enrichment data; this could be due to its potential to influence pathways linked to metabolism, ER stress, mitochondrial dysfunction, oxidative stress, and inflammation.

CONCLUSIONS

These results offer a promising approach to developing treatment and repurposing CPV for complex conditions such as MetS.

Mechanism of Smilax china L. in the treatment of intrauterine adhesions based on network pharmacology, molecular docking and experimental validation

BACKGROUND

Smilax china L. (SCL) is a traditional herbal medicine for the potential treatment of intrauterine adhesion (IUA). However, the mechanisms of action have not yet been determined. In this study, we explored the effects and mechanisms of SCL in IUA by network pharmacology, molecular docking and molecular biology experiments.

METHODS

Active ingredients and targets of SCL were acquired from TCMSP and SwissTargetPrediction. IUA-related targets were collected from the GeneCards, DisGeNET, OMIM and TTD databases. A protein‒protein interaction (PPI) network was constructed by Cytoscape 3.9.1 and analysed with CytoHubba and CytoNCA to identify the core targets. The DAVID tool was used for GO and KEGG enrichment analyses. Furthermore, molecular docking was employed to assess the interaction between the compounds and key targets. Finally, the mechanisms and targets of SCL in IUA were verified by cellular experiments and western blot.

RESULTS

A total of 196 targets of SCL were identified, among which 93 were related to IUA. Topological and KEGG analyses results identified 15 core targets that were involved in multiple pathways, such as inflammation, apoptosis, and PI3K/AKT signalling pathways. Molecular docking results showed that the active compounds had good binding to the core targets. In vitro experiments showed that astilbin (AST), a major component of SCL, significantly reduced TGF-β-induced overexpression of fibronectin (FN), activation of the PI3K/AKT signalling pathway and the expression of downstream factors (NF-κB and BCL2) in human endometrial stromal cells, suggesting that AST ameliorates IUA by mediating the PI3K/AKT/NF-κB and BCL2 proteins.

CONCLUSIONS

AST, a major component of SCL, may be a potential therapeutic agent for IUA. Moreover, its mechanism is strongly associated with regulation of the PI3K/AKT signalling pathway and the downstream NF-κB and BCL2 proteins. This study will provide new strategies that utilize AST for the treatment of IUA.

Elucidation of the mechanism of Zhenbao pills for the treatment of spinal cord injury by network pharmacology and molecular docking: A review

To explore the mechanism of the Zhenbao pill (ZBP) in treating spinal cord injury (SCI). The TCMSP Database, HERB Database and literature search were used to screen the effective ingredients and targets of ZBP; SCI-related genes were searched in GeneCards, OMIM, PharmGkb, TTD and DrugBank databases; the potential targets of ZBP for treating SCI were predicted and Venn diagrams were drawn, and the "herb-ingredient-target" network was constructed by Cytoscape software. The PPI network was constructed by STRING software, and the core targets were screened by cytoNCA plug-in; GO enrichment and KEGG pathway analysis were performed on the predicted targets using the DAVID Platform, and visualized with the Microbiology Network Platform. The molecular docking between the key ingredients and the core target was carried out by AutoDockVina software. 391 active ingredients and 836 action targets were obtained from ZBP and there are 1557 SCI related genes in 5 disease databases. The top 5 active ingredients were Quercetin, Camptothecin, Kaempferol, Ethyl iso-allocholate, and Ethyl linoleate, and 5 core genes were SRC, CTNNB1, TP53, AKT1, and STAT3. GO enrichment analysis showed that the core targets were involved in 1206 biological processes, 120 cellular components and 160 molecular functions; KEGG enrichment analysis showed that the core targets involved 183 pathways, including PI3K-Akt signaling pathway and other signaling pathways. Molecular docking indicated that CTNNB1, SRC, TP53, AKT1 and STAT3 showed good binding ability with the active ingredients quercetin, kaempferol and ethyl isobutyric acid. ZBP improves SCI through multi-components, multi-targets and multi-pathways.

A network pharmacology, molecular docking and in vitro investigation of Picrorhiza kurroa extract for the treatment of diabetic nephropathy

Picrorhiza kurroa Royle ex Benth. (P. kurroa/PK/Kutki), a Himalayan herb belonging to the family Scrophulariaceae, is widely known for its hepatoprotective activity. Traditionally, it is found to be effective for upper respiratory tract disorders, kidney and liver problems, dyspepsia and chronic diarrhoea but the mechanism of action is unclear. In this study, the mode of action of P. kurroa for the treatment of diabetic nephropathy (DN) was investigated by network pharmacology, molecular docking and in vitro assays. Numerous databases have been screened and 33 P. kurroa bioactive compounds and 56 targets were identified. The compounds-targets network, targets-pathways network and compounds-targets-pathways network were constructed. The major bioactive compounds include picrorhizaoside D, scrophuloside A, vanillic acid, arvenin I, cinnamic acid, picein, 6-feruloyl catalpol, picroside V, pikuroside, apocynin, picroside I, picroside IV, androsin, cucurbitacin P, boschnaloside, kutkoside, cucurbitacin O, cucurbitacin K, picracin, etc. The potential protein targets identified in this study were MMP1, PRKCA, MMP7, IL18, IL1, TNF, ACE, ASC, CASP1, NLRP3, MAP, KURROA1, mitogen-activated protein kinase (MAPK)14 and MAPK8. In the Database for annotation visualization and integrated discovery (DAVID) pathways and Gene Ontology enrichment analysis, 14 major DN signalling pathways were identified, including MAPK, renin-angiotensin system (RAS), TNF, signal transducer and activator of transcription (JAK-STAT), TLR, vascular endothelial growth factor (VEGF), mTOR, Wnt, Ras, PPARs, NFB, NOD and phosphatidylinositol signalling pathways. A molecular docking study revealed that 32 bioactive compounds of P. kurroa interacted with 14 significant proteins/genes associated with DN. P. kurroa extract was proven to enhance the survival rate of HEK cells significantly. Protein expression analysis using Western blot demonstrated that P. kurroa extract significantly altered the expression of p47phox, p67phox, gp91phox, IL-1 and TGFβ-1. As a result of network pharmacology and docking work, new concepts for discovering bioactive compounds and effective modes of action could be developed. The potential effect of P. kurroa extract on DN disease was evident in the in-vitro studies aided by network pharmacology and molecular docking.Communicated by Ramaswamy H. Sarma.

Comprehensive analysis of the proximity-dependent nuclear interactome for the oncoprotein NOTCH1 in live cells

Notch signaling plays a critical role in cell fate decisions in all cell types. Furthermore, gain-of-function mutations in NOTCH1 have been uncovered in many human cancers. Disruption of Notch signaling has recently emerged as an attractive disease treatment strategy. However, the nuclear interaction landscape of the oncoprotein NOTCH1 remains largely unexplored. We therefore employed here a proximity-dependent biotin identification approach to identify in vivo protein associations with the nuclear Notch1 intracellular domain in live cells. We identified a large set of previously reported and unreported proteins that associate with NOTCH1, including general transcription and elongation factors, DNA repair and replication factors, coactivators, corepressors, and components of the NuRD and SWI/SNF chromatin remodeling complexes. We also found that Notch1 intracellular domain associates with protein modifiers and components of other signaling pathways that may influence Notch signal transduction and protein stability such as USP7. We further validated the interaction of NOTCH1 with histone deacetylase 1 or GATAD2B using protein network analysis, proximity-based ligation, in vivo cross-linking and coimmunoprecipitation assays in several Notch-addicted cancer cell lines. Through data mining, we also revealed potential drug targets for the inhibition of Notch signaling. Collectively, these results provide a valuable resource to uncover the mechanisms that fine-tune Notch signaling in tumorigenesis and inform therapeutic targets for Notch-addicted tumors.

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

BACKGROUND

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSION

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

Integrated network pharmacology and cellular assay reveal the biological mechanisms of Limonium sinense (Girard) Kuntze against Breast cancer

BACKGROUND

Limonium Sinense (Girard) Kuntze (L. sinense) has been widely used for the treatment of anaemia, bleeding, cancer, and other disorders in Chinese folk medicine. The aim of this study is to predict the therapeutic effects of L. sinense and investigate the potential mechanisms using integrated network pharmacology methods and in vitro cellular experiments.

METHODS

The active ingredients of L. sinense were collected from published literature, and the potential targets related to L. sinense were obtained from public databases. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and DisGeNET enrichment analyses were performed to explore the underlying mechanisms. Molecular docking, cellular experiments, RNA-sequencing (RNA-seq) and Gene Expression Omnibus (GEO) datasets were employed to further evaluate the findings.

