Understanding ZHENG in traditional Chinese medicine in the context of neuro-endocrine-immune network

Ursolic acid inhibits NF-κB signaling and attenuates MMP-9/TIMP-1 in progressive osteoarthritis: a network pharmacology-based analysis

Osteoarthritis (OA) is a degenerative joint disease, characterized by infiltration of monocytes into the synovial joint which promotes inflammation, stiffness, joint swelling, cartilage degradation and further bone destruction. The leaves of Ocimum forskolei have been used for inflammation-related disease management in traditional medicine. Additionally, the downregulation of NF-κB and the MMP/TIMP-1 ratio has been shown to protect against OA. The LC-HR-MS metabolic analysis of Ocimum yielded 19 putative compounds, among which ursolic acid (UA) was detected. Ursolic acid possesses significant anti-inflammatory effects and has been reported to downregulate oxidative stress and inflammatory biomarkers. It was tested on rats in a model of intra-articular carrageenan injection to investigate its efficacy on osteoarthritis progression. The UA emulgel exerted chondroprotective, analgesic and local anaesthetic efficacies confirmed via histopathological investigation and radiographical imaging. A network pharmacology followed by molecular docking highlighted TNF-α, TGF-β and NF-κB as the top filtered genes. Quantitative real-time PCR analysis showed that UA significantly attenuated serum levels of TNF-α, IL-1β, NF-κB, MMP-9/TIMP-1 and elevated levels of TGF-β. Taken together, these results suggest that UA could serve as a functional food-derived phytochemical with a multi-targeted efficacy on progression of OA, regulating the immune and inflammatory responses, particularly, attenuating chondrocytes degeneration via suppression of NF-κB and MMP-9/TIMP-1. Accordingly, UA might be a promising alternative to conventional therapy for safe, easily applicable and effective management of OA.

The characterization of traditional Chinese medicine natures and flavors using network pharmacology integrated strategy

Background and aim

Due to the complexity of TCM ingredients and medication compatibility, TCM cannot be used like chemical medicines. The theory of "Four Natures and five Flavors" provides a theoretical basis for the use of TCM. "Four Natures and five Flavors" are originated from pharmacological rules based on clinical practices. Whereas, How to describe and characterize "Natures"(Warm, Hot, Cold and Cool) and "Flavors" (Pungent, Sour, Sweet, Bitter and Salty) scientifically remain the issue that needs to be solved. The aim of this study is to establish the TCM characterization models based on the integrated pharmacology network strategy and provide a deeper understanding of TCM theory.

Experimental procedure

Five "Pungent-Neutral", nine "Sweet-Neutral and nine "Bitter-Neutral" TCMs were selected to characterize the "Flavors" (Pungent, Sweet and Bitter). Nine "Pungent-Warm" and nine "Bitter-Cold" TCMs were selected to characterize the "Natures" (Warm and Cold). The screened chemical ingredients were analyzed by classification and the screened characteristics targets were analyzed by GO and KEGG enrichment analysis.

Results and conclusion

In the "Pungent" group, flavonoids are the most. "Pungent" may have immune-regulatory effects and potential anticancer activity. In the "Sweet" group, isoflavones are the most. "Sweet" are related to effectively invigorate health. Fatty acids in the "Warm" group are the most. Flavonoids in the "Cold' group are far more than other components. "Warm" and "Cold" are both related to fatty acid and energy metabolism.

Jianpi-Yangxue-Jiedu decoction improves the energy metabolism of psoriasis mice by regulating the electron transfer of oxidative phosphorylation

ETHNOPHARMACOLOGICAL RELEVANCE

The inflammatory skin condition psoriasis is immune-related. The decoction of Jianpi-Yangxue-Jiiedu (JPYX) is a useful medication for psoriasis. However, the underlying mechanics of JPYX have not yet been clarified.

AIM OF THE STUDY

The objective of this study was to investigate the mechanism underlying the efficacy of JPYX in the treatment of psoriasis in the context of a high-fat diet.

MATERIALS AND METHODS

This work generated a high-fat feeding model of imiquimod (IMQ)-induced psoriasis-like lesion mice. The blood composition of JPYX was examined using ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). The mechanism of JPYX decoction for treating psoriasis was predicted using methods of network pharmacology, metabolomics, and transcriptomics.

RESULTS

JPYX prevented the release of inflammatory cytokines, decreased keratinocyte proliferation, enhanced the percentage of Treg cells in the skin, lymph nodes, and thymus, and greatly alleviated psoriatic lesions. Network pharmacology predicted that IL-1β, TNF, STAT3, and EGFR may be potential targets, and KEGG results showed that PI3K-AKT-mTOR may be a potential mechanism of action. Verification of experimental data demonstrated that the JPYX decoction dramatically decreased mTOR and AKT phosphorylation. According to metabolomics analysis, amino acids and their metabolites, benzene and its substitutes, aldehyde ketone esters, heterocyclic compounds, etc. were the primary metabolites regulated by JPYX. KEGG enrichment analysis of differential metabolites was performed. Fatty acid biosynthesis, Type I polyketide structures, Steroid hormone biosynthesis, Biosynthesis of unsaturated fatty acid, etc. Transcriptomic results showed that JPYX significantly regulated skin development, keratinocyte differentiation, and oxidative phosphorylation. Further experimental data verification showed that JPYX decoction significantly reduced the mRNA levels of mt-Nd4, mt-Nd5, mt-Nd1, Ifi205, Ifi211, and mt-Atp8.

CONCLUSIONS

JPYX may improve psoriasis by regulating the metabolic pathways of fatty acids and electron transport of oxidative phosphorylation.

Uncovering the pharmacological mechanism of Shou Tai Wan on recurrent spontaneous abortion: A integrated pharmacology strategy-based research

ETHNOPHARMACOLOGICAL RELEVANCE

Shou Tai Wan (STW), a traditional Chinese medicine formula, has been historically used for the treatment of recurrent spontaneous abortion (RSA). Despite its long-standing usage, the exact mechanism underlying the therapeutic effects of STW remains unclear in the existing literature.

AIMS OF THIS STUDY

To explore the Pharmacological Mechanism of STW on RSA.

METHODS

A network pharmacological methodology was utilized to predict the active compounds and potential targets of STW, collect the RSA targets and other human proteins of STW, and analyze the STW related networks. The animal experiments were also performed to validate the effect of STW on RSA.

RESULTS

The results of network analysis showed that STW may regulate PI3K/AKT, MAPK, FoxO signaling pathways and so on. Animal experiment established the RSA model with CBA/J × DBA/2 mice. It was found that STW can reduce the embryo absorption rate of RSA group (p < 0.05) and balance the expression of Th 1/Th2 type cytokines compared with the model group. After 14 days of administration, the decidual and placental tissues were taken and the CD4+ T cells were isolated, and the phosphorylation level of signaling pathway was detected by Springbio720 antibody microarray. This experiment found that STW can significantly up-regulate the phosphorylation levels of STAT3 and STAT6 proteins in the STAT signaling pathway, and down-regulating the phosphorylation level of STAT1 protein. STW also significantly up-regulated the phosphorylation levels of Raf1, A-Raf, Ask1, Mek1, Mek2, JKK1, ERK1, ERK2, c-fos, c-Jun and CREB proteins in the MAPK signaling pathway, and down-regulate the phosphorylation levels of MEK6 and IKKb proteins. Compared with the RSA group, the STW group increased the expression levels of ERK1/2 mRNA and proteins and p-ERK1/2 proteins, and there was a statistical difference (p < 0.05). This is consistent with the chip results.

CONCLUSION

STW may achieve therapeutic effects by interfering with the signaling pathways, biological processes and targets discovered in this study. It provides a new perspective for revealing the immunological mechanism of STW in the treatment of RSA, and also provides a theoretical basis for the clinical use of STW in the treatment of RSA.

Anti-rheumatoid arthritis potential of different fractions derived from of Coluria longifolia

Coluria longifolia Maxim (C. longifolia) is a Chinese folk medication commonly used to treat arthritis and joint pain. Literatures have reported that C. longifolia has significant anti-inflammatory, analgesic and antipyretic effects. The aim of this research was to assay the effective fractions of C. longifolia (EFCL) against rheumatoid arthritis (RA) and to elucidate its anti-RA mechanism on a preliminary basis. The rat model of collagen-induced arthritis (CIA) was established. The therapeutic effects of different fractions in vivo were evaluated by body weight changes, a foot swelling score, inflammatory factors and histopathological examination. The mechanism of EFCL was investigated by activity of oxidative stress related enzyme, qPCR and Western blotting tests. In vivo results showed that total extraction (TE) and n-butanol fraction (NF) could significantly alleviate the symptoms of RA, decrease the levels of IL-6 and TNF-α (P < 0.01), and improve histopathological injury. The mechanism study showed that SOD level was significantly increased with MDA level decreased in the NF group. The upregulated proteins and mRNA expression levels of Nrf2, HO1 and NQO1 after TE and NF administration suggested that the anti-arthritic effect may be related to the Nrf2 signaling pathway and downstream HO1 and NQO1. In conclusion, this study confirmed that C. longifolia is capable of treating RA with NF as the main effective fraction. Its anti-RA action may be associated with Nrf2 signaling pathway and downstream HO1 and NQO1.

Data-mining-based of ancient traditional Chinese medicine records from 475 BC to 1949 to potentially treat COVID-19

Traditional Chinese Medicine (TCM) plays a role in preventing and treating COVID-19 in China. Based on the manifestations and symptoms of COVID-19, our study used the data mining method to summarize related therapeutic experience left by predecessors who used TCM to treat epidemics in their eras. Initially, we collected abundant medical records with similar manifestations of COVID-19 in Chinese ancient times. The key words including wen (), yi (), li (), and zhang () were searched in ZhongyiZhiku (https://www.zk120.com/) from Warring States Period (475 BC-221 BC) to the Republic of China era (1912-1949) to locate ancient medical records according to inclusion criteria and exclusion criteria. Moreover, COVID-19-related manifestations and corresponding medications in those records were categorized. Eventually, Traditional Chinese Medicine Inheritance Support System version 2.5 was used to build a medical record database of TCM treating COVID-19. Our study collected 263 epidemic medical records comprising COVID-19 related manifestations and found that Chinese Materia Medica (CMM) combinations excavated from ancient medical records included Ren Shen Bai Du San, Wu Ling San, Xiao Chai Hu Tang, Da Cheng Qi Tang, Da Chai Hu Tang, Ling Gui Zhu Gan Tang, and Qing Wen Bai Du Yin. The recurrent CMMs with a high frequency for treating COVID-19 manifestations were Scutellariae Radix (Huang Qin), Paeoniae Alba Radix (Bai Shao), Poria (Fu Ling), and Bupleuri Radix (Chai Hu). Our study suggests that TCM might offer new therapeutic strategies for COVID-19.

Network pharmacology: towards the artificial intelligence-based precision traditional Chinese medicine

Network pharmacology (NP) provides a new methodological perspective for understanding traditional medicine from a holistic perspective, giving rise to frontiers such as traditional Chinese medicine network pharmacology (TCM-NP). With the development of artificial intelligence (AI) technology, it is key for NP to develop network-based AI methods to reveal the treatment mechanism of complex diseases from massive omics data. In this review, focusing on the TCM-NP, we summarize involved AI methods into three categories: network relationship mining, network target positioning and network target navigating, and present the typical application of TCM-NP in uncovering biological basis and clinical value of Cold/Hot syndromes. Collectively, our review provides researchers with an innovative overview of the methodological progress of NP and its application in TCM from the AI perspective.

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.

Evaluation of the Effect and Mechanism of Sanhuang Ointment on MRSA Infection in the Skin and Soft Tissue via Network Pharmacology

Introduction

Skin and soft tissue infection (SSTI) is a frequently encountered clinical disease, and Sanhuang ointment, a traditional Chinese medicine, is used to treat it. However, the pharmacological effect of Sanhuang ointment on SSTI and its underlying mechanism remains unclear. Here, we investigate the protective effect of Sanhuang ointment on Methicillin-resistant Staphylococcus aureus (MRSA) infection in the skin and soft tissues and the underlying mechanism by network pharmacological analysis, followed by in vivo experimental validation.

Methods

Via network pharmacology, the active components and disease targets of Sanhuang ointment were screened and intersected for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. A rat model of skin and soft tissue infection was established, and pathological features were observed. Large, medium, and small-dose groups (1 g, 0.5 g, and 0.25 g/animal, with the total amount of Vaseline, dispensed 1 g/animal) of Sanhuang ointment were prepared and Mupirocin ointment was used as a positive control (0.5 g/animal, with the total amount of Vaseline, dispensed 1 g/animal). The expressions of key proteins of the IL-17/NF-κB signaling pathway and downstream inflammatory factors were analyzed by histomorphological analysis, enzyme-linked immunosorbent assay, polymerase chain reaction, and Western blotting.

Results

In all, 119 active components and 275 target genes of Sanhuang ointment were identified and intersected with MRSA infection-related genes via network pharmacology analysis, and 34 target genes of Sanhuang ointment were found to be involved in skin and soft tissue infections with MRSA. Sanhuang ointment (1 g/mouse) could effectively ameliorate histopathological changes and significantly inhibit the expression of key proteins involved in the IL-17/NF-κB signaling pathway and downstream inflammatory factors (p < 0.05).

Conclusion

Sanhuang ointment has a protective effect on MRSA infection and inhibits inflammation by inhibiting the IL-17/NF-κB signaling pathway. Our findings are important for the secondary development and new drug development of Sanhuang ointment.

Homotherapy for heteropathy of Alzheimer's disease and anemia through reducing the expression of toll-like receptor and TNF by steamed Panax notoginseng

BACKGROUND

One of the effects of Steamed Panax notoginsen (SPN) is to replenish blood, which is mostly used to treat anemia in clinic. SPN has the effect of treating anemia and Alzheimer's disease (AD) in clinical and basic research. In traditional Chinese medicine, anemia and AD have the same characteristics, and their symptoms are qi and blood deficiency.

METHODS

First, data analysis was carried out through network pharmacology to predict the action targets of SPN homotherapy in the treatment of AD and anemia. Specifically, TCMSP and relevant literature were used to screen the main active ingredients of Panax notoginseng, and SuperPred was used to predict the action targets of the active ingredients. Disease targets related to AD and anemia were collected through Genecards database, and STRING and protein interaction (PPI) was used for enrichment analysis, Analyze the characteristics of the active ingredient target network on the Cytascape 3.9.0 platform, and use Metascape to enrich the gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes Pathway Enrichment (KEGG pathway). Then Drosophila was used as the AD animal model, and the effects of SPN on the climbing ability, olfactory memory and brain Aβ, with rats as anemia animal models, the improvement effect of SPN on blood routine and organ index of rats with blood deficiency induced by CTX and APH was analyzed to further explain the therapeutic effect of SPN on these two diseases. Finally, the regulatory effect of SPN on the key active target of allotherapy for AD and anemia was verified by PCR.

RESULTS

After the screening, 17 active components and 92 action targets of SPN were obtained. The degree values of components and the first 15 targets are NFKB1, IL10, PIK3CA, PTGS2, SRC, ECFR, CASP3, MTOR, IL1B, ESR1, AKT1, HSP90AA1, IL6, TNF, and Toll-like receptor, it is mainly related to inflammatory response, immune regulation and antioxidation. SPN improved the climbing ability, olfactory memory ability, and Aβ42 content in the brain of Aβ flies, and significantly reduced the expression of TNF and Toll-like receptor in the brain after treatment. SPN can significantly improve the blood routine index and organ index of anemia rats, and also significantly reduce the expression of TNF and Toll-like receptor in the brain after treatment.

CONCLUSION

SPN can regulate the expression of TNF and Toll-like receptor to achieve the same treatment of AD and anemia.

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.

Expanding potential targets of herbal chemicals by node2vec based on herb-drug interactions

BACKGROUND

The identification of chemical-target interaction is key to pharmaceutical research and development, but the unclear materials basis and complex mechanisms of traditional medicine (TM) make it difficult, especially for low-content chemicals which are hard to test in experiments. In this research, we aim to apply the node2vec algorithm in the context of drug-herb interactions for expanding potential targets and taking advantage of molecular docking and experiments for verification.

METHODS

Regarding the widely reported risks between cardiovascular drugs and herbs, Salvia miltiorrhiza (Danshen, DS) and Ligusticum chuanxiong (Chuanxiong, CX), which are widely used in the treatment of cardiovascular disease (CVD), and approved drugs for CVD form the new dataset as an example. Three data groups DS-drug, CX-drug, and DS-CX-drug were applied to serve as the context of drug-herb interactions for link prediction. Three types of datasets were set under three groups, containing information from chemical-target connection (CTC), chemical-chemical connection (CCC) and protein-protein interaction (PPI) in increasing steps. Five algorithms, including node2vec, were applied as comparisons. Molecular docking and pharmacological experiments were used for verification.

RESULTS

Node2vec represented the best performance with average AUROC and AP values of 0.91 on the datasets "CTC, CCC, PPI". Targets of 32 herbal chemicals were identified within 43 predicted edges of herbal chemicals and drug targets. Among them, 11 potential chemical-drug target interactions showed better binding affinity by molecular docking. Further pharmacological experiments indicated caffeic acid increased the thermal stability of the protein GGT1 and ligustilide and low-content chemical neocryptotanshinone induced mRNA change of FGF2 and MTNR1A, respectively.

CONCLUSIONS

The analytical framework and methods established in the study provide an important reference for researchers in discovering herb-drug interactions, alerting clinical risks, and understanding complex mechanisms of TM.

Mechanisms of Ganweikang Tablets against Chronic Hepatitis B: A Comprehensive Study of Network Analysis, Molecular Docking, and Chemical Profiling

The hepatitis B virus (HBV) is one of the major viral infection problems worldwide in public health. The exclusive proprietary Chinese medicine Ganweikang (GWK) tablet has been marketed for years in the treatment of chronic hepatitis B (CHB). However, the pharmacodynamic material basis and underlying mechanism of GWK are not completely clear. This study is aimed at investigating the pharmacological mechanism of the GWK tablet in the treatment of CHB. The chemical ingredient information was obtained from the Traditional Chinese Medicine Database and Analysis Platform (TCMSP), Traditional Chinese Medicines Integrated Database (TCMID), and Shanghai Institute of Organic Chemistry of CAS. Ingredients and disease-related targets were defined by a combination of differentially expressed genes from CHB transcriptome data and open-source databases. Target-pathway-target (TPT) network analysis, molecular docking, and chemical composition analysis were adopted to further verify the key targets and corresponding active ingredients of GWK. Eight herbs of GWK were correlated to 330 compounds with positive oral bioavailability, and 199 correlated targets were identified. The TPT network was constructed based on the 146 enriched targets by KEGG pathway analysis, significantly associated with 95 pathways. Twenty-five nonvolatile components and 25 volatile components in GWK were identified in UPLC-QTOF/MS and GC-MS chromatograms. The key active ingredients of GWK include ferulic acid, oleanolic acid, ursolic acid, tormentic acid, 11-deoxyglycyrrhetic acid, dibenzoyl methane, anisaldehyde, wogonin, protocatechuic acid, psoralen, caffeate, dimethylcaffeic acid, vanillin, β-amyrenyl acetate, formonentin, aristololactam IIIa, and 7-methoxy-2-methyl isoflavone, associated with targets CA2, NFKB1, RELA, AKT1, JUN, CA1, CA6, IKBKG, FOS, EP300, CREB1, STAT1, MMP9, CDK2, ABCB1, and ABCG2.

Network Pharmacology Was Used to Predict the Active Components and Prospective Targets of Paeoniae Radix Alba for Treatment in Endometriosis

Endometriosis is one of the most common benign gynecologic diseases. Paeoniae Radix Alba (PRA) has been utilized to treat endometriosis. We wished to identify potential targets for PRA in the treatment of endometriosis, as well as to provide a groundwork for future studies into its pharmacological mechanism of action. Network pharmacology was employed to conduct investigations on PRA. Target proteins were chosen from the components of PRA for endometriosis treatment. A protein-protein interaction (PPI) was established using overlapping genes. Analyses of enrichment of function and signaling pathways were undertaken using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes databases to select "hub genes." Finally, the feasibility of analysis based on network pharmacology was determined using real-time reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and western blotting. We demonstrated that PRA has 25 bioactive components and 167 putative targets that are therapeutically important. The anti-inflammatory and immune-boosting actions of tumor necrosis factor, albumin, signal transducer and activator of transcription (STAT)3, mitogen-activated protein kinase, Jun, interleukin (IL)-1B, prostaglandin-endoperoxide synthase 2, matrix metalloproteinase-9, vascular endothelial growth factor A, and IL-6 were identified as prospective targets. Seven major compounds in PRA and related to the STAT3 pathway could bind spontaneously to it. RT-qPCR and western blotting showed that expression of STAT3 and phospho-STAT3 was reduced significantly after PRA intervention. Hence, analyses of the active components of traditional Chinese medicine formulations through network pharmacology may open up new ideas for the treatment of diseases.

Insights into the mechanisms of triptolide nephrotoxicity through network pharmacology-based analysis and RNA-seq

INTRODUCTION

Triptolide (TPL) is a promising plant-derived compound for clinical therapy of multiple human diseases; however, its application was limited considering its toxicity.

METHODS

To explore the underlying molecular mechanism of TPL nephrotoxicity, a network pharmacology based approach was utilized to predict candidate targets related with TPL toxicity, followed by deep RNA-seq analysis to characterize the features of three transcriptional elements include protein coding genes (PCGs), long noncoding RNAs (lncRNAs) and circular RNAs (circRNAs) as well as their associations with nephrotoxicity in rats with TPL treatment.

RESULTS & DISCUSSION

Although the deeper mechanisms of TPL nephrotoxcity remain further exploration, our results suggested that c-Jun is a potential target of TPL and Per1 related circadian rhythm signaling is involved in TPL induced renal toxicity.

Withdrawn: A data-mining based analysis of traditional Chinese medicine in diagnosing and treating COVID-19

Yongshen Fan, Ting Zhao, Yaxue Han, Zi Yang, Shan Fang, Mengqing Zhang, Zhijun Xie, A data-mining based analysis of traditional Chinese medicine in diagnosing and treating COVID-19, The Anatomical Record: Advances in Integrative Anatomy and Evolutionary Biology 2021, (https://doi.org/10.1002/ar.24677). The above article, published online on 24 June 2021 in Wiley Online Library (wileyonlinelibrary.com), has been withdrawn by agreement between the journal Editor-in-Chief, Heather F. Smith, Ph.D., the American Association for Anatomy, and Wiley Periodicals LLC. The authors have been notified of the decision to withdraw the article. The decision is based on concerns raised by a third party. The Editor-in-Chief considers the conclusions of the paper compromised and has initiated an investigation.

Network pharmacology and experimental validation to identify the potential mechanism of Hedyotis diffusa Willd against rheumatoid arthritis

Rheumatoid arthritis (RA) is a chronic, systemic, autoimmune disease that may lead to joint damage, deformity, and disability, if not treated effectively. Hedyotis diffusa Willd (HDW) and its main components have been widely used to treat a variety of tumors and inflammatory diseases. The present study utilized a network pharmacology approach, microarray data analysis and molecular docking to predict the key active ingredients and mechanisms of HDW against RA. Eleven active ingredients in HDW and 180 potential anti-RA targets were identified. The ingredients-targets-RA network showed that stigmasterol, beta-sitosterol, quercetin, kaempferol, and 2-methoxy-3-methyl-9,10-anthraquinone were key components for RA treatment. KEGG pathway results revealed that the 180 potential targets were inflammatory-related pathways with predominant enrichment of the AGE-RAGE, TNF, IL17, and PI3K-Akt signaling pathways. Screened through the PPI network and with Cytoscape software, RELA, TNF, IL6, TP53, MAPK1, AKT1, IL10, and ESR1 were identified as the hub targets in the HDW for RA treatment. Molecular docking was used to identify the binding of 5 key components and the 8 related-RA hub targets. Moreover, the results of network pharmacology were verified by vitro experiments. HDW inhibits cell proliferation in MH7A cells in a dose and time-dependent manner. RT-qPCR and WB results suggest that HDW may affect hub targets through PI3K/AKT signaling pathway, thereby exerting anti-RA effect. This study provides evidence for a clinical effect of HDW on RA and a research basis for further investigation into the active ingredients and mechanisms of HDW against RA.

Exploring the active ingredients and potential mechanisms of action of sinomenium acutum in the treatment of rheumatoid arthritis based on systems biology and network pharmacology

Objective: To investigate and predict the targets and signaling pathways of sinomenium acutum (SA) in the treatment of rheumatoid arthritis (RA) through systems biology and network pharmacology, and to elucidate its possible mechanisms of action. Methods: We screened the active ingredients and corresponding target proteins of SA in Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), Traditional Chinese Medicines Integrated Database (TCMID) and Bioinformatics Analysis Tool for Molecular mechANism of Traditional Chinese Medicine (BATMAN); and obtained the targets of rheumatoid arthritis diseases in a database of gene-disease associations (DisGeNET), Online Mendelian Inheritance in Man (OMIM) database. The two targets were mapped by Venn diagram and the intersection was taken. The intersecting targets were used to construct protein-protein interaction (PPI) network maps in the String database, and Metascape was used for Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. Finally, the molecular docking technique was applied to validate and further clarify the core target of SA for the treatment of rheumatoid arthritis. Results: A total of six active ingredients and 217 potential targets were obtained after screening; 2,752 rheumatoid arthritis-related targets and 66 targets common to RA and SA. GO function and KEGG pathway enrichment analysis yielded 751 GO function entries (652 GO biological processes, 59 GO molecular functions and 40 GO cellular components) and 77 KEGG signaling pathways. It mainly involves pathways related to neural activity ligand-receptor interaction pathways, cancer pathways, calcium signaling channels, Th17 cell differentiation and others, which are mainly classified into four categories, including regulation of immunity, anti-inflammation, regulation of cell growth and apoptosis, and signaling. The molecular docking results showed that the binding energy of PTGS2, CASP3, JUN and PPARG to the key components beta-sitosterol, 16-epi-Isositsirikine, Sinomenine and Stepholidine were ≤ -6.5 kcal/mol, suggesting the existence of molecular binding sites. Conclusion: SA acts on key targets such as PTGS2, CASP3, JUN, and PPARG to modulate signaling pathways such as neural activity ligand-receptor interaction, cancer, calcium ion, NF-κB, and Th17 cell differentiation to regulate immunity, anti-inflammation, modulation of cell cycle, bone metabolism, and signaling for the treatment of RA. It was also confirmed that the treatment of RA with SA has multi-component, multi-target, multi-pathway and multi-mechanism characteristics.

The mechanism of Bai He Gu Jin Tang against non-small cell lung cancer revealed by network pharmacology and molecular docking

BACKGROUND

Non-small cell lung cancer (NSCLC) is a leading cause of cancer-related burden and deaths, thus effective treatment strategies with lower side effects for NSCLC are urgently needed. To systematically analyze the mechanism of Bai He Gu Jin Tang (BHGJT) against NSCLC by network pharmacology and molecular docking.

METHODS

The active compounds of BHGJT were obtained by searching the Bioinformatics Analysis Tool for Molecular Mechanism of Traditional Chinese Medicine and Encyclopaedia of Traditional Chinese Medicine. Search tool for interactions of chemicals was used for acquiring the targets of BHGJT. The component-target network was mapped by Cytoscape. NSCLC-related genes were obtained by searching Genecards, DrugBank and Therapeutic Target Database. The protein-protein interaction network of intersection targets was established based on Search Tool for Recurring Instances of Neighboring Genes (STRING), and further, the therapeutic core targets were selected by topological parameters. The hub targets were transmitted to Database for Annotation, Visualization and Integrated Discovery for gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Finally, AutoDock Vina and MglTools were employed for molecular docking validation.

RESULTS

Two hundred fifty-six compounds and 237 putative targets of BHGJT-related active compounds as well as 1721potential targets of NSCLC were retrieved. Network analysis showed that 8 active compounds of BHGJT including kaempferol, quercetin, luteolin, isorhamnetin, beta-sitosterol, stigmasterol, mairin and liquiritigenin as well as 15 hub targets such as AKR1B10 and AKR1C2 contribute to the treatment of BHGJT against NSCLC. GO functional enrichment analysis shows that BHGJT could regulate many biological processes, such as apoptotic process. Three modules of the endocrine related pathways including the inflammation, hypoxia related pathways as well as the other cancer related pathways based on Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis might explain the biological mechanisms of BHGJT in treating BHGJT. The results of molecular docking verified that AKR1B10 and AKR1C2 had the strongest binding activity with the 8 key compounds of NSCLC.

CONCLUSION

Our study reveals the mechanism of BHGJT in treating NSCLC involving multiple components, multiple targets and multiple pathways. The present study laid an initial foundation for the subsequent research and clinical application of BHGJT and its active compounds against NSCLC.

Potential bioactive compounds and mechanisms of Fibraurea recisa Pierre for the treatment of Alzheimer's disease analyzed by network pharmacology and molecular docking prediction

Introduction

Heat-clearing and detoxifying Chinese medicines have been documented to have anti-Alzheimer's disease (AD) activities according to the accumulated clinical experience and pharmacological research results in recent decades. In this study, Fibraurea recisa Pierre (FRP), the classic type of Heat-clearing and detoxifying Chinese medicine, was selected as the object of research.

Methods

12 components with anti-AD activities were identified in FRP by a variety of methods, including silica gel column chromatography, multiple databases, and literature searches. Then, network pharmacology and molecular docking were adopted to systematically study the potential anti-AD mechanism of these compounds. Consequently, it was found that these 12 compounds could act on 235 anti-AD targets, of which AKT and other targets were the core targets. Meanwhile, among these 235 targets, 71 targets were identified to be significantly correlated with the pathology of amyloid beta (Aβ) and Tau.

Results and discussion

In view of the analysis results of the network of active ingredients and targets, it was observed that palmatine, berberine, and other alkaloids in FRP were the key active ingredients for the treatment of AD. Further, Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis revealed that the neuroactive ligand-receptor interaction pathway and PI3K-Akt signaling pathway were the most significant signaling pathways for FRP to play an anti-AD role. Findings in our study suggest that multiple primary active ingredients in FRP can play a multitarget anti-AD effect by regulating key physiological processes such as neurotransmitter transmission and anti-inflammation. Besides, key ingredients such as palmatine and berberine in FRP are expected to be excellent leading compounds of multitarget anti-AD drugs.

Explore the mechanism and substance basis of Mahuang FuziXixin Decoction for the treatment of lung cancer based on network pharmacology and molecular docking

BACKGROUND

Mahuang FuziXixin Decoction (MFXD) is a classic Chinese herbal formula for the treatment of lung cancer. However, its mechanisms of action are unclear. In present study, network pharmacology and molecular docking technology were employed to investigate the molecular mechanism and substance basis of MFXD for the treatment of lung cancer.

METHOD

The active compounds and corresponding targets of MFXD were collected through the TCMSP database. OMIM and GeneCards databases were applied to filter the targets of lung cancer. The protein-protein interaction (PPI) were acquired through the STRING platform. Metascape and the Bioinformatics server were used for the visualization of GO and KEGG analysis. The tissue and organ distribution of targets was evaluated based on the BioGPS database. The binding affinity between potential targets and active compounds was evaluated by molecular docking.

RESULT

A total of 51 active compounds and 118 targets of MFXD were collected. The target with a higher degree were identified through the PPI network, namely AR, RELA, NCOA1, EGFR, FOS, CCND1, ESR1 and HSP90AA1. GO and KEGG analysis suggested that MFXD treatment of lung cancer mainly involves hormone and response to inorganic substance, transcription regular complex, transcription factor binding and Pathways in cancer. Experimental validation showed that MFXD treatment inhibited the proliferation of NSCLC cells through downregulation the expression of EGFR, HIF1A, NCOA1 and RELA. Moreover, molecular docking revealed that hydrogen bond and hydrophobic interaction contribute to the binding of the compounds to targets.

CONCLUSION

Our findings comprehensively elucidated the actives, potential targets, and molecular mechanisms of MFXD against lung cancer, providing a promising strategy for the scientific basis and therapeutic mechanism of traditional Chinese medicine prescriptions for the treatment of the disease.

Disease-related compound identification based on deeping learning method

Acute lung injury (ALI) is a serious respiratory disease, which can lead to acute respiratory failure or death. It is closely related to the pathogenesis of New Coronavirus pneumonia (COVID-19). Many researches showed that traditional Chinese medicine (TCM) had a good effect on its intervention, and network pharmacology could play a very important role. In order to construct "disease-gene-target-drug" interaction network more accurately, deep learning algorithm is utilized in this paper. Two ALI-related target genes (REAL and SATA3) are considered, and the active and inactive compounds of the two corresponding target genes are collected as training data, respectively. Molecular descriptors and molecular fingerprints are utilized to characterize each compound. Forest graph embedded deep feed forward network (forgeNet) is proposed to train. The experimental results show that forgeNet performs better than support vector machines (SVM), random forest (RF), logical regression (LR), Naive Bayes (NB), XGBoost, LightGBM and gcForest. forgeNet could identify 19 compounds in Erhuang decoction (EhD) and Dexamethasone (DXMS) more accurately.

Study on the mechanism of Jin Gui Shen Qi Pill in the treatment of erectile dysfunction based on bioinformatics analysis

Erectile dysfunction (ED) is a male disease, which is easy to cause disharmony in sexual life. However, at present, there are few drugs with small side effects in clinic. Jin Gui Shen Qi Pill (JGSQP) is a traditional Chinese medicine compound with obvious clinical effect in treating ED. Therefore, it is imperative to explore clinical drugs based on inhibiting the pathological characteristics of ED. First, the active ingredients and action targets in JGSQP were screened by applying Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and SWISS Target Prediction. Further, a systematic pharmacological analysis platform for traditional Chinese medicine, and the ED targets were screened by applying Gene Cards and Online Mendelian Inheritance in Man databases to construct drug active ingredient-target-disease mapping, followed by gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and protein-protein interaction (PPI) network analysis. Finally, Molecular docking and molecular dynamics simulations were used to screen the active ingredients of JGSQP acting on PDE-5, and analyze the ligand-receptor interaction relationship and binding free energy. The results showed that there were 212 potential targets of JGSQP for ED disease, and GO analysis revealed that the main pathways were positive regulation of DNA-binding transcription factor activity, regulation of vascular diameter, and negative regulation of vascular diameter, etc. KEGG analysis revealed that the main pathways were HIF-1 signaling pathway, prolactin signaling pathway, fluid shear stress, and atherosclerosis, etc. PPI network analysis revealed that the core targets TGFB1 and EGFR have important roles. Molecular docking and molecular dynamics simulations showed that the main components acting on PDE-5 were MOL000546, MOL011169, MOL000279, MOL000273 and Sildenafil. MOL000546 was able to bind stably to PDE-5. The multi-component, multi-target, and multi-pathway action characteristics of JGSQP were confirmed by network pharmacology, which predicted the possible mechanism of action of JGSQP in the treatment of ED and provided a theoretical reference for further experimental validation.

An optimal medicinal and edible Chinese herbal formula attenuates particulate matter-induced lung injury through its anti-oxidative, anti-inflammatory and anti-apoptosis activities

Objective

Identifying novel strategies to prevent particulate matter (PM)-induced lung injury is crucial for the reduction of the morbidity of chronic respiratory diseases. The combined intervention represented by herbal formulae for simultaneously targeting multiple pathological processes can provide a more beneficial effect than the single intervention. The aim of this paper is therefore to design a safe and effective medicinal and edible Chinese herbs (MECHs) formula against PM-induced lung injury.

Methods

PM-induced oxidative stress, inflammatory response and apoptosis A549 cell model were used to screen anti-oxidant, anti-inflammatory and anti-apoptotic MECHs, respectively. A network pharmacology method was utilized to rationally design a novel herbal formula. Ultra performance liquid chromatography-mass spectrometer was utilized to assess the quality control of MECHs formula. The excretion of magnetic iron oxide nanospheres of the MECHs formula was estimated in zebrafish. The MECH formula against PM-induced lung injury was investigated with mice experiments.

Results

Five selected herbs were rationally designed to form a new MECH formula, including Citri Exocarpium Rubrum (Juhong), Lablab Semen Album (Baibiandou), Atractylodis Macrocephalae Rhizoma (Baizhu), Mori Folium (Sangye) and Polygonati Odorati Rhizoma (Yuzhu). The formula effectively promoted the magnetic iron oxide nanospheres excretion in zebrafish. The mid/high dose formula significantly prevented PM-induced lung damage in mice by enhancing the activity of SOD and GSH-Px, reducing the MDA and ROS level and attenuating the upregulation of pro-inflammatory cytokine (IL-6, IL-8, IL-1β and TNF-α), down regulating the protein expression of NF-κB, STAT3 and Caspase-3.

Conclusion

Our findings suggest that the effective MECHs formula will become a novel strategy for preventing PM-induced lung injury and provide a paradigm for the development of functional foods using MECHs.

Multi-omics approaches for deciphering the complexity of traditional Chinese medicine syndromes in stroke: A systematic review

Background: Deciphering the biological basis of traditional Chinese medicine (TCM) syndromes in complex diseases is challenging. Rapid advances in multi-omics approaches provide new opportunities to unveil the biological basis of TCM syndromes. We intend to summarize the latest significant progress and highlight the crucial value of applying multi-omics approaches to reveal TCM syndromes of stroke in a new horizon.

Methods: We systematically searched PubMed, EMBASE, Web of Science Core Collection (WOSCC), Cochrane Library, China National Knowledge Infrastructure (CNKI), Chinese Science and Technology Periodical Database (VIP), Wanfang database and China Biology Medicine Database (SinoMed) for relevant studies from their inception to 31 March 2022, and conducted a comprehensive systematic review (PROSPERO registration number: CRD42021285922).

Results: A total of 43 relevant studies were included in the final systematic review, genomics, transcriptomics, proteomics, and metabolomics were all involved. Some gene polymorphisms, differential lncRNAs, mRNAs, miRNAs, proteins, and metabolites may be associated with TCM syndromes of stroke. In addition, some studies conducted a preliminary exploration on the different diseases with the same TCM syndrome. The results showed that thioredoxin-dependent peroxidase reductase may be the specific marker protein of Liver-yang transforming into wind syndrome, and the network formed by mir-146b-5p, -199a-5p, and 23 targeted mRNAs may be the biomarker of Blood-stasis syndrome.

Conclusion: Multi-omics technologies have served as powerful tools to investigate the complexity of TCM syndromes and may hold the promise of promoting the modernization of TCM as well as personalized medicine of TCM in stroke.

Network Pharmacology of Adaptogens in the Assessment of Their Pleiotropic Therapeutic Activity

The reductionist concept, based on the ligand–receptor interaction, is not a suitable model for adaptogens, and herbal preparations affect multiple physiological functions, revealing polyvalent pharmacological activities, and are traditionally used in many conditions. This review, for the first time, provides a rationale for the pleiotropic therapeutic efficacy of adaptogens based on evidence from recent gene expression studies in target cells and where the network pharmacology and systems biology approaches were applied. The specific molecular targets and adaptive stress response signaling mechanisms involved in nonspecific modes of action of adaptogens are identified.

Herb-anticancer drug interactions in real life based on VigiBase, the WHO global database

Cancer patients could combine herbal treatments with their chemotherapy. We consulted VigiBase, a WHO database of individual case safety reports (ICSRs) which archives reports of suspected Adverse Drug Reactions (ADRs) when herbal products are used in conjunction with anti-cancer treatment. We focused on the possible interactions between antineoplastic (L01 ATC class) or hormone antagonists (L02B ATC class) with 10 commonly used herbs (pineapple, green tea, cannabis, black cohosh, turmeric, echinacea, St John’s wort, milk thistle and ginger) to compare ADRs described in ICSRs with the literature. A total of 1057 ICSRs were extracted from the database but only 134 were complete enough (or did not concern too many therapeutic lines) to keep them for analysis. Finally, 51 rationalizable ICSRs could be explained, which led us to propose a pharmacokinetic or pharmacodynamic interaction mechanism. Reports concerned more frequently women and half of the rationalizable ICSRs involved Viscum album and Silybum marianum. 5% of the ADRs described could have been avoided if clinicians had had access to the published information. It is also important to note that in 8% of the cases, the ADRs observed were life threatening. Phytovigilance should thus be considered more by health care professionals to best treat cancer patients and for better integrative care.

An integrative approach to uncover the components, mechanisms, and functions of traditional Chinese medicine prescriptions on male infertility

Male infertility is a major and growing health problem with an estimated global prevalence of 4.2%. The current therapy is limited by the unknown etiology of MI, emphasizing the critical requirement forward to a more efficient method or medication. Through thousands of years, Traditional Chinese Medicine (TCM) has been shown to be effective in treating MI effectively. However, the components, mechanisms and functions of TCM prescriptions on MI are still obscure, severely limiting its clinical application. In order to discover the molecular mechanism of TCM against MI, our study presents a comprehensive approach integrated data mining, network pharmacology, molecular docking, UHPLC-Q-Orbitrap HRMS, and experimental validation. Here, we begin to acquire 289 clinical TCM prescriptions for MI from a TCM hospital’s outpatient department. Then, Core Chinese Materia Medica (CCMM) was then retrieved from the TCM Inheritance Support System (TCMISS), which was utilized to discover the underlying rules and connections in clinical prescriptions. After that, 98 CCMM components and 816 MI targets were obtained from ten distinct databases. Additionally, the network pharmacology methods, including network construction, GO and KEGG pathway enrichment, PPI analysis, were utilized to reveal that kaempferol, quercetin, isorhamnetin, and beta-sitosterol are the core components of CCMM in treating MI. The mechanisms and functions of CCMM against MI are hormone regulation, anti-apoptosis, anti-oxidant stress, and anti-inflammatory. Furthermore, the strong connections between four core components and six key targets were verified using a molecular docking method. Following that, the core components of the CCMM extract were identified using UHPLC-Q-Orbitrap HRMS analysis. Finally, in vivo experiments demonstrated that CCMM and four core components could improve the density, motility, viability of sperm, lecithin corpuscle density, decrease the rate of sperm malformation and testis tissue damage, and regulate the protein expressions of AKT1, MAPK3/1, EGFR, and TNF-α in a mouse model of MI. UHPLC-Q-Orbitrap HRMS analysis and in vivo experiments further validated the results of data mining, network pharmacology, and molecular docking. Our study could uncover the components, mechanisms, and functions of TCM prescriptions against MI and develop a new integrative approach to demonstrate TCM’s multi-component, multi-target, and multi-pathway approach to disease treatment.

Systems pharmacology, proteomics and in vivo studies identification of mechanisms of cerebral ischemia injury amelioration by Huanglian Jiedu Decoction

ETHNOPHARMACOLOGICAL RELEVANCE

Huanglian Jiedu Decoction (HLJDD) has the effect of clearing heat and detoxifying, and has been considered as an effective prescription for cerebral ischemia (CI) for thousands of years in traditional Chinese medicine (TCM). It can improve the quality of life of patients with ischemic stroke, but its pharmacological mechanism remains unclear.

AIM OF THE STUDY

The study aimed to explore the pharmacological action and potential mechanism of HLJDD against CI by systems pharmacology, proteomics and in vivo experiments.

MATERIALS AND METHODS

In this study, databases such as TCMIP V2.0 and Genecards were used to predict compounds, targets and CI related targets, and network topology criteria of protein-protein interaction (PPI) network was used to screen core targets. The Database for Annotation, Visualization and Integrated Discovery database (DAVID) was used to discover biological processes and pathways. In addition, molecular docking was performed between the screened core biological active compounds and targets to verify the binding activity. Finally, proteomics and Western blot were performed on cerebral cortex tissues of middle cerebral artery occlusion (MCAO) model rats with HLJDD intervention to further verify the predicted results.

RESULTS

77 compounds and 308 targets of HLJDD were identified, 54 of which were predicted to be associated with cerebral ischemia. PPI network and enrichment results showed that 8 targets, including AKT1, PTGS2 and TLR4, were core targets of HLJDD in CI. And 19 signaling pathways, including Rap1 signaling pathway, cAMP signaling pathway and arachidonic acid metabolism, were identified as key pathways to the therapeutic activity of HLJDD in CI. Combined with proteomics studies, we identified that Rap1 signaling pathway and upstream and downstream targets were the key mechanisms. Molecular biology experiments showed that RAP1A and AKT expression levels were significantly up-regulated in middle cerebral artery occlusion (MCAO) rats treated with HLJDD (P < 0.0001), GRIN1 expression level was significantly down-regulated (P < 0.0001). However, ACTB expression level was slightly down-regulated (P > 0.05), which may be related to the biological function.

CONCLUSION

This study confirms the pharmacological effect of HLJDD on cerebral ischemia. These results indicate that HLJDD mediates various pathways such as inhibition of apoptosis, regulation of oxygen balance, inhibition of excitatory toxicity and maintenance of basic cell functions to improve CI by regulating Rap1 signaling pathway.

Mechanisms of Action of Semen Ziziphi spinosae in the Treatment of Tourette Syndrome

Background

Semen Ziziphi spinosae, known as Suanzaoren (SZR) in Chinese, is a Chinese herbal medicine widely used in sedatives and tranquilizers. Although SZR is important for the clinical treatment of Tourette syndrome (TS), its mechanism of action remains unclear. Therefore, we investigated the pharmacological mechanisms of SZR in TS treatment using network pharmacology and systems biology approaches.

Methods

The bioactive components and potential targets of SZR were screened using the TCMSP database. UniProt was used to identify targets by mapping the known genes related to SZR. The known genes related to TS were identified by GeneCards and OMIM databases. A protein-protein interaction network was constructed using information from STRING 11.0 database. Cytoscape 3.8.0 software and Bioinformatics online platform were used for plotting this network. Gene ontology and KEGG enrichment analyses were performed using Metascape. Finally, AutoDock was used to verify the molecular docking.

Results

We found that SZR had 10 active compounds. There were 30 overlapping target genes between TS and SZR. These genes were associated with several signaling and metabolic pathways. AChE, SLC6A4, and HTR3A were the top three hub genes. The active components in SZR had a high binding affinity for the key targets.

Conclusion

SZR therapy for TS could achieve network regulation through the action of various active components of Chinese medicine on different targets and generate a complex regulatory relationship via interaction with potential targets, thereby playing a therapeutic role. Thus, SZR is a potential candidate for treating TS because it regulates nervous system functions.

Network pharmacology combined with GEO database identifying the mechanisms and molecular targets of Polygoni Cuspidati Rhizoma on Peri-implants

Peri-implants is a chronic disease leads to the bone resorption and loss of implants. Polygoni Cuspidati Rhizoma (PCRER), a traditional Chinese herbal has been used to treat diseases of bone metabolism. However, its mechanism of anti-bone absorption still remains unknown. We aimed to identify its molecular target and the mechanism involved in PCRER potential treatment theory to Peri-implants by network pharmacology. The active ingredients of PCRER and potential disease-related targets were retrieved from TCMSP, Swiss Target Prediction, SEA databases and then combined with the Peri-implants disease differential genes obtained in the GEO microarray database. The crossed genes were used to protein–protein interaction (PPI) construction and Gene Ontology (GO) and KEGG enrichment analysis. Using STRING database and Cytoscape plug-in to build protein interaction network and screen the hub genes and verified through molecular docking by AutoDock vina software. A total of 13 active compounds and 90 cross targets of PCRER were selected for analysis. The GO and KEGG enrichment analysis indicated that the anti-Peri-implants targets of PCRER mainly play a role in the response in IL-17 signaling, Calcium signaling pathway, Toll-like receptor signaling pathway, TNF signaling pathway among others. And CytoHubba screened ten hub genes (MMP9, IL6, MPO, IL1B, SELL, IFNG, CXCL8, CXCL2, PTPRC, PECAM1). Finally, the molecular docking results indicated the good binding ability with active compounds and hub genes. PCRER’s core components are expected to be effective drugs to treat Peri-implants by anti-inflammation, promotes bone metabolism. Our study provides new thoughts into the development of natural medicine for the prevention and treatment of Peri-implants.

Methodology improvement for network pharmacology to correct the deviation of deduced medicinal constituents and mechanism: Xian-Ling-Gu-Bao as an example

ETHNOPHARMACOLOGICAL RELEVANCE

Network pharmacology is extremely adaptive for investigating traditional ethnic drugs, especially the herbal medicines. However, challenges still hang over many related studies due to the limitations in the methodology of conventional network pharmacology.

AIM OF THE STUDY

Our work was aimed to investigate the methodology limitations of conventional network pharmacology with Xian-Ling-Gu-Bao (XLGB) as a representative, meanwhile, propose the strategies for coping with these issues.

MATERIALS AND METHODS

Predicted phytochemical constituents formed virtual XLGB. The constituents in realistic XLGB samples was detected by liquid chromatography-mass spectrometry (LC-MS) to correct the constituent deviation resulted from virtual prediction. Multivariate statistical analysis of quantitative target data were used to reveal the relation of target profile between drug and disease. The key constituents and targets were screened and compared between virtual and realistic XLGB through network analysis. After enrichment analysis, reversing network pharmacology was performed to exclude weak targets and re-construct the interaction from key pathways to key targets. Finally, the core constituents and action mechanism of XLGB were deduced.

RESULTS

Significant deviation of phytochemical constituents was found between virtual and realistic XLGB. As expected, this deviation led to a cascade of deviation ranging from deduced key constituents to key targets and key pathways. Moreover, many key KEGG pathways were enriched and screened out, however, they were almost irrelevant to the studied disease. These results systemically illustrated the limitations in the methodology of conventional network pharmacology. Importantly, the strategies for coping with these limitations were proposed, such as high-throughput detection of the realistic samples, multivariate analysis of target profile and combined enrichment analysis. Finally, based on the improved network pharmacology, the medicinal constituents and mechanism of XLGB against osteoarthritis were effectively deduced.

CONCLUSIONS

Our work highlighted the necessity and proposed the strategies for improving the methodology of conventional network pharmacology. The corrected results from improved network pharmacology provided promising directions for future research on XLGB.

Prediction of the Active Components and Possible Targets of Xanthii Fructus Based on Network Pharmacology for Use in Chronic Rhinosinusitis

Chronic rhinosinusitis (CRS) is a complex condition brought on for many reasons, and its prevalence is rising gradually around the world. Xanthii Fructus (XF) has been used in the treatment of CRS for decades and is effective. The chemical and pharmacological profiles of XF, on the other hand, are still unknown and need to be clarified. The potential mechanisms of XF in CRS treatment were investigated using a network pharmacology approach in this study. OB and DL were in charge of screening the bioactive components in XF and drug-likeness. TCMSP and PubChem databases were used to identify prospective XF proteins, whereas GeneCards and the DisGeNET database were used to identify potential CRS genes. An interactive network of XF and CRS is built using the STRING database based on common goals identified by the online tool Venny. Cytoscape was used to visualize the topological characteristics of nodes, while the biological function pathways were identified by GO Knowledge Base, KEGG. There were 26 bioactive components and 115 potential targets in XF that bind to CRS or are considered therapeutically relevant. Five significant signaling pathways have been found for CRS by the pathway analysis including the HIF-1 signaling pathway, TNF signaling pathway, Toll-like receptor signaling pathway, NOD-like receptor signaling pathway, and PI3K-Akt signaling pathway. We simultaneously confirmed that the PI3K-Akt pathway promotes the development of CRS. Finally, this study took a holistic approach to the pharmacological actions and molecular mechanisms of XF in the treatment of CRS. TNF, INS, CCL2, CXCL8, IL-10, VEGFA, and IL-6 have all been identified as potential targets for anti-inflammatory and immune-boosting effects. This network pharmacology prediction could be useful in manifesting the molecular mechanisms of the Chinese herbal compound XF for CRS.

Identification of the potential mechanism of Radix pueraria in colon cancer based on network pharmacology

Radix Puerariae (RP), a dry root of Pueraria lobata (Willd.) Ohwi, is used to treat a variety of diseases, including cancer. Several in vitro and in vivo studies have demonstrated the efficacy of RP in the treatment of colon cancer (CC). However, the biological mechanism of RP in the treatment of colon cancer remains unclear. In this study, the active component of RP and its potential molecular mechanism against CC were studied by network pharmacology and enrichment analysis. The methods adopted included screening active ingredients of Chinese medicine, predicting target genes of Chinese medicine and disease, constructing of a protein interaction network, and conducting GO and KEGG enrichment analysis. Finally, the results of network pharmacology were further validated by molecular docking experiments and cell experiments. Eight active constituents and 14 potential protein targets were screened from RP, including EGFR, JAK2 and SRC. The biological mechanism of RP against CC was analysed by studying the relationship between active components, targets, and enrichment pathways. These findings provide a basis for understanding the clinical application of RP in CC.

Gene Expression Profile Analyses of the Skin Response of Balb/c-Nu Mice Model Injected by Staphylococcus aureus

Background

Pathogenesis and persistence of many skin diseases are related to Staphylococcus aureus (S. aureus) colonization. S. aureus infection can cause varying degrees of changes in cell gene expression, resulting in complex changes in cell phenotype and finally changes in cell life activities.

Materials and Methods

The transcriptomes of healthy and Staphylococcus aureus (S. aureus)-infected murine skin tissues were analyzed. We identified 638 differentially expressed genes (DEGs) in the infected tissues compared to the control samples, of which 324 were upregulated and 314 were downregulated, following the criteria of P < 0.01 and |log₂FC| > 3. The DEGs were functionally annotated by Gene Ontology (GO), KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway and the protein–protein interaction (PPI) network analyses.

Results

The upregulated DEGs were mainly enriched in GO terms, such as response to stimulus, immune system process and signal transduction, as well as in the complement and coagulation cascade pathway. Thus, S. aureus infection likely activates these pathways to limit the influx of neutrophils and prevent skin damage. Four clusters were identified in the PPI network, and the major hubs were mainly related to cell cycle and proliferation, and mostly downregulated. The expression levels of Nox4, Mmrn1, Mcm5, Msx1 and Fgf5 mRNAs were validated by qRT-PCR and found to be consistent with the RNA-Seq data, confirming a strong correlation between the two approaches.

Conclusion

The identified genes and pathways are potential drug targets for treating skin inflammation caused by S. aureus and should be investigated further.

A network pharmacology-based approach to explore mechanism of action of medicinal herbs for alopecia treatment

Hair loss is one of the most common skin problems experienced by more than half of the world's population. In East Asia, medicinal herbs have been used widely in clinical practice to treat hair loss. Recent studies, including systematic literature reviews, indicate that medicinal herbs may demonstrate potential effects for hair loss treatment. In a previous study, we identified medical herbs used frequently for alopecia treatment. Herein, we explored the potential novel therapeutic mechanisms of 20 vital medicinal herbs for alopecia treatment that could distinguish them from known mechanisms of conventional drugs using network pharmacology analysis methods. We determined the herb-ingredient–target protein networks and ingredient-associated protein (gene)-associated pathway networks and calculated the weighted degree centrality to define the strength of the connections. Data showed that 20 vital medicinal herbs could exert therapeutic effects on alopecia mainly mediated via regulation of various target genes and proteins, including acetylcholinesterase (AChE), phospholipase A2 (PLA2) subtypes, ecto-5-nucleotidase (NTE5), folate receptor (FR), nicotinamide N-methyltransferase (NNMT), and quinolinate phosphoribosyltransferase (QPRT). Findings regarding target genes/proteins and pathways of medicinal herbs associated with alopecia treatment offer insights for further research to better understand the pathogenesis and therapeutic mechanism of medicinal herbs for alopecia treatment with traditional herbal medicine.

Elaborate the Mechanism of Ancient Classic Prescriptions (Erzhi Formula) in Reversing GIOP by Network Pharmacology Coupled with Zebrafish Verification

Osteoporosis is a degenerative disease that endangers human health. At present, chemical drugs used for osteoporosis have serious side effects. Therefore, it is valuable to search herbs with high safety and good curative effect in antiosteoporosis. Erzhi formula (EZF), an ancient classic compound, has been reported to have a beneficial effect in antiosteoporosis, but its mechanism is unclear. In this paper, the active compounds of EZF were found in Systems Pharmacology Database, and gene targets related to osteoporosis were obtained in GeneCards. The GO functional and KEGG pathway enrichment analysis were performed by Metascape. The network of “components-targets-signal pathway” was constructed by Cytoscape. Next, molecular docking between the active components and hub genes related to the PI3K-Akt signaling pathway was conducted by Autodock. In the verification experiment, the zebrafish induced by prednisolone (PNSL) was used to reproduce glucocorticoid-induced osteoporosis (GIOP) model, and then the reversal effects of EZF were systematically evaluated according to the behavior, skull staining area, bone mineralization area (BMA), average optical density (AOD), and cumulative optical density (COD). Finally, it was shown that 24 components in EZF could regulate 39 common gene targets to exert antiosteoporosis effect. Besides, the main regulatory mechanisms of EZF were 4 signaling pathways: PI3K-Akt, JAK-STAT, AGE-RAGE, and cancer pathway. In PI3K-Akt signaling pathway, wedelolactone, dimethyl wedelolactone, specnuezhenide, ursolic acid, acacetin, beta-sitosterol, apigenin, and kaempferol can bind tightly with EGF, IL-2, and IL-4 genes. Compared with the model group, the moving distance, swimming speed, and cumulative swimming time of zebrafish in EZF group were significantly increased (P < 0.05). Meanwhile, the BMA and COD of zebrafish were significantly improved after the intervention of EZF (P < 0.05). In summary, the 24 components of EZF exert their antiosteoporosis effects by regulating 39 related gene targets, among which the PI3K signaling pathway is crucial. EZF can promote bone formation and reversed GIOP through “multicomponent/multitarget/multipathway” and the medium dose of EZF may be the most suitable concentration for the treatment of GIOP in zebrafish model.

Effects of Qinghuang Powder on Acute Myeloid Leukemia Based on Network Pharmacology, Molecular Docking, and In Vitro Experiments

Qinghuang powder (QHP) is a traditional Chinese herbal medicine. This is a unique formula that is frequently used to treat malignant hematological diseases such as acute myeloid leukemia (AML) in modern clinical practice. An approach of network pharmacology and experimental validation were applied to investigate the pharmacological mechanisms of QHP in AML treatment. First, public databases for target genes known to be associated with AML are searched and compared to the target genes of the active compounds in QHP. Second, AML-associated genes and QHP target genes are compared to identify overlapping enriched genes, and these were used to predict selected target genes that may be implicated in the effects of QHP on AML. Additionally, we conducted functional enrichment analyses, such as gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The significantly enriched pathway associated with potential target proteins was the PI3K-Akt signaling pathway, suggesting that these potential target proteins and pathways may mediate the beneficial biological effects of QHP on AML. All these following genes were found to occur in the compounds-target-pathway networks: AKT1, MAPK1, MAPK3, PIK3CG, CASP3, CASP9, TNF, TGFB1, MAPK8, and TP53. Then, based on the molecular docking studies, it was suggested that the active compound isovitexin can fit into the binding pockets of the top candidate QHP-AML target proteins (PIK3CG). Subsequently, based on the prediction by network pharmacology analysis, both in vitro AML cells and western blot experiments were performed to validate the curative role of QHP. QHP exerted its antitumor activity on AML in vitro, as it inhibits cells proliferation, reduced the expression of Bcl-2 protein, and downregulated the PI3K-Akt signaling pathway. In conclusion, these results revealed that QHP could treat AML via a “multicomponent, multitarget, multipathway” regulatory network. Furthermore, our study also demonstrated that the combination of network pharmacology with the experimental study is effective in discovering and identifying QHP in the treatment of AML and its underlying pharmacological mechanisms.

Network pharmacology to unveil the mechanism of Moluodan in the treatment of chronic atrophic gastritis

BACKGROUND

Moluodan (MLD) is a traditional Chinese patent medicine for the treatment of chronic atrophic gastritis (CAG). However, the mechanism of action (MoA) of MLD for treating CAG still remain unclear.

PURPOSE

Elucidate the MoA of MLD for treating CAG based on network pharmacology.

STUDY DESIGN

Integrate computational prediction and experimental validation based on network pharmacology.

METHODS

Computationally, compounds of MLD were scanned by LC-MS/MS and the target profiles of compounds were identified based on network-based target prediction method. Compounds in MLD were compared with western drugs used for gastritis by hierarchical clustering of target profile. Key biological functional modules of MLD were analyzed, and herb-biological functional module network was constructed to elucidate combinatorial rules of MLD herbs for CAG. Experimentally, MLD's effect on different biological functional modules were validated from both phenotypic level and molecular level in 1- Methyl-3-nitro-1-nitrosoguanidine (MNNG)-induced GES-1 cells.

RESULTS

Computational results show that the target profiles of compounds in MLD can cover most of the biomolecules reported in literature. The MoA of MLD can cover most types of MoA of western drugs for CAG. The treatment of CAG by MLD involved the regulation of various biological functional modules, e.g., inflammation/immune, cell proliferation, cell apoptosis, cell differentiation, digestion and metabolism. Experimental results show that MLD can inhibit cell proliferation, promote cell apoptosis and differentiation, reduce the inflammation level and promote lipid droplet accumulation in MNNG-induced GES-1 cells.

CONCLUSION

The network pharmacology framework integrating computational prediction and experimental validation provides a novel way for exploring the MoA of MLD.

Using the Symptom Patient Similarity Network to Explore the Difference between the Chinese and Western Medicine Pathways of Ischemic Stroke and its Comorbidities

Methods

Individualized treatment of traditional Chinese medicine (TCM) provides a theoretical basis for the study of the personalized classification of complex diseases. Utilizing the TCM clinical electronic medical records (EMRs) of 7170 in patients with IS, a patient similarity network (PSN) with shared symptoms was constructed. Next, patient subgroups were identified using community detection methods and enrichment analyses were performed. Finally, genetic data of symptoms, herbs, and drugs were used for pathway and GO analysis to explore the characteristics of pathways of subgroups and to compare the similarities and differences in genetic pathways of herbs and drugs from the perspective of molecular pathways of symptoms.

Results

We identified 34 patient modules from the PSN, of which 7 modules include 98.48% of the whole cases. The 7 patient subgroups have their own characteristics of risk factors, complications, and comorbidities and the underlying genetic pathways of symptoms, drugs, and herbs. Each subgroup has the largest number of herb pathways. For specific symptom pathways, the number of herb pathways is more than that of drugs.

Conclusion

The research of disease classification based on community detection of symptom-shared patient networks is practical; the common molecular pathway of symptoms and herbs reflects the rationality of TCM herbs on symptoms and the wide range of therapeutic targets.

Network Pharmacology and Experimental Assessment to Explore the Pharmacological Mechanism of Qimai Feiluoping Decoction Against Pulmonary Fibrosis

Pulmonary fibrosis (PF) is one of the pathologic changes in COVID-19 patients in convalescence, and it is also a potential long-term sequela in severe COVID-19 patients. Qimai Feiluoping decoction (QM) is a traditional Chinese medicine formula recommended in the Chinese national medical program for COVID-19 convalescent patients, and PF is one of its indications. Through clinical observation, QM was found to improve the clinical symptoms and pulmonary function and reduce the degree of PF of COVID-19 convalescent patients. To further explore the pharmacological mechanisms and possible active components of QM in anti-PF effect, UHPLC/Q-TOF-MS was used to analyze the composition of the QM extract and the active components that can be absorbed into the blood, leading to the identification of 56 chemical compounds and 10 active components. Then, network pharmacology was used to predict the potential mechanisms and targets of QM; it predicted that QM exerts its anti-PF effects via the regulation of the epithelial-mesenchymal transition (EMT), extracellular matrix (ECM) degradation, and TGF-β signaling pathway. Finally, TGF-β1-induced A549 cells were used to verify and explore the pharmacological effects of QM and found that QM could inhibit the proliferation of TGF-β1-induced A549 cells, attenuate EMT, and promote ECM degradation by inhibiting the TGF-β/Smad3 pathway.

Digital tongue image analyses for health assessment

Traditional Chinese Medicine (TCM), as an effective alternative medicine, utilizes tongue diagnosis as a major method to assess the patient's health status by examining the tongue's color, shape, and texture. Tongue images can also give the pre-disease indications without any significant disease symptoms, which provides a basis for preventive medicine and lifestyle adjustment. However, traditional tongue diagnosis has limitations, as the process may be subjective and inconsistent. Hence, computer-aided tongue diagnoses have a great potential to provide more consistent and objective health assessments. This paper reviewed the current trends in TCM tongue diagnosis, including tongue image acquisition hardware, tongue segmentation, feature extraction, color correction, tongue classification, and tongue diagnosis system. We also present a case of TCM constitution classification based on tongue images.

Exploring biological basis of Syndrome differentiation in coronary heart disease patients with two distinct Syndromes by integrated multi-omics and network pharmacology strategy

Background

Traditional Chinese Medicine (TCM) is distinguished by Syndrome differentiation, which prescribes various formulae for different Syndromes of same disease. This study aims to investigate the underlying mechanism.

Methods

Using a strategy which integrated proteomics, metabolomics study for clinic samples and network pharmacology for six classic TCM formulae, we systemically explored the biological basis of TCM Syndrome differentiation for two typical Syndromes of CHD: Cold Congealing and Qi Stagnation (CCQS), and Qi Stagnation and Blood Stasis (QSBS).

Results

Our study revealed that CHD patients with CCQS Syndrome were characterized with alteration in pantothenate and CoA biosynthesis, while more extensively altered pathways including D-glutamine and D-glutamate metabolism; alanine, aspartate and glutamate metabolism, and glyoxylate and dicarboxylate metabolism, were present in QSBS patients. Furthermore, our results suggested that the down-expressed PON1 and ADIPOQ might be potential biomarkers for CCQS Syndrome, while the down-expressed APOE and APOA1 for QSBS Syndrome in CHD patients. In addition, network pharmacology and integrated analysis indicated possible comorbidity differences between the two Syndromes, that is, CCQS or QSBS Syndrome was strongly linked to diabetes or ischemic stroke, respectively, which is consistent with the complication disparity between the enrolled patients with two different Syndromes. These results confirmed our assumption that the molecules and biological processes regulated by the Syndrome-specific formulae could be associated with dysfunctional objects caused by the Syndrome of the disease.

Conclusion

This study provided evidence-based strategy for exploring the biological basis of Syndrome differentiation in TCM, which sheds light on the translation of TCM theory in the practice of precision medicine.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13020-021-00521-3.

1. Our work was based on clinical samples rather than pure data analysis or animal models.

2. We conducted multiple omics studies. Especially, as for metabolomics study, we performed both untargeted and targeted metabolomics experiments.

3. We performed network pharmacological study to cross-validated the results of multi-omics study. Although the data sources of network pharmacology were completely unrelated with our omics data, they came to the same conclusion about the difference of the two Syndromes.

4. In the network pharmacological study, we made efforts to collect and screen high-quality data. We collected data from multiple TCM databases and conducted drug likeness screening. Especially, we added quality markers of each herb, whose pharmacological relevance had been validated. To enhance the reliability of targets, for each Syndrome, we only studied common targets of 3 different TCM formulae prescribed for this Syndrome.

Network Pharmacology-based and Molecular Docking Analysis of Resveratrol's Pharmacological Effects on Type I Endometrial Cancer

Background

Resveratrol is a natural polyphenol commonly seen in foods. It has demonstrated an inhibitive effect on endometrial cancer, but the molecular action is still not known.

Objective

We aimed to use network pharmacology to systematically study the possible mechanisms of resveratrol’s pharmacological effects on type I endometrial cancer.

Methods

Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) were used to predict resveratrol’s possible target genes. They were then converted to UniProt gene symbols. Simultaneously, type I endometrial cancer-related target genes were collected from GeneCards. All data were pooled to identify common target genes. The protein-protein interaction (PPI) network was constructed and further analyzed via STRING Online Database. Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway were also performed afterward. To visualise resveratrol's overall pharmacological effects on type I endometrial cancer, a network of drug components-target gene-disease (CTD) was constructed. Then, we performed in silico molecular docking study to validate the possible binding conformation between resveratrol and candidate targets.

Results

There are 150 target genes of resveratrol retrieved after UniProt conversion; 122 of them shared interaction with type I endometrial cancer. Some important oncogenes and signaling pathways are involved in the process of resveratrol’s pharmacological effects on endometrioid cancer. Molecular docking analysis confirmed that hydrogen bonding and hydrophobic interaction are the main interaction between resveratrol and its targets.

Conclusion

We have explored the possible underlying mechanism of resveratrol in antagonising type I endometrial cancer through a network pharmacology-based approach and in-silico verification. However, further experiments are necessary to add to the evidence identifying resveratrol as a promising anti-type I endometrial cancer agent.

Alysicarpus vaginalis Bio-Actives as ESR Signaling Pathway Inhibitor for Breast Cancer Treatment: A Network Pharmacology Approach

In our previous study Alysicarpus vaginalis (AV) has appeared as a promising target for breast cancer hence we have screened potential targets by in silico, In Vitro and In Vivo methods. A network pharmacology (NP) approach involves prediction and validating of targets via molecular modeling, western blotting and In Vivo MNU-induced mammary cancer. The PPI network showed the 573 edges between 214 nodes (targets) that are involved in breast cancer and important one are ESR-1, ESR-2, AR, EGFR, NOS3, MAPK, KDR, SRC and MET. Compound-target-pathway network involves 04 compounds and 221 interactive protein targets associated with breast cancer. GO and KEGG enrichment analysis predicted the ERR, c-MET, PDGFR-α/β, EGFR, and VEGF as a key targets in the breast cancer treatment which are validated via molecular modeling. Expression of ER-α, AR and EGFR were significantly down regulated by AV in MCF-7 cell line. In addition, the immunoreactivity of ER-α was reduced significantly in MNU-induced mammary carcinoma, which is a key target in ER + breast cancer. Overall, this study scientifically light ups the pharmacological mechanism of AV in the treatment of breast cancer, strongly associated with the regulation of ESR signaling pathway.