TMNP: a transcriptome-based multi-scale network pharmacology platform for herbal medicine

Bioactive components of Jiedu Sangen decoction against colorectal cancer: A novel and comprehensive research strategy for natural drug development

BACKGROUND

Jiedu Sangen Decoction (JSD) is widely used in the treatment of colorectal cancer (CRC) patients in southern China due to its good clinical efficacy, but the effective active ingredients are still unknown.

PURPOSE

This study fully explored the bioactive components of JSD based on an innovative and comprehensive research strategy. Using advanced computer technology (e.g., machine learning AHP-SOM algorithm and molecular dynamics simulation) to identify the most promising bioactive components and key targets in JSD, in order to provide new perspectives for the development of natural drugs.

METHODS

UPLC-MS/MS was used to screen bioactive components in JSD and rat plasma, and network pharmacology analysis combined with machine learning yielded the most promising bioactive components. RNA-seq was used to screen therapeutic targets before and after JSD acted on SW620 cells, and bioinformatics was used to analyze the clinical significance of these key targets. Molecular docking, molecular dynamics simulation, and experiments verified the most promising bioactive components and their therapeutic targets.

RESULTS

JSD exhibited a strong pro-apoptotic effect on CRC in vitro. UPLC-MS/MS screened out 18 prototype components and 8 possible metabolites of JSD entering the blood. Network pharmacology combined with machine learning identified the three most promising bioactive components. RNA sequencing and bioinformatics analysis revealed six key targets of JSD against CRC. Molecular docking and molecular dynamics simulations proposed the most promising "small molecule drug-target protein" combinations, and SPR and MST demonstrated the direct binding between them: Resveratrol - CA9, Genistein - NOTUM, and Afzelin - DPEP1. Molecular biology experiments found that resveratrol may promote CRC apoptosis through the CA9/PI3K/AKT signaling pathway, and genistein targets NOTUM to downregulate β-catenin expression to inhibit CRC proliferation.

CONCLUSION

It is feasible to develop a novel and comprehensive research strategy to fully explore bioactive components of JSD and provide full support for natural drug development.

A universal gene expression signature-based strategy for the high-throughput discovery of anti-inflammatory drugs

BACKGROUND

Traditional Chinese medicine (TCM) is a valuable resource for drug discovery and has demonstrated excellent efficacy in treating inflammatory diseases. This study aimed to develop a universal gene signature-based strategy for high-throughput discovery of anti-inflammatory drugs, especially Traditional Chinese medicine (TCM).

METHODS

The disease gene signature of liposaccharide-stimulated THP-1 cells and drug gene signatures of 655 drug candidates were established via sequencing. Anti-inflammatory drugs were screened based on similarities between drug gene signatures and the reversed disease gene signature.

RESULTS

Through screening, 83 potential anti-inflammatory drugs were identified. The efficacy of the TCM formula Biyun Powder, along with individual TCMs, Centipedea Herba, Kaempferiae Rhizoma, and Schizonepetae Spica Carbonisata, was verified in vitro or in vivo. Mechanistically, they exerted anti-inflammatory effects by inhibiting the nuclear factor-kappa B pathway. Kaempferol and luteolin were identified as bioactive IκB kinase-β inhibitors in Kaempferiae Rhizoma and Schizonepetae Spica Carbonisata, respectively.

CONCLUSION

We developed a universal gene signature-based approach for the high-throughput discovery of anti-inflammatory drugs that is applicable to compounds and to TCM herbs/formulae and established a workflow (screening, validation of efficacy, and identification of the mechanism of action and bioactive compounds) that can serve as a research template for high-throughput drug research.

Advances in the application of network analysis methods in traditional Chinese medicine research

OBJECTIVE

This review aims at evaluating the role and potential applications of network analysis methods in the medicinal substances of traditional Chinese medicine (TCM), theories of TCM compatibility, properties of herbs, and TCM syndromes.

METHODS

Literature was retrieved from databases, such as CNKI, PubMed, and Web of Science, using keywords, including "network analysis," "network biology," "network pharmacology," and "network medicine." The extracted literature included the biological network construction (including ingredient-target and target-disease relations), analysis of network topology characteristics (including node degree, clustering coefficient, and path length), network modularization analysis, functional annotation and so on. These studies were categorized and organized based on their research methods, application domains, and other relevant characteristics.

RESULTS

Network analysis algorithms, such as network distance, random walk, matrix factorization, graph embedding, and graph neural networks, are widely applied in fields related to the properties, compatibility, and mechanisms of TCM. They effectively reflect the interactive relations within the complex systems of TCM and elucidate and clarify theories, such as the effective substances, the principles of TCM compatibility, the TCM syndromes, and the properties of TCM.

CONCLUSION

The network analysis method is a powerful mathematical and computational tool that reveals the structure, dynamics, and functions of complex systems by analyzing the elements and their relations. This approach has effectively promoted the modernization of TCM, providing essential theoretical and practical tools for personalized treatment and scientific research on TCM. It also offers a significant methodological framework for the modernization and internationalization of TCM.

NP-TCMtarget: a network pharmacology platform for exploring mechanisms of action of traditional Chinese medicine

The biological targets of traditional Chinese medicine (TCM) are the core effectors mediating the interaction between TCM and the human body. Identification of TCM targets is essential to elucidate the chemical basis and mechanisms of TCM for treating diseases. Given the chemical complexity of TCM, both in silico high-throughput compound-target interaction predicting models and biological profile-based methods have been commonly applied for identifying TCM targets based on the structural information of TCM chemical components and biological information, respectively. However, the existing methods lack the integration of TCM chemical and biological information, resulting in difficulty in the systematic discovery of TCM action pathways. To solve this problem, we propose a novel target identification model NP-TCMtarget to explore the TCM target path by combining the overall chemical and biological profiles. First, NP-TCMtarget infers TCM effect targets by calculating associations between herb/disease inducible gene expression profiles and specific gene signatures for 8233 targets. Then, NP-TCMtarget utilizes a constructed binary classification model to predict binding targets of herbal ingredients. Finally, we can distinguish TCM direct and indirect targets by comparing the effect targets and binding targets to establish the action pathways of herbal component-direct target-indirect target by mapping TCM targets in the biological molecular network. We apply NP-TCMtarget to the formula XiaoKeAn to demonstrate the power of revealing the action pathways of herbal formula. We expect that this novel model could provide a systematic framework for exploring the molecular mechanisms of TCM at the target level. NP-TCMtarget is available at http://www.bcxnfz.top/NP-TCMtarget.

Effects of Mao tea from Nankun Mountain on nonalcoholic fatty liver disease in mice

Non-alcoholic fatty liver disease (NAFLD) poses a significant health threat due to its potential progression to liver fibrosis, cirrhosis, and even liver cancer. Without proper management, NAFLD can lead to severe complications and significantly impact overall health and longevity. This study explores the potential anti-steatosis effects of Nankun Mountain Mao tea (MT) on hepatic lipid accumulation using both in vitro and in vivo models. In vitro experiments reveal that MT reduces lipid accumulation in hepatocytes and counteracts hepatic steatosis induced by palmitic acid and oleic acid. In vivo investigations on high-fat diet (HFD)-fed and high-fat, fructose, and cholesterol (HFFC)-fed mice demonstrate that MT administration alleviates hepatic steatosis by reducing lipid accumulation, enhancing liver function, and mitigating inflammation. Transcriptomic analyses unveil the molecular mechanisms underlying the impact of MT on lipid metabolism and inflammation. It turns out that MT inhibits de novo lipid synthesis and NF-κB pathway against NAFLD. Furthermore, target prediction analysis identifies potential bioactive components group (BCG) within MT that may contribute to its anti-steatosis properties. Validation studies on primary hepatocytes confirm the effectiveness of these bioactive components in diminishing lipid accumulation and inflammation, suggesting their role in the therapeutic efficacy of MT against NAFLD.

RNA-Seq-Based Transcriptome Analysis of Chinese Cordyceps Aqueous Extracts Protective Effect against Adriamycin-Induced mpc5 Cell Injury

Pharmacogenomic analysis based on drug transcriptome characteristics is widely used to identify mechanisms of action. The purpose of this study was to elucidate the molecular mechanism of protective effect against adriamycin (ADM)-induced mpc5 cell injury of Chinese cordyceps aqueous extracts (WCCs) by a systematic transcriptomic analysis. The phytochemicals of WCCs were analyzed via the "phenol-sulfuric acid method", high-performance liquid chromatography (HPLC), and HPLC-mass spectrometry (MS). We analyzed the drug-reaction transcriptome profiles of mpc5 cell after treating them with WCCs. RNA-seq analysis revealed that WCCs alleviated ADM-induced mpc5 cell injury via restoring the expression of certain genes to normal level mainly in the one-carbon pool by the folate pathway, followed by the relaxin, apelin, PI3K-Akt, and nucleotide-binding, oligomerization domain (NOD)-like receptor signaling pathway, enhancing DNA synthesis and repair, cell proliferation, fibrosis reduction, and immune regulation. Otherwise, WCCs also modulated the proliferation and survival of the mpc5 cell by regulating metabolic pathways, and partially restores the expression of genes related to human disease pathways. These findings provide an innovative understanding of the molecular mechanism of the protective effect of WCCs on ADM-induced mpc5 cell injury at the molecular transcription level, and Mthfd2, Dhfr, Atf4, Creb5, Apln, and Serpine1, etc., may be potential novel targets for treating nephrotic syndrome.

Exploring the potential mechanism of Heng-Gu-Gu-Shang-Yu-He-Ji therapy for osteoporosis based on network pharmacology and transcriptomics

ETHNOPHARMACOLOGICAL RELEVANCE

Heng-Gu-Gu-Shang-Yu-He-Ji (Osteoking, OK) is a well-known formula for fracture therapy. In clinic, OK is effective in treating fractures while alleviating osteoporosis (OP) symptoms. However, active components of OK and the associated molecular mechanisms remain not fully elucidated.

AIM OF THE STUDY

This study aims to systematically evaluate the anti-osteoporosis efficacy of OK and for the first time combine network pharmacology with high-throughput whole gene transcriptome sequencing to study its underlying mechanism.

MATERIALS AND METHODS

In this study, the osteoporosis model was established by the castration of both ovaries. The level of serum bone turnover factor was detected by enzyme-linked immunosorbent assay. Micro-CT and HE staining were used to observe the changes of bone histopathology, and nano-indentation technique was used to detect the biomechanical properties of rat bone. The main active Chemical components of OK were identified using UPLC-DAD. Efficacy verification and mechanism exploration were conducted by network pharmacology, molecular docking, whole gene transcriptomics and in vivo experiments.

RESULTS

In our study, OK significantly improved bone microarchitecture and bone biomechanical parameters in OVX rats, reduced osteoclast indexes such as C-telopeptide of type I collage (CTX-I) and increased Osteoprotegerin (OPG)/Receptor activator of NF-κB ligand (RANKL) levels. Mechanistically, PI3K/AKT pathway was a common pathway for genome enrichment analysis (KEGG) of both network pharmacology and RNA-seq studies. G protein-β-like protein (GβL), Ribosomal-protein S6 kinase homolog 2 (S6K2), and Phosphoinositide 3-kinase (PI3K) appeared differentially expression in the PI3K-AKT signaling pathway. These results were also confirmed by qRT-PCR and immunohistochemistry.

CONCLUSIONS

OK may be used to treat osteoporosis, at least partly by activating PI3K/AKT/mTORC1 signaling pathway.

Qing-Zhi-Tiao-Gan-Tang (QZTGT) prevents nonalcoholic steatohepatitis (NASH) by expression pattern correction

ETHNOPHARMACOLOGICAL RELEVANCE

Qing-Zhi-Tiao-Gan-Tang or Qing-Zhi-Tiao-Gan Decoction (QZTGT) is based on the compatibility theory of traditional Chinese medicine (TCM), that is a combination of three classical formulae for the treatment of nonalcoholic fatty liver disease (NAFLD). Its pharmacodynamic material basis is made up of quinones, flavanones, and terpenoids.

AIM OF THE STUDY

This study aimed to look for a promising recipe for treating nonalcoholic steatohepatitis (NASH), a more advanced form of NAFLD, and to use a transcriptome-based multi-scale network pharmacological platform (TMNP) to find its therapy targets.

MATERIALS AND METHODS

A classical dietary model of NASH was established using MCD (Methionine- and choline-deficient) diet-fed mice. Liver coefficients like ALT, AST, serum TC, and TG levels were tested following QZTGT administration. A transcriptome-based multi-scale network pharmacological platform (TMNP) was used to further analyze the liver gene expression profile.

RESULTS

The composition of QZTGT was analyzed by HPLC-Q-TOF/MS, a total of 89 compounds were separated and detected and 31 of them were found in rat plasma. QZTGT improved liver morphology, inflammation and fibrosis in a classical NASH model. Transcriptomic analysis of liver samples from NASH animal model revealed that QZTGT was able to correct gene expression. We used transcriptome-based multi-scale network pharmacological platform (TMNP) to predicted molecular pathways regulated by QZTGT to improve NASH. Further validation indicated that "fatty acid degradation", "bile secretion" and "steroid biosynthesis" pathways were involved in the improvement of NASH phenotype by QZTGT.

CONCLUSIONS

Using HPLC-Q-TOF/MS, the compound composition of QZTGT, a Traditional Chinese prescription, was separated, analyzed and identified systematically. QZTGT mitigated NASH symptoms in a classical dietary model of NASH. Transcriptomic and network pharmacology analysis predicted the potential QZTGT regulated pathways. These pathways could be used as therapeutic targets for NASH.

Elucidating the pharmacodynamic mechanisms of Yuquan pill in T2DM rats through comprehensive multi-omics analyses

Background: Yuquan Pill (YQW) is a modern concentrated pill preparation of six herbs, namely, Ge Gen (Pueraria lobata Ohwi), Di huang (Rehmannia glutinosa Libosch.), Tian Huafen (Trichosanthes kirilowii Maxim.), Mai Dong (Ophiopogon japonicus (L. f.) Ker Gawl.), Wu Weizi (Schisandra chinensis (Turcz.) Baill.) and Gan Cao (Glycyrrhiza uralensis Fisch.). It is extensively used to treat type 2 diabetes-related glucose and lipid metabolism disorders. But what's the pharmacodynamic substance and how it works in the treatment of Type 2 diabetes mellitus (T2DM) are still unclear. Purpose: The purpose of this study is to determine the likely pharmacological components and molecular mechanism of YQW's intervention on T2DM by combining serum pharmacochemistry, network analysis and transcriptomics. Methods: The efficacy and prototypical components of blood entry were determined after oral administration of YQW aqueous solution to T2DM rats induced by high-fat feed and low-dose streptozotocin (STZ), and the key targets and pathways for these compounds to intervene in T2DM rats were predicted and integrated using network analysis and transcriptomics techniques. Results: In diabetic rats, YQW can lower TG, CHO, NO, and MDA levels (p < 0.05) while increasing HDL-C levels (p < 0.01), and protecting the liver and kidney. 22 prototype components (including puerarin, daidzein, 3'-methoxypuerarin, and liquiritigenin, among others) were found in the serum of rats after oral administration of YQW for 90 min, which might be used as a possible important ingredient for YQW to intervene in T2DM rats. 538 YQW pharmacodynamic components-related targets and 1,667 disease-related targets were projected through the PharmMapper database, with 217 common targets between the two, all of which were engaged in regulating PI3K-Akt, MAPK, Ras and FoxO signal pathway. Finally, the mRNA expression profiles of liver tissues from rats in the control, model, and YQW groups were investigated using high-throughput mRNA sequencing technology. YQW can regulate the abnormal expression of 89 differential genes in a disease state, including 28 genes with abnormally high expression and 61 genes with abnormally low expression. Five common genes (Kit, Ppard, Ppara, Fabp4, and Tymp) and two extensively used regulatory pathways (PI3K-Akt and MAPK signaling pathways) were revealed by the integrated transcriptomics and network analysis study. Conclusion: The mechanism of YQW's intervention in T2DM rats could be linked to 22 important components like puerarin, daidzein, and glycyrrhetinic acid further activating PI3K-Akt and MAPK signaling pathways by regulating key targets Kit, Ppard, Ppara, Fabp4, and Tymp, and thus improving lipid metabolism disorder, oxidative stress, and inflammation levels in T2DM rats. On the topic, more research into the pharmacological ingredient foundation and mechanism of YQW intervention in T2DM rats can be done.

Exploring pharmacological active ingredients of traditional Chinese medicine by pharmacotranscriptomic map in ITCM

With the emergence of high-throughput technologies, computational screening based on gene expression profiles has become one of the most effective methods for drug discovery. More importantly, profile-based approaches remarkably enhance novel drug-disease pair discovery without relying on drug- or disease-specific prior knowledge, which has been widely used in modern medicine. However, profile-based systematic screening of active ingredients of traditional Chinese medicine (TCM) has been scarcely performed due to inadequate pharmacotranscriptomic data. Here, we develop the largest-to-date online TCM active ingredients-based pharmacotranscriptomic platform integrated traditional Chinese medicine (ITCM) for the effective screening of active ingredients. First, we performed unified high-throughput experiments and constructed the largest data repository of 496 representative active ingredients, which was five times larger than the previous one built by our team. The transcriptome-based multi-scale analysis was also performed to elucidate their mechanism. Then, we developed six state-of-art signature search methods to screen active ingredients and determine the optimal signature size for all methods. Moreover, we integrated them into a screening strategy, TCM-Query, to identify the potential active ingredients for the special disease. In addition, we also comprehensively collected the TCM-related resource by literature mining. Finally, we applied ITCM to an active ingredient bavachinin, and two diseases, including prostate cancer and COVID-19, to demonstrate the power of drug discovery. ITCM was aimed to comprehensively explore the active ingredients of TCM and boost studies of pharmacological action and drug discovery. ITCM is available at http://itcm.biotcm.net.

A Natural Glucan from Black Bean Inhibits Cancer Cell Proliferation via PI3K-Akt and MAPK Pathway

A natural α-1,6-glucan named BBWPW was identified from black beans. Cell viability assay showed that BBWPW inhibited the proliferation of different cancer cells, especially HeLa cells. Flow cytometry analysis indicated that BBWPW suppressed the HeLa cell cycle in the G2/M phase. Consistently, RT-PCR experiments displayed that BBWPW significantly impacts the expression of four marker genes related to the G2/M phase, including p21, CDK1, Cyclin B1, and Survivin. To explore the molecular mechanism of BBWPW to induce cell cycle arrest, a transcriptome-based target inference approach was utilized to predict the potential upstream pathways of BBWPW and it was found that the PI3K-Akt and MAPK signal pathways had the potential to mediate the effects of BBWPW on the cell cycle. Further experimental tests confirmed that BBWPW increased the expression of BAD and AKT and decreased the expression of mTOR and MKK3. These results suggested that BBWPW could regulate the PI3K-Akt and MAPK pathways to induce cell cycle arrest and ultimately inhibit the proliferation of HeLa cells, providing the potential of the black bean glucan to be a natural anticancer drug.

Systematic transcriptome analysis reveals molecular mechanisms and indications of bupleuri radix

Pharmacogenomic analysis based on drug transcriptomic signatures is widely used to identify mechanisms of action and pharmacological indications. Despite accumulating reports on the efficacy of medicinal herbs, related transcriptome-level analyses are lacking. The aim of the present study was to elucidate the underlying molecular mechanisms of action of Bupleuri Radix (BR), a widely used herbal medicine, through a systematic transcriptomic analysis. We analyzed the drug-responsive transcriptome profiling of A549 lung cancer cell line after treating them with multiple doses of BR water (W-BR) and ethanol (E-BR) extracts and their phytochemicals. In vitro validation experiments were performed using both A549 and the immortalized human keratinocyte line HaCaT. Pathway enrichment analysis revealed the anti-cancer effects of BR treatment via inhibition of cell proliferation and induction of apoptosis. Enhanced cell adhesion and migration were observed with the W-BR but not with the E-BR. Comparison with a disease signature database validated an indication of the W-BR for skin disorders. Moreover, W-BR treatment showed the wound-healing effect in skin and lung cells. The main active ingredients of BR showed only the anti-cancer effect of the E-BR and not the wound healing effect of the W-BR, suggesting the need for research on minor ingredients of BR.

Systems pharmacology approaches in herbal medicine research: a brief review

Herbal medicine, a multi-component treatment, has been extensively practiced for treating various symptoms and diseases. However, its molecular mechanism of action on the human body is unknown, which impedes the development and application of herbal medicine. To address this, recent studies are increasingly adopting systems pharmacology, which interprets pharmacological effects of drugs from consequences of the interaction networks that drugs might have. Most conventional network- based approaches collect associations of herb-compound, compound-target, and target-disease from individual databases, respectively, and construct an integrated network of herb-compound- target-disease to study the complex mechanisms underlying herbal treatment. More recently, rapid advances in highthroughput omics technology have led numerous studies to exploring gene expression profiles induced by herbal treatments to elicit information on direct associations between herbs and genes at the genome-wide scale. In this review, we summarize key databases and computational methods utilized in systems pharmacology for studying herbal medicine. We also highlight recent studies that identify modes of action or novel indications of herbal medicine by harnessing drug-induced transcriptome data. [BMB Reports 2022; 55(9): 417-428].

Letter regarding article named 'Is acupuncture effective in the treatment of COVID-19 related symptoms? Based on bioinformatics/network topology strategy'

I noticed a recently published paper named 'Is acupuncture effective in the treatment of COVID-19 related symptoms? Based on bioinformatics/network topology strategy' with great interest. I am inspired and