RESULTS

A total of 15 active ingredients of L. sinense and their corresponding 389 targets were obtained. KEGG enrichment analysis revealed that the biological effects of L. sinense were primarily associated with "Pathways in cancer". DisGeNET enrichment analysis highlighted the potential role of L. sinense in the treatment of breast cancer. Apigenin within L. sinense showed promising potential against cancer. Cellular experiments demonstrated that the L. sinense ethanol extract (LSE) exhibited a significant growth inhibitory effect on multiple breast cancer cell lines in both 2D and 3D cultures. RNA-seq analysis revealed a potential impact of LSE on breast cancer. Additionally, analysis of GEO datasets verified the significant enrichment of breast cancer and several cancer-related pathways upon treatment with Apigenin in human breast cancer cells.

CONCLUSION

This study predicts the biological activities of L. sinense and demonstrates the inhibitory effect of LSE on breast cancer cells, highlighting the potential application of L. sinense in cancer treatment.

Exploring the mechanism of Semen Strychni in treating amyotrophic lateral sclerosis based on network pharmacology

Semen Strychni (SS), known as an agonist of central nervous system, is a traditional herb widely used in treating amyotrophic lateral sclerosis (ALS) in small doses to relieve muscle weakness and improve muscle strength. However, the potential mechanisms and the main components of SS in treating ALS remain unclear. To explore the underlying mechanism of SS in treating ALS based on network pharmacology and molecular docking. The active components of SS were obtained using TCMSP, Herb, ETCM, and BATMAN-TCM. The targets of SS were gained from PharmMapper. The targets of ALS were searched on Genecards, Drugbank, DisGeNET, OMIM, TTD and GEO database. After obtaining the coincidence targets, we submitted them to the STRING database to build a protein-protein interaction network. Gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis were performed subsequently. The active components and targets were further investigated using molecular docking technology. 395 targets of SS and 1925 targets of ALS were obtained with 125 common targets. The protein-protein interaction analysis indicated that SRC, AKT1, MAPK1, EGFR, and HSP90AA1 received the higher degree value and were considered the central genes. The Ras, PI3K-Akt, and MAPK signaling pathway could be involved in the treatment of ALS. Brucine-N-oxide obtained the lowest binding energy in molecular docking. This study explored the mechanism of SS in the treatment of ALS and provides a new perspective for future study. However, further experimental studies are needed to validate the therapeutic effect.

Exploring the active components and potential mechanisms of Rosa roxburghii Tratt in treating type 2 diabetes mellitus based on UPLC-Q-exactive Orbitrap/MS and network pharmacology

BACKGROUND

Type 2 diabetes mellitus (T2DM) is a global disease with growing prevalence that is difficult to cure. Rosa roxburghii Tratt is an edible and medicinal plant, and modern pharmacological studies have shown that it has potential anti-diabetic activity. This is the first study to explore the active components and potential mechanisms of Rosa roxburghii Tratt fruit for treating T2DM based on UPLC-Q-Exactive Orbitrap/MS and network pharmacology.

METHODS

The active components of Rosa roxburghii Tratt fruit were obtained from UPLC-Q-Exactive Orbitrap/MS analysis and retrieval in the SciFinder, PubMed, Web of Science, and CNKI databases. The potential targets of the active components were obtained from the SwissTargetPrediction and PharmMapper databases. The disease targets for T2DM were obtained from GeneCards, OMIM, TTD, DisGENent, and GEO databases. The intersection of the two datasets was used to obtain the potential targets of Rosa roxburghii Tratt fruit against T2DM. The target protein interaction network was constructed using the String database and Cytoscape software. The R software ClusterProfiler package was used for target enrichment analysis and the Cytoscape CytoNCA plug-in was used to screen core targets. Molecular docking and result visualization were performed using PyMOL and Autodock Vina software.

RESULTS

We obtained 20 bioactive ingredients, including alphitolic acid, quercetin, and ellagic acid, as well as 13 core targets, such as AKT1, TNF, SRC, and VEGFA. All bioactive ingredients in Rosa roxburghii Tratt fruit were active against T2DM-related therapeutic targets. Rosa roxburghii Tratt fruit may play a therapeutic role in T2DM by regulating the PI3K/AKT, RAS, AGE-RAGE, and other signaling pathways.

CONCLUSIONS

This study explored the active components and potential mechanisms of Rosa roxburghii Tratt fruit in the treatment of T2DM, laying the foundation for a further experimental study based on pharmacodynamic substances and their mechanisms of action.

Network pharmacology-based strategy to investigate pharmacological mechanism of Liuwei Dihuang Pill against postmenopausal osteoporosis

Postmenopausal osteoporosis (PMOP) has became 1 of most prevalent bone disorders with aging population. Liuwei Dihuang (LWDH) Pill, a classical kidney-tonifying prescription, is extensively used to treat PMOP in China. The aim of this study is to explore the pharmacological mechanisms of LWDH Pill against PMOP via network pharmacological strategy. The active ingredients of LWDH Pill were screened out from the Traditional Chinese Medicine System Pharmacology, Encyclopedia of Traditional Chinese Medicine and Bioinformatics Analysis Tool for Molecular mechANism of Traditional Chinese Medicine Databases, and their related target genes were fished in the UniProt database. Simultaneously, the GeneCards and DisGeNET databases were used to identify the target genes of PMOP. Through establishing a protein-protein interaction network, the overlapping genes between LWDH Pill and PMOP were identified to analyze their interactions and the hub target genes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed to predict the underlying biological processes (BP) and signaling pathways, respectively. A total of 64 active ingredients and 653 related target genes were identified in LWDH Pill, and 292 target genes were closely associated with PMOP. After matching the target genes between LWDH Pill and PMOP, 84 overlapping targets were obtained and considered as therapeutically relevant. Through construction of a protein-protein interaction network, we identified 20 hub target genes including IL6, INS, tumor necrosis factor, AKT1, vascular endothelial growth factor A, IGF1, TP53, IL1B, MMP9, JUN, LEP, CTNNB1, EGF, PTGS2, PPARG, CXCL8, IL10, CCL2, FOS and ESR1. Gene Ontology enrichment analysis suggested that LWDH Pill exerted anti-PMOP effects via regulating multiple BP including cell proliferation and apoptosis, oxidative stress, inflammation and angiogenesis. Kyoto Encyclopedia of Genes and Genomes enrichment analysis revealed several pathways, such as PI3K-AKT pathway, mitogen-activated protein kinase pathway, hypoxia-inducible factors-1 pathway, tumor necrosis factor pathway, interleukin-17 (IL-17) pathway and FoxO pathway that might be involved in modulating the above BP. Through network pharmacological approach, we investigated the potential therapeutic mechanism of LWDH Pill against postmenopausal osteoporosis in a systemic perspective. These identified multi-targets and multi-pathways provide promising directions for further revealing more exact mechanisms.

Hedysarum multijugum Maxim treats ulcerative colitis through the PI3K-AKT and TNF signaling pathway according to network pharmacology and molecular docking

BACKGROUND

Ulcerative colitis (UC) is a chronic inflammatory bowel disease (IBD) that prevails mainly in western countries. Due to the unknown etiology of UC, the purpose of treatments has predominantly comprised symptomatic and pain relief. With extensive research focusing on the pathogenesis of UC, various novel treatments have emerged, although their efficiency has remained unsatisfactory. Hedysarum multijugum Maxim (HMM), a crucial constituent of traditional Chinese medicine, has a broad application in many diseases and has been found beneficial for UC patients.

METHODS

In this study, network pharmacology and molecular docking analyses were applied to explore the potential mechanism of HMM treating UC. Active ingredients of HMM and target genes were acquired from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). UC-related genes were obtained from three disease databases. Common genes were selected from these two gene sets, and a compound-genes network was drawn by Cytoscape. Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO) enrichment, and protein-protein interaction (PPI) analyses were performed to identify the essential pathways and proteins in UC.

RESULTS

A total of 121 genes were found related to UC and targeted by HMM. The GO and KEGG analyses showed that these genes were associated with inflammation and immune signaling pathways and inflammation-related biological processes (BP) such as the tumor necrosis factor (TNF) and PI3K-AKT signaling pathways. Four active ingredients (quercetin, kaempferol, formononetin, and isorhamnetin) and five genes (RELA, MAPK14, MAPK1, JUN, AKT1) were reserved after screening. Molecular docking further showed that the receptor had a high binding affinity with HMM active ingredients.

CONCLUSIONS

This study revealed that HMM treats UC through four active ingredients (quercetin, kaempferol, formononetin, and isorhamnetin) targeting five hub genes (RELA, MAPK14, MAPK1, JUN, AKT1) by regulating the PI3K-AKT1 and TNF signaling pathways.

Analyzing integrated network of methylation and gene expression profiles in lung squamous cell carcinoma

Gene expression, DNA methylation, and their organizational relationships are commonly altered in lung squamous cell carcinoma (LUSC). To elucidate these complex interactions, we reconstructed a differentially expressed gene network and a differentially methylated cytosine (DMC) network by partial information decomposition and an inverse correlation algorithm, respectively. Then, we performed graph union to integrate the networks. Community detection and enrichment analysis of the integrated network revealed close interactions between the cell cycle, keratinization, immune system, and xenobiotic metabolism gene sets in LUSC. DMC analysis showed that hypomethylation targeted the gene sets responsible for cell cycle, keratinization, and NRF2 pathways. On the other hand, hypermethylated genes affected circulatory system development, the immune system, extracellular matrix organization, and cilium organization. By centrality measurement, we identified NCAPG2, PSMG3, and FADD as hub genes that were highly connected to other nodes and might play important roles in LUSC gene dysregulation. We also found that the genes with high betweenness centrality are more likely to affect patients’ survival than those with low betweenness centrality. These results showed that the integrated network analysis enabled us to obtain a global view of the interactions and regulations in LUSC.

Quantitative Proteomics and Network Analysis of Differentially Expressed Proteins in Proteomes of Icefish Muscle Mitochondria Compared with Closely Related Red-Blooded Species

Simple Summary

Antarctic icefish are unusual in that they are the only vertebrates that survive without the protein haemoglobin. One way to try and understand the biological processes that support this anomaly is to record how proteins are regulated in these animals and to compare what we find to closely related Antarctic fish that do still retain haemoglobin. The part of the cell that most clearly utilises oxygen, which is normally transported by haemoglobin, is the mitochondrion. Therefore, we chose to catalogue all the proteins and their relative quantities in the mitochondria (pl.) from two different muscle types in two species of icefish and two species of red-blooded notothenioids. We used an approach called mass spectrometry to reveal relative amounts of the proteins from the muscles of each fish. We present analysis that shows how the connections and relative quantities of proteins differ between these species.

Abstract

Antarctic icefish are extraordinary in their ability to thrive without haemoglobin. We wanted to understand how the mitochondrial proteome has adapted to the loss of this protein. Metabolic pathways that utilise oxygen are most likely to be rearranged in these species. Here, we have defined the mitochondrial proteomes of both the red and white muscle of two different icefish species (Champsocephalus gunnari and Chionodraco rastrospinosus) and compared these with two related red-blooded Notothenioids (Notothenia rossii, Trematomus bernacchii). Liquid Chromatography-Mass spectrometry (LC-MS/MS) was used to generate and examine the proteomic profiles of the two groups. We recorded a total of 91 differentially expressed proteins in the icefish red muscle mitochondria and 89 in the white muscle mitochondria when compared with the red-blooded related species. The icefish have a relatively higher abundance of proteins involved with Complex V of oxidative phosphorylation, RNA metabolism, and homeostasis, and fewer proteins for striated muscle contraction, haem, iron, creatine, and carbohydrate metabolism. Enrichment analyses showed that many important pathways were different in both red muscle and white muscle, including the citric acid cycle, ribosome machinery and fatty acid degradation. Life in the Antarctic waters poses extra challenges to the organisms that reside within them. Icefish have successfully inhabited this environment and we surmise that species without haemoglobin uniquely maintain their physiology. Our study highlights the mitochondrial protein pathway differences between similar fish species according to their specific tissue oxygenation idiosyncrasies.

The Landscape of Virus-Host Protein–Protein Interaction Databases

Knowledge of virus-host interactomes has advanced exponentially in the last decade by the use of high-throughput screening technologies to obtain a more comprehensive landscape of virus-host protein–protein interactions. In this article, we present a systematic review of the available virus-host protein–protein interaction database resources. The resources covered in this review are both generic virus-host protein–protein interaction databases and databases of protein–protein interactions for a specific virus or for those viruses that infect a particular host. The databases are reviewed on the basis of the specificity for a particular virus or host, the number of virus-host protein–protein interactions included, and the functionality in terms of browse, search, visualization, and download. Further, we also analyze the overlap of the databases, that is, the number of virus-host protein–protein interactions shared by the various databases, as well as the structure of the virus-host protein–protein interaction network, across viruses and hosts.

Exploring the Mechanisms and Molecular Targets of Taohong Siwu Decoction for the Treatment of Androgenetic Alopecia Based on Network Analysis and Molecular Docking

Purpose

Taohong Siwu decoction (THSWD) is traditionally used to treat androgenic alopecia (AGA) in clinical practice of traditional Chinese medicine. This study used a network pharmacology approach to elucidate the molecular mechanism governing the effect of THSWD on AGA.

Materials and Methods

The major active components and their corresponding targets of THSWD were screened. AGA-related targets were obtained by analyzing the differentially expressed genes between AGA patients and healthy individuals. The protein–protein interaction networks of putative targets of THSWD and AGA-related targets were visualized and merged to identify the candidate targets for THSWD against AGA. Gene ontology (GO) biological processes and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis for core targets were performed. Finally, the key effective components and core targets screened were verified by molecular docking.

Results

In this study, 69 compounds and 202 compound targets of THSWD, as well as 1158 disease targets, were screened. Forty-five interactive targets were identified for constructing the “ingredient-targets” network. The functional annotations of target genes were found to be related to oxidative stress, reactive oxygen species, and hydrogen peroxide. Pathways involved in the treatment of AGA included apoptosis and PI3K-AKT signaling pathways. The luteolin, quercetin, kaempferol, baicalein, and beta-carotene were identified as the vital active compounds, and AKT1, TP53, JUN, CASP3 and MYC were considered as the core targets. Assessment of molecular docking revealed that these active compounds and targets had good-binding interactions.

Conclusion

The results indicated that the effects of THSWD against AGA may be related to anti-inflammation and anti-oxidation properties of the compounds through the specific biological processes and the related pathways.

Mechanisms of Gynostemma pentaphyllum against non-alcoholic fibre liver disease based on network pharmacology and molecular docking

As a progressive chronic disease, the effective treatment for non‐alcoholic fibre liver disease (NAFLD) has not yet been thoroughly explored at the moment. The widespread use of Gynostemma pentaphyllum (Thunb) for its anti‐insulin resistance effect indicates that potential therapeutic value may be found in Thunb for NAFLD. Hence, this research aims to discover the latent mechanism of Thunb for NAFLD treatment. To achieve the goal of discovering the latent mechanism of Thunb for NAFLD treatment, molecular docking strategy integrated a network phamacology was adopted in the exploration. We acquire Thunb compounds with activeness from TCMSP database. We collect the putative targets of Thunb and NAFLD to generate the network. Key targets and mechanism are screened by PPI analysis, GO and KEGG pathway enrichment analyses. Molecular docking simulation is introduced into the study as assessment method. Through network analysis and virtual screening based on molecular docking, 2 targets (AKT 1 and GSK3B) are identified as key therapeutic targets with satisfying binding affinity. Main mechanism is believed to be the biological process and pathway related to insulin resistance according to the enrichment analyses outcomes. Particularly, the P13K–AKT signalling pathway is recognized as a key pathway of the mechanism. In conclusion, the study shows that Thunb could be a potential treatment against NAFLD and may suppress insulin resistance through the P13K–AKT signalling pathway. The result of the exploration provides a novel perspective for approaching experimental exploration.

Integration of Network Pharmacology and Molecular Docking Technology Reveals the Mechanism of the Therapeutic Effect of Xixin Decoction on Alzheimer's Disease

BACKGROUND

So far, only a few researchers have systematically analyzed the constituents of the traditional Chinese medicine prescription Xixin Decoction (XXD) and its potential mechanism of action in treating Alzheimer's disease (AD). This study aimed to explore the potential mechanism of XXD in the treatment of AD using network pharmacology and molecular docking.

METHODS

The compounds of XXD were searched within the Traditional Chinese Medicine System Pharmacology Database (TCMSP) and the Traditional Chinese Medicine Integrated Database (TCMID) databases. Overlapping AD-related targets obtained from the two databases and the predicted targets of XXD obtained from SwissTargetPrediction platform were imported into the STRING database to build PPI networks including hub targets; Cytoscape software was used to construct the herb-compound-target network while its plug-in CytoNCA was used to screen the main active compounds of XXD. Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses explored the core biological mechanism and pathways via the Metascape platform. In addition, we used AutoDock Vina and PyMOL software to investigate the molecular docking of main compounds to hub targets.

RESULTS

We determined 114 active compounds, 973 drug targets, and 973 disease targets. However, intersection analysis screened out 208 shared targets.Protein-protein interaction (PPI) network identified 9 hub targets. The hub targets were found to be majorly enriched in several biological processes (positive regulation of kinase activity, positive regulation of cell death, regulation of MAPK cascade, trans-synaptic signaling, synaptic signaling, etc.) and the relevant pathways of Alzheimer's disease, including neuroactive ligand-receptor interaction, dopaminergic synapse, serotonergic synapse, and the MAPK signaling pathway, etc. The pathway-target-compound network of XXD for treating AD was then constructed. 8 hub targets exhibited good binding activity with 9 main active compounds of XXD in molecular docking.

CONCLUSION

In this study, we found multi-compound-multi-target-multi-pathway regulation to reveal the mechanism of XXD for treating AD based on network pharmacology and molecular docking. XXD may play a therapeutic role through regulating the Alzheimer's disease pathway, its downstream PI3K/Akt signaling pathway or the MAPK signaling pathway, thereby treating AD. This provides new insights for further experiments on the pharmacological effects of XXD.

Immune-Related Protein Interaction Network in Severe COVID-19 Patients toward the Identification of Key Proteins and Drug Repurposing

Coronavirus disease 2019 (COVID-19) is still an active global public health issue. Although vaccines and therapeutic options are available, some patients experience severe conditions and need critical care support. Hence, identifying key genes or proteins involved in immune-related severe COVID-19 is necessary to find or develop the targeted therapies. This study proposed a novel construction of an immune-related protein interaction network (IPIN) in severe cases with the use of a network diffusion technique on a human interactome network and transcriptomic data. Enrichment analysis revealed that the IPIN was mainly associated with antiviral, innate immune, apoptosis, cell division, and cell cycle regulation signaling pathways. Twenty-three proteins were identified as key proteins to find associated drugs. Finally, poly (I:C), mitomycin C, decitabine, gemcitabine, hydroxyurea, tamoxifen, and curcumin were the potential drugs interacting with the key proteins to heal severe COVID-19. In conclusion, IPIN can be a good representative network for the immune system that integrates the protein interaction network and transcriptomic data. Thus, the key proteins and target drugs in IPIN help to find a new treatment with the use of existing drugs to treat the disease apart from vaccination and conventional antiviral therapy.

Artificial intelligence in cancer target identification and drug discovery

Artificial intelligence is an advanced method to identify novel anticancer targets and discover novel drugs from biology networks because the networks can effectively preserve and quantify the interaction between components of cell systems underlying human diseases such as cancer. Here, we review and discuss how to employ artificial intelligence approaches to identify novel anticancer targets and discover drugs. First, we describe the scope of artificial intelligence biology analysis for novel anticancer target investigations. Second, we review and discuss the basic principles and theory of commonly used network-based and machine learning-based artificial intelligence algorithms. Finally, we showcase the applications of artificial intelligence approaches in cancer target identification and drug discovery. Taken together, the artificial intelligence models have provided us with a quantitative framework to study the relationship between network characteristics and cancer, thereby leading to the identification of potential anticancer targets and the discovery of novel drug candidates.

A Rice Protein Interaction Network Reveals High Centrality Nodes and Candidate Pathogen Effector Targets

Network science identifies key players in diverse biological systems including host-pathogen interactions. We demonstrated a scale-free network property for a comprehensive rice protein–protein interactome (RicePPInets) that exhibits nodes with increased centrality indices. While weighted k-shell decomposition was shown efficacious to predict pathogen effector targets in Arabidopsis, we improved its computational code for a broader implementation on large-scale networks including RicePPInets. We determined that nodes residing within the internal layers of RicePPInets are poised to be the most influential, central, and effective information spreaders. To identify central players and modules through network topology analyses, we integrated RicePPInets and co-expression networks representing susceptible and resistant responses to strains of the bacterial pathogens Xanthomonas oryzae pv. oryzae and X. oryzae pv. oryzicola (Xoc) and generated a RIce-Xanthomonas INteractome (RIXIN). This revealed that previously identified candidate targets of pathogen transcription activator-like (TAL) effectors are enriched in nodes with enhanced connectivity, bottlenecks, and information spreaders that are located in the inner layers of the network, and these nodes are involved in several important biological processes. Overall, our integrative multi-omics network-based platform provides a potentially useful approach to prioritizing candidate pathogen effector targets for functional validation, suggesting that this computational framework can be broadly translatable to other complex pathosystems.

Use of Network Pharmacology and Molecular Docking Methods to Elucidate the Curative Effect of Epimedium–Anemarrhen on Osteoporosis

Objective: Using network pharmacology and molecular docking methods, this study aimed to elucidate the key targets and molecular mechanisms of the Epimedium–Anemarrhen (EA) combination as a therapeutic approach for osteoporosis (OP). Methods: The TCMSP database was used to identify effective active ingredients and information on targets of EA according to the ADME threshold. An OP target database was established using the GeneCards, OMIM, DrugBank, and DisGeNET databases. The intersection of drug targets and disease targets was used to identify common genes, and protein interaction network, GO function enrichment, and KEGG signal pathway enrichment analyses were performed. A molecular docking analysis of active pharmaceutical ingredients with core genes was also conducted. Results: The analysis identified 30 effective active ingredients in EA and 149 common genes. A total of 20 core genes were identified by constructing a protein–protein interaction network and calculating the network topology parameters. An enrichment analysis revealed that these targets were primarily involved in biological functions and processes such as cell proliferation, apoptosis, inflammation, oxidative stress, and immunity. The signaling pathways associated with OP include the AGE-RAGE signaling pathway in relation to diabetes complications, the IL-17 signaling pathway, and the TNF signaling pathway. Molecular docking showed stable affinity between the core genes and most of the key components. Conclusion: These data provide mechanistic insights into the pharmacological activity of EA in the treatment of OP and provide an essential theoretical basis for clinical practice.

Mechanisms of magnoliae cortex on treating sarcopenia explored by GEO gene sequencing data combined with network pharmacology and molecular docking

Background

Administration of Magnoliae Cortex (MC) could induce remission of cisplatin-induced sarcopenia in mice, however, whether it is effective on sarcopenia patients and the underlying mechanisms remain unclear.

Methods

Sarcopenia related differentially expressed genes were analysed based on three Gene Expression Omnibus (GEO) transcriptome profiling datasets, which was merged and de duplicated with disease databases to obtain sarcopenia related pathogenic genes. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were than performed to analyse the role of proteins encoded by sarcopenia related pathogenic genes and the signal regulatory pathways involved in. The main active components and target proteins of MC were obtained by searching traditional Chinese medicine network databases (TCMSP and BATMAN-TCM). MC and sarcopenia related pathogenic genes shared target proteins were identified by matching the two. A protein–protein interaction network was constructed subsequently, and the core proteins were filtered according to the topological structure. GO and KEGG analysis were performed again to analyse the key target proteins and pathways of MC in the treatment of sarcopenia, and build the herbs-components-targets network, as well as core targets-signal pathways network. Molecular docking technology was used to verify the main compounds-targets.

Results

Sarcopenia related gene products primarily involve in aging and inflammation related signal pathways. Seven main active components (Anonaine, Eucalyptol, Neohesperidin, Obovatol, Honokiol, Magnolol, and beta-Eudesmol) and 26 target proteins of MC-sarcopenia, of which 4 were core proteins (AKT1, EGFR, INS, and PIK3CA), were identified. The therapeutic effect of MC on sarcopenia may associate with PI3K-Akt signaling pathway, EGFR tyrosine kinase inhibitor resistance, longevity regulating pathway, and other cellular and innate immune signaling pathways.

Conclusion

MC contains potential anti-sarcopenia active compounds. These compounds play a role by regulating the proteins implicated in regulating aging and inflammation related signaling pathways, which are crucial in pathogenesis of sarcopenia. Our study provides new insights into the development of a natural therapy for the prevention and treatment of sarcopenia.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12863-022-01029-x.

A New Prospect for the Treatment of Nephrotic Syndrome Based on Network Pharmacology Analysis

Network pharmacology is an emerging field which is currently capturing interest in drug discovery and development. Chronic kidney conditions have become a threat globally due to its associated lifelong therapies. Nephrotic syndrome (NS) is a common glomerular disease that is seen in paediatric and adult population with characteristic manifestation of proteinuria, oedema, hypoalbuminemia, and hyperlipidemia. It involves podocyte damage with tubulointerstitial fibrosis and glomerulosclerosis. Till date there has been no specific treatment available for this condition that provides complete remission. Repurposing of drugs can thus be a potential strategy for the treatment of NS. Recently, epigenetic mechanisms were identified that promote progression of many renal diseases. Therefore, in the present study, we investigated two epigenetic drugs valproic acid (VPA) and all-trans retinoic acid (ATRA). Epigenetic drugs act by binging about changes in gene expression without altering the DNA sequence. The changes include DNA methylation or histone modifications. The targets for the two drugs ATRA and VPA were collated from ChEMBL and Binding DB. All the genes associated with NS were collected from DisGeNET and KEGG database. Interacting proteins for the target genes were acquired from STRING database. The genes were then subjected to gene ontology and pathway enrichment analysis using a functional enrichment software tool. A drug-target and drug-potential target-protein interaction network was constructed using the Cytoscape software. Our results revealed that the two drugs VPA and ATRA had 65 common targets that contributed to kidney diseases. Out of which, 25 targets were specifically NS associated. Further, our work exhibited that ATRA and VPA were synergistically involved in pathways of inflammation, renal fibrosis, glomerulosclerosis and possibly mitochondrial biogenesis and endoplasmic reticulum stress. We thus propose a synergistic potential of the two drugs for treating chronic kidney diseases, specifically NS. The outcomes will undoubtedly invigorate further preclinical and clinical explorative studies. We identify network pharmacology as an initial inherent approach in identifying drug candidates for repurposing and synergism.

The modulatory properties of Astragalus membranaceus treatment on endometrial cancer: an integrated pharmacological method

Astragalus membranaceus is a traditional Chinese medicine and has been used for adjuvant clinical therapy for a variety of cancers. However, the mechanism of its action on endometrial carcinoma is unclear. Based on the Gene Expression Omnibus (GEO) database, the Cancer Genome Atlas (TCGA) database, and the Traditional Chinese Medicine System Pharmacology Database (TCMSP™), the drug and target compounds were initially screened to construct a common network module. Twenty active compounds in Astragalus membranaceus were successfully identified, which hit by 463 potential targets related to endometrial cancer. Eight of the more highly predictive compounds (such as Jaranol, Bifendate, Isorhamnetin, Calycosin, 7-O-methylisomucronulatol, Formononetin, Kaempferol, Quercetin) were involved in DNA integrity checkpoint, cyclin-dependent protein kinase holoenzyme complex, and histone kinase activity. Additionally, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway confirmed that Astragalus membranaceus might play a role in the treatment of endometrial cancer through p53 signalling pathway, transcriptional misregulation in cancer, and endometrial cancer signalling pathway. Drug-target-pathway networks were constructed using Cytoscape to provide a visual perspective. In addition, we verified that formononetin inhibited the proliferation of endometrial cancer cells through cell viability tests and clone formation tests. And qPCR and western blot found that formononetin exerts anti-cancer effects by promoting the expression of estrogen receptor beta (ERβ) and p53. Based on a systematic network pharmacology approach, our works successfully predict the active ingredients and potential targets of Astragalus membranaceus for application to endometrial cancer and helps to illustrate mechanism of action on a comprehensive level.

Comparison of anti-inflammatory effects of Lonicerae Japonicae Flos and Lonicerae Flos based on network pharmacology

Objective

Methods

Results

Conclusion

Predictive Study of the Active Ingredients and Potential Targets of Codonopsis pilosula for the Treatment of Osteosarcoma via Network Pharmacology

Osteosarcoma (OS) is the most common type of primary bone tumor in children and adults. Dangshen (Codonopsis pilosula) is a traditional Chinese medicine commonly used in the treatment of OS worldwide. However, the molecular mechanisms of Dangshen in OS remain unclear. Hence, in this study, we aimed to systematically explore the underlying mechanisms of Dangshen in the treatment of OS. Our study adopted a network pharmacology approach, focusing on the identification of active ingredients, drug target prediction, gene collection, gene ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment, and other network tools. The network analysis identified 15 active compounds in Dangshen that were linked to 48 possible therapeutic targets related to OS. The results of the gene enrichment analysis show that Dangshen produces a therapeutic effect in OS likely by regulating multiple pathways associated with DNA damage, cell proliferation, apoptosis, invasion, and migration. Based on the network pharmacology approach, we successfully predicted the active compounds and their respective targets. In addition, we illustrated the molecular mechanisms that mediate the therapeutic effect of Dangshen in OS. These findings may aid in the development of novel targeted therapies for OS in the future.

Protein interaction potential landscapes for yeast replicative aging

We proposed a novel interaction potential landscape approach to map the systems-level profile changes of gene networks during replicative aging in Saccharomyces cerevisiae. This approach enabled us to apply quasi-potentials, the negative logarithm of the probabilities, to calibrate the elevation of the interaction landscapes with young cells as a reference state. Our approach detected opposite landscape changes based on protein abundances from transcript levels, especially for intra-essential gene interactions. We showed that essential proteins play different roles from hub proteins on the age-dependent interaction potential landscapes. We verified that hub proteins tend to avoid other hub proteins, but essential proteins prefer to interact with other essential proteins. Overall, we showed that the interaction potential landscape is promising for inferring network profile change during aging and that the essential hub proteins may play an important role in the uncoupling between protein and transcript levels during replicative aging.

Opportunities at the Interface of Network Science and Metabolic Modeling

Metabolism plays a central role in cell physiology because it provides the molecular machinery for growth. At the genome-scale, metabolism is made up of thousands of reactions interacting with one another. Untangling this complexity is key to understand how cells respond to genetic, environmental, or therapeutic perturbations. Here we discuss the roles of two complementary strategies for the analysis of genome-scale metabolic models: Flux Balance Analysis (FBA) and network science. While FBA estimates metabolic flux on the basis of an optimization principle, network approaches reveal emergent properties of the global metabolic connectivity. We highlight how the integration of both approaches promises to deliver insights on the structure and function of metabolic systems with wide-ranging implications in discovery science, precision medicine and industrial biotechnology.

SPONGEdb: a pan-cancer resource for competing endogenous RNA interactions

microRNAs (miRNAs) are post-transcriptional regulators involved in many biological processes and human diseases, including cancer. The majority of transcripts compete over a limited pool of miRNAs, giving rise to a complex network of competing endogenous RNA (ceRNA) interactions. Currently, gene-regulatory networks focus mostly on transcription factor-mediated regulation, and dedicated efforts for charting ceRNA regulatory networks are scarce. Recently, it became possible to infer ceRNA interactions genome-wide from matched gene and miRNA expression data. Here, we inferred ceRNA regulatory networks for 22 cancer types and a pan-cancer ceRNA network based on data from The Cancer Genome Atlas. To make these networks accessible to the biomedical community, we present SPONGEdb, a database offering a user-friendly web interface to browse and visualize ceRNA interactions and an application programming interface accessible by accompanying R and Python packages. SPONGEdb allows researchers to identify potent ceRNA regulators via network centrality measures and to assess their potential as cancer biomarkers through survival, cancer hallmark and gene set enrichment analysis. In summary, SPONGEdb is a feature-rich web resource supporting the community in studying ceRNA regulation within and across cancer types.

Network Pharmacology Study of the Hepatoprotective Effects of Quercetin-Containing Traditional Chinese Medicine, Anoectochilus roxburghii, and Validation of Quercetin as an Anti-Liver Injury Agent in a Mouse Model of Liver Injury

Background

Anoectochilus roxburghii (Orchidaceae) (AR) has been widely used to treat liver injury in China, but its underlying mechanisms remain elusive. Network pharmacology was utilized to assess the hepatoprotective effects of quercetin (Que)-containing AR, and to validate the anti-liver injury effects of Que in a mouse model of liver injury.

Material/Methods

Network pharmacology analysis was performed to determine bio-active compounds in AR. The core therapeutic targets of AR against liver injury were identified using a protein–protein interaction network. Biological function and pathway enrichment were analyzed based on the identified core therapeutic targets. The hepatoprotective effects of Que in a mouse model of liver injury induced by CCl₄ were assessed to verify the reliability of network pharmacology analysis.

Results

Seven bio-active compounds of AR met drug screening criteria and 17 core therapeutic targets of AR against liver injury were identified. Biological function analysis demonstrated that the therapeutic effects of AR against liver injury were chiefly associated with the suppression of inflammation and immunity; and pathway enrichment analysis showed that nuclear factor-kappa B (NF-κB) and tumor necrosis factor (TNF) signaling pathways were associated with the inflammatory responses. Experimental validation in a mouse model showed that AR exerted anti-inflammatory effects by regulating the NF-κB signaling pathway, a finding that also confirmed the reliability of network pharmacology analysis.

Conclusions

The bio-active compounds identified in AR and the elucidation of their mechanisms of action against liver injury provide a theoretical basis for designing agents that can prevent or suppress liver injury.

Bacteria use structural imperfect mimicry to hijack the host interactome

Bacteria use protein-protein interactions to infect their hosts and hijack fundamental pathways, which ensures their survival and proliferation. Hence, the infectious capacity of the pathogen is closely related to its ability to interact with host proteins. Here, we show that hubs in the host-pathogen interactome are isolated in the pathogen network by adapting the geometry of the interacting interfaces. An imperfect mimicry of the eukaryotic interfaces allows pathogen proteins to actively bind to the host's target while preventing deleterious effects on the pathogen interactome. Understanding how bacteria recognize eukaryotic proteins may pave the way for the rational design of new antibiotic molecules.

Essential gene prediction using limited gene essentiality information-An integrative semi-supervised machine learning strategy

Essential gene prediction helps to find minimal genes indispensable for the survival of any organism. Machine learning (ML) algorithms have been useful for the prediction of gene essentiality. However, currently available ML pipelines perform poorly for organisms with limited experimental data. The objective is the development of a new ML pipeline to help in the annotation of essential genes of less explored disease-causing organisms for which minimal experimental data is available. The proposed strategy combines unsupervised feature selection technique, dimension reduction using the Kamada-Kawai algorithm, and semi-supervised ML algorithm employing Laplacian Support Vector Machine (LapSVM) for prediction of essential and non-essential genes from genome-scale metabolic networks using very limited labeled dataset. A novel scoring technique, Semi-Supervised Model Selection Score, equivalent to area under the ROC curve (auROC), has been proposed for the selection of the best model when supervised performance metrics calculation is difficult due to lack of data. The unsupervised feature selection followed by dimension reduction helped to observe a distinct circular pattern in the clustering of essential and non-essential genes. LapSVM then created a curve that dissected this circle for the classification and prediction of essential genes with high accuracy (auROC > 0.85) even with 1% labeled data for model training. After successful validation of this ML pipeline on both Eukaryotes and Prokaryotes that show high accuracy even when the labeled dataset is very limited, this strategy is used for the prediction of essential genes of organisms with inadequate experimentally known data, such as Leishmania sp. Using a graph-based semi-supervised machine learning scheme, a novel integrative approach has been proposed for essential gene prediction that shows universality in application to both Prokaryotes and Eukaryotes with limited labeled data. The essential genes predicted using the pipeline provide an important lead for the prediction of gene essentiality and identification of novel therapeutic targets for antibiotic and vaccine development against disease-causing parasites.

Exploring the complexity of soybean (Glycine max) transcriptional regulation using global gene co-expression networks

MAIN CONCLUSION

We report a soybean gene co-expression network built with data from 1284 RNA-Seq experiments, which was used to identify important regulators, modules and to elucidate the fates of gene duplicates. Soybean (Glycine max (L.) Merr.) is one of the most important crops worldwide, constituting a major source of protein and edible oil. Gene co-expression networks (GCN) have been extensively used to study transcriptional regulation and evolution of genes and genomes. Here, we report a soybean GCN using 1284 publicly available RNA-Seq samples from 15 distinct tissues. We found modules that are differentially regulated in specific tissues, comprising processes such as photosynthesis, gluconeogenesis, lignin metabolism, and response to biotic stress. We identified transcription factors among intramodular hubs, which probably integrate different pathways and shape the transcriptional landscape in different conditions. The top hubs for each module tend to encode proteins with critical roles, such as succinate dehydrogenase and RNA polymerase subunits. Importantly, gene essentiality was strongly correlated with degree centrality and essential hubs were enriched in genes involved in nucleic acids metabolism and regulation of cell replication. Using a guilt-by-association approach, we predicted functions for 93 of 106 hubs without functional description in soybean. Most of the duplicated genes had different transcriptional profiles, supporting their functional divergence, although paralogs originating from whole-genome duplications (WGD) are more often preserved in the same module than those from other mechanisms. Together, our results highlight the importance of GCN analysis in unraveling key functional aspects of the soybean genome, in particular those associated with hub genes and WGD events.

Systems pharmacology in combination with proteomics reveals underlying mechanisms of Xihuang pill against triple-negative breast cancer

Xihuang pill (XHP), a traditional Chinese herbal formula, has been clinically used as an adjuvant therapy against triple-negative breast cancer (TNBC) via inhibiting cancer cell invasion and proliferation, as well as promoting cancer cell apoptosis. However, its anti-TNBC bio-active ingredients and possible mechanisms are still unclear. Herein, the hub bio-active compounds and underlying mechanisms of XHP against TNBC were systematically elucidated by integrating systems pharmacology approach and in vitro proteomics analysis. Using systems pharmacology analysis and molecular docking evaluation, 28 bio-active compounds and 10 potential therapeutic targets of XHP were identified. Functional analysis showed that the core therapeutic targets against TNBC were mainly involved in epidermal growth factor receptor (EGFR)-phosphatidylinositol 3-kinase (PI3K)-AKT signaling pathway to prevent cancer cell proliferation and angiogenesis, as well as to enhance cancer cell apoptosis. The in vitro proteomics analysis identified 153 differentially expressed proteins (DEPs), including HASP90AA1, AKT1, and EGFR, which were also identified as therapeutic targets against TNBC through systems pharmacology analysis. Protein function analysis showed that the DEPs were mainly involved in PI3K-AKT signaling pathway, which was consistent with the result of systems pharmacology, suggesting the reliability of systems pharmacology analysis. Taken together, these findings uncover the underlying mechanism of XHP against TNBC, and provide a scientific method for the rational development of traditional Chinese medicine.

Identification of the Active Constituents and Significant Pathways of Guizhi-Shaoyao-Zhimu Decoction for the Treatment of Diabetes Mellitus Based on Molecular Docking and Network Pharmacology

AIM AND OBJECTIVE

This study was designed to explore the active compounds and significant pathways of Guizhi-Shaoyao-Zhimu decoction (GSZD) for treating diabetes mellitus using molecular docking combined with network pharmacology.

MATERIALS AND METHODS

Chemical constituents of GSZD and diabetes-related target proteins were collected from various databases. Then, compounds were filtered by Lipinski's and Veber's rules with Discovery studio software. The "Libdock" module was used to carry out molecular docking, and LibDockScores, default cutoff values for hydrogen bonds, and van der Waals interactions were recorded. LibDockScore of the target protein and its prototype ligand was considered as the threshold, and compounds with higher LibDockScores than the threshold were regarded as the active constituents of GSZD. Cytoscape software was used to construct the herb-active molecule-target interaction network of GSZD. ClueGO and CluePedia were applied to enrich the analysis of the biological functions and pathways of GSZD.

RESULTS

A total of 275 potential active compounds with 57 possible pathways in GSZD were identified by molecular docking combined with network pharmacology. TEN, INSR, PRKAA2, and GSK3B are the four most important target proteins. Gancaonin E, 3'-(γ,γ-dimethylallyl)-kievitone, aurantiamide, curcumin and 14-O-cinnamoylneoline, could interact with more than 14 of the selected target proteins. Besides, 57 potential pathways of GSZD were identified, such as insulin signaling pathway, metabolites and energy regulation, glucose metabolic process regulation, and positive regulation of carbohydrate metabolic process, etc. Conclusion: These results showed that molecular docking combined with network pharmacology is a feasible strategy for exploring bioactive compounds and mechanisms of Chinese medicines, and GSZD can be used to effectively treat diabetes through multi-components and multi-targets & pathways.

Dynamics of a Protein Interaction Network Associated to the Aggregation of polyQ-Expanded Ataxin-1

Background: Several experimental models of polyglutamine (polyQ) diseases have been previously developed that are useful for studying disease progression in the primarily affected central nervous system. However, there is a missing link between cellular and animal models that would indicate the molecular defects occurring in neurons and are responsible for the disease phenotype in vivo. Methods: Here, we used a computational approach to identify dysregulated pathways shared by an in vitro and an in vivo model of ATXN1(Q82) protein aggregation, the mutant protein that causes the neurodegenerative polyQ disease spinocerebellar ataxia type-1 (SCA1). Results: A set of common dysregulated pathways were identified, which were utilized to construct cerebellum-specific protein-protein interaction (PPI) networks at various time-points of protein aggregation. Analysis of a SCA1 network indicated important nodes which regulate its function and might represent potential pharmacological targets. Furthermore, a set of drugs interacting with these nodes and predicted to enter the blood–brain barrier (BBB) was identified. Conclusions: Our study points to molecular mechanisms of SCA1 linked from both cellular and animal models and suggests drugs that could be tested to determine whether they affect the aggregation of pathogenic ATXN1 and SCA1 disease progression.

Mechanisms of indigo naturalis on treating ulcerative colitis explored by GEO gene chips combined with network pharmacology and molecular docking

Oral administration of indigo naturalis (IN) can induce remission in ulcerative colitis (UC); however, the underlying mechanism remains unknown. The main active components and targets of IN were obtained by searching three traditional Chinese medicine network databases such as TCMSP and five Targets fishing databases such as PharmMapper. UC disease targets were obtained from three disease databases such as DrugBank,combined with four GEO gene chips. IN-UC targets were identified by matching the two. A protein–protein interaction network was constructed, and the core targets were screened according to the topological structure. GO and KEGG enrichment analysis and bioGPS localization were performed,and an Herbs-Components-Targets network, a Compound Targets-Organs location network, and a Core Targets-Signal Pathways network were established. Molecular docking technology was used to verify the main compounds-targets. Ten core active components and 184 compound targets of IN-UC, of which 43 were core targets, were enriched and analyzed by bioGPS, GO, and KEGG. The therapeutic effect of IN on UC may involve activation of systemic immunity, which is involved in the regulation of nuclear transcription, protein phosphorylation, cytokine activity, reactive oxygen metabolism, epithelial cell proliferation, and cell apoptosis through Th17 cell differentiation, the Jak-STAT and IL-17 signaling pathways, toll-like and NOD-like receptors, and other cellular and innate immune signaling pathways. The molecular mechanism underlying the effect of IN on inducing UC remission was predicted using a network pharmacology method, thereby providing a theoretical basis for further study of the effective components and mechanism of IN in the treatment of UC.

Deciphering the Underlying Mechanism of Eucommiae Cortex against Osteoporotic Fracture by Network Pharmacology

Background

Du Zhong (DZ), or Eucommiae Cortex, a traditional Chinese herbal medicine, has been used to treat osteoporosis. Although it has been reported that DZ can improve bone mass in ovariectomized rats, its pharmacological mechanisms in treating osteoporotic fractures (OPF) remain unclear.

Methods

In this study, we used a network pharmacological manner to explore its potential complicated mechanism in treating OPF. We obtained DZ compounds from TCMSP and BATMAN-TCM databases and collected potential targets of these compounds through target fishing based on TCMSP and BATMAN-TCM databases. Next, we collected the OPF targets by using CTD, GeneCards, OMIM, HPO, and GenCLiP 3 databases. And then the overlapping genes between DZ potential targets and OPF targets were used to build up the protein-protein interaction (PPI) network and to analyze their interactions and find out the big hub genes in this network. Subsequently, clusterProfiler package in R language was utilized to conduct the enrichment of Gene Ontology biological process and KEGG pathways.

Results

There were totally 93 active compounds and 916 related targets in DZ. After the enrichment analysis, we collected top 25 cellular biological processes and top 25 pathways based on the adjusted P value and found that the DZ anti-OPF effect was mainly associated with the regulation of ROS and inflammatory response. Furthermore, 64 hub genes in PPI network, such as MAPK1 (degree = 41), SRC (degree = 39), PIK3R1 (degree = 36), VEGFA (degree = 31), TP53 (degree = 29), EGFR (degree = 29), JUN (degree = 29), AGT (degree = 29), MAPK1, SRC, PIK3R1, VEGFA, and TP53, were considered as potential therapeutic targets, implying the underlying mechanisms of DZ acting on OPF.

Conclusion

We investigated the possible therapeutic mechanisms of DZ from a systemic perspective. These key targets and pathways provided promising directions for the future research to reveal the exact regulating mechanisms of DZ in treating OPF.

Mechanisms of Spica Prunellae against thyroid-associated Ophthalmopathy based on network pharmacology and molecular docking

BACKGROUND

Thyroid-associated ophthalmopathy (TAO) is an autoimmune inflammatory disorder, which lacks effective treatment currently. Spica Prunellae (SP) is popularly used for its anti-inflammatory and immune-regulating properties, indicating SP may have potential therapeutic value in TAO. Therefore, the purpose of this study is to identify the efficiency and potential mechanism of SP in treating TAO.

METHODS

A network pharmacology integrated molecular docking strategy was used to predict the underlying molecular mechanism of treating TAO. Firstly, the active compounds of SP were obtained from TCMSP database and literature research. Then we collected the putative targets of SP and TAO based on multi-sources databases to generate networks. Network topology analysis, GO and KEGG pathway enrichment analysis were performed to screen the key targets and mechanism. Furthermore, molecular docking simulation provided an assessment tool for verifying drug and target binding.

RESULTS

Our results showed that 8 targets (PTGS2, MAPK3, AKT1, TNF, MAPK1, CASP3, IL6, MMP9) were recognized as key therapeutic targets with excellent binding affinity after network analysis and molecular docking-based virtual screening. The results of enrichment analysis suggested that the underlying mechanism was mainly focused on the biological processes and pathways associated with immune inflammation, proliferation, and apoptosis. Notably, the key pathway was considered as the PI3K-AKT signaling pathway.

CONCLUSION

In summary, the present study elucidates that SP may suppress inflammation and proliferation and promote apoptosis through the PI3K-AKT pathway, which makes SP a potential treatment against TAO. And this study offers new reference points for future experimental research and provides a scientific basis for more widespread clinical application.

Deciphering the underlying mechanism of Xianlinggubao capsule against osteoporosis by network pharmacology

Background

Xianlinggubao formula (XLGB), a Chinese State Food and Drug Administration-permitted traditional Chinese herbal medicine, has been extensively used to treat osteoporosis. Although XLGB was shown to improve bone mass in ovariectomized rats and clinically alleviate osteoporosis symptoms, its pharmacological mechanisms remain unclear.

Methods

In this study, we used a network pharmacological approach to explore the potential mechanism of XLGB in treating osteoporosis. We obtained XLGB compounds from the TCMSP and TCMID databases and identified potential targets of these compounds through target fishing based on the TCMSP and Swiss Target Prediction databases. Next, we identified the osteoporosis targets by using the CTD, TTD, GeneCards, OMIM and PharmGKB databases. Then, the overlapping genes between the XLGB potential targets and the osteoporosis targets were used to establish a protein-protein interaction (PPI) network and to analyze their interactions and identify the major hub genes in this network. Subsequently, the Metascape database was utilized to conduct the enrichment of Gene Ontology biological processes and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways.

Results

There were 104 active compounds and 295 related targets identified overall. After the Metascape enrichment analysis, we identified the top 25 cellular biological processes and top 15 pathways based on the logP value and found that the XLGB-mediated anti-osteoporosis effect was mainly associated with reactive oxygen species, organonitrogen compound response and cell migration. Furthermore, 36 hub genes of XLGB, such as EGF, EGFR, MTOR, MAPK14 and NFKB1, were considered potential therapeutic targets, suggesting the underlying mechanisms of XLGB acting on osteoporosis.

Conclusion

We investigated the possible therapeutic mechanisms of XLGB from a systemic perspective. These key targets and pathways provide promising directions for future research to reveal the exact regulatory mechanisms of XLGB.

Integrated Analysis of the Mechanisms of Da-Chai-Hu Decoction in Type 2 Diabetes Mellitus by a Network Pharmacology Approach

Background

The incidence of type 2 diabetes mellitus (T2DM) has increased year by year, which not only seriously affects people's quality of life, but also imposes a heavy economic burden on the family, society, and country. Currently, the pathogenesis, diagnosis, and treatment of T2DM are still unclear. Therefore, exploration of a precise multitarget treatment strategy is urgent. Here, we attempt to screen out the active components, effective targets, and functional pathways of therapeutic drugs through network pharmacology with taking advantages of traditional Chinese medicine (TCM) formulas for multitarget holistic treatment of diseases to clarify the potential therapeutic mechanism of TCM formulas and provide a systematic and clear thought for T2DM treatment.

Methods

First, we screened the active components of Da-Chai-Hu Decoction (DCHD) by absorption, distribution, metabolism, excretion, and toxicity (ADME/T) calculation. Second, we predicted and screened the active components of DCHD and its therapeutic targets for T2DM relying on the Traditional Chinese Medicine Systems Pharmacology Analysis Platform (TCMSP database) and Text Mining Tool (GoPubMed database), while using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) to obtain T2DM targets. Third, we constructed a network of the active component-target, target-pathway of DCHD using Cytoscape software (http://cytoscape.org/,ver.3.5.1) and then analyzed gene function, related biological processes, and signal pathways through the DAVID database.

Results

We screened 77 active components from 1278 DCHD components and 116 effective targets from 253 ones. After matching the targets of T2DM, we obtained 38 important targets and 7 core targets were selected through further analysis. Through enrichment analysis, we found that these important targets were mainly involved in many biological processes such as oxidative stress, inflammatory reaction, and apoptosis. After analyzing the relevant pathways, the synthetic pathway for the treatment of T2DM was obtained, which provided a diagnosis-treatment idea for DCHD in the treatment of T2DM.

Conclusions

This article reveals the mechanism of DCHD in the treatment of T2DM related to inflammatory response and apoptosis through network pharmacology, which lays a foundation for further elucidation of drugs effective targets.

Network Pharmacology-based Investigation of the Underlying Mechanism of Panax notoginseng Treatment of Diabetic Retinopathy

Background: Panax notoginseng, a Chinese herbal medicine, has been widely used to treat vascular diseases. Diabetic retinopathy (DR) is one of the complications of diabetic microangiopathy. According to recent studies, the application of Panax notoginseng extract and related Chinese patent medicine preparations can significantly improve DR. However, the pharmacological mechanisms remain unclear. Therefore, the purpose of this study was to decipher the potential mechanism of Panax notoginseng treatment of DR using network pharmacology.

Method: We evaluated and screened the active compounds of Panax notoginseng using the Traditional Chinese Medicine Systems Pharmacology database and collected potential targets of the compounds by target fishing. A multi-source database was also used to organize targets of DR. The potential targets as the treatment of DR with Panax notoginseng were then obtained by matching the compound targets with the DR targets. Using protein-protein interaction networks and topological analysis, interactions between potential targets were identified. In addition, we also performed gene ontology-biological process and pathway enrichment analysis for the potential targets by using the Biological Information Annotation Database.

Results: Eight active ingredients of Panax notoginseng and 31 potential targets for the treatment of DR were identified. The screening and enrichment analysis revealed that the treatment of DR using Panax notoginseng primarily involved 28 biological processes and 10 related pathways. Further analyses indicated that angiogenesis, inflammatory reactions, and apoptosis may be the main processes involved in the treatment of DR with Panax notoginseng. In addition, we determined that the mechanism of intervention of Panax notoginseng in treating DR may involve five core targets, VEGFA, MMP-9, MMP-2, FGF2, and COX-2.

Conclusion: Panax notoginseng may treat diabetic retinopathy through the mechanism of network pharmacological analysis. The underlying molecular mechanisms were closely related to the intervention of angiogenesis, inflammation, and apoptosis with VEGFA, MMP-9, MMP-2, FGF2, and COX-2 being possible targets.

A network analysis revealed the essential and common downstream proteins related to inguinal hernia

Although more than 1 in 4 men develop symptomatic inguinal hernia during their lifetime, the molecular mechanism behind inguinal hernia remains unknown. Here, we explored the protein-protein interaction network built on known inguinal hernia-causative genes to identify essential and common downstream proteins for inguinal hernia formation. We discovered that PIK3R1, PTPN11, TGFBR1, CDC42, SOS1, and KRAS were the most essential inguinal hernia-causative proteins and UBC, GRB2, CTNNB1, HSP90AA1, CBL, PLCG1, and CRK were listed as the most commonly-involved downstream proteins. In addition, the transmembrane receptor protein tyrosine kinase signaling pathway was the most frequently found inguinal hernia-related pathway. Our in silico approach was able to uncover a novel molecular mechanism underlying inguinal hernia formation by identifying inguinal hernia-related essential proteins and potential common downstream proteins of inguinal hernia-causative proteins.

An Investigation of the Mechanism of Rapid Relief of Ulcerative Colitis Induced by Five-flavor Sophora Flavescens Enteric-coated Capsules Based on Network Pharmacology

AIM AND OBJECTIVE

Five-Flavor Sophora flavescens Enteric-Coated Capsules (FSEC) are the only proprietary Chinese medicine approved for the treatment of ulcerative colitis (UC) in China. Phase II and III clinical trials have shown that the curative effect of FSEC in relieving UC was not inferior to that of mesalazine granules and enteric-coated tablets, but its pharmacological mechanism is unclear. Therefore, the network pharmacology is used to reveal the more comprehensive effective components and targets of FSEC in the treatment of UC.

METHODS

We screened the components of FSEC based on the TCMSP database, determined the action targets of these compounds through target fishing, and integrated the UC disease targets of several disease gene databases. The FSEC-UC composite targets were obtained by matching the two results, and then a PPI network was constructed to analyze the relationship between these targets, and the core targets were selected by topological correlation parameters. Finally, GO-BP and KEGG enrichment analyses were carried out using the clusterProfiler software package.

RESULTS

One hundred and sixty active components of FSEC were identified and 77 targets were obtained. Of these, 30 core targets were the main targets of FESC in the treatment of UC. And quercetin, kaempferol, luteolin and mangiferin were regarded as the core active components of FSEC. The results screened by GO and KEGG enrichment analysis showed that FSEC played a comprehensive therapeutic role in immune recognition, anti-inflammation and antioxidation mainly through IL-17, TNF, Toll-like receptor, NF-kappa B, and Th17 cell differentiation.

CONCLUSION

The molecular mechanism of UC remission induced by FSEC was predicted by network pharmacology. These findings provide an important theoretical basis for further study of the effective substances and mechanism of FSEC in the treatment of UC.

Network analysis of host-pathogen protein interactions in microbe induced cardiovascular diseases

Large-scale visualization and analysis of HPIs involved in microbial CVDs can provide crucial insights into the mechanisms of pathogenicity. The comparison of CVD associated HPIs with the entire set of HPIs can identify the pathways specific to CVDs. Therefore, topological properties of HPI networks in CVDs and all pathogens was studied using Cytoscape3.5.1. Ontology and pathway analysis were done using KOBAS 3.0. HPIs of Papilloma, Herpes, Influenza A virus as well as Yersinia pestis and Bacillus anthracis among bacteria were predominant in the whole (wHPI) and the CVD specific (cHPI) network. The central viral and secretory bacterial proteins were predicted virulent. The central viral proteins had higher number of interactions with host proteins in comparison with bacteria. Major fraction of central and essential host proteins interacts with central viral proteins. Alpha-synuclein, Ubiquitin ribosomal proteins, TATA-box-binding protein, and Polyubiquitin-C &B proteins were the top interacting proteins specific to CVDs. Signaling by NGF, Fc epsilon receptor, EGFR and ubiquitin mediated proteolysis were among the top enriched CVD specific pathways. DEXDc and HELICc were enriched host mimicry domains that may help in hijacking of cellular machinery by pathogens. This study provides a system level understanding of cardiac damage in microbe induced CVDs.

Uncovering Synergistic Mechanism of Chinese Herbal Medicine in the Treatment of Atrial Fibrillation with Obstructive Sleep Apnea Hypopnea Syndrome by Network Pharmacology

Paroxysmal atrial fibrillation (AF) combined with obstructive sleep apnea hypopnea syndrome (OSAHS) is very common in clinical practice. Traditional Chinese medicine (TCM) rule of regulating the liver based on psycho-cardiology shows satisfactory effectiveness in the treatment of paroxysmal AF combined with OSAHS. However, its underlying pharmacological mechanism has not yet been elucidated. This study applied network pharmacology to identify 94 active components in the six TCM liver-regulating herbs and 182 corresponding targets from several databases and comprehensive literature studies, as well as retrieved AF combined with OSAHS-related targets. Cytoscape software was adopted to construct the component-component target network and component-putative target-AF combined with OSAHS target network. Then, we obtained 38 putative therapeutic targets against AF combined with OSAHS. After the production of a putative therapeutic target interaction network, topological analysis was adopted to determine the core targets of TCM liver-regulating herbs in the treatment of paroxysmal AF combined with OSAHS. For all putative therapeutic targets, biological process analysis and pathway enrichment analysis were utilized to investigate the possible mechanism of TCM liver-regulating herbs in the treatment of paroxysmal AF combined with OSAHS. Mechanistically, it included positive regulation of nitric oxide biosynthetic process, aging, response to hypoxia, TNF signaling pathway, HIF-1 signaling pathway, PI3K-Akt signaling pathway, neuroactive ligand-receptor interaction, and calcium signaling pathway. Especially, six core targets of TCM liver-regulating herbs, namely, TNF, STAT3, AKT1, IL-6, TP53, and INS, were significant in the regulation of the above biological processes and pathways. This study demonstrates the multicomponent, multitarget, and multipathway feature of TCM liver-regulating herbs, provides an extensional foundation for further research, and facilitates the reasonable application of TCM liver-regulating herbs in treating paroxysmal AF combined with OSAHS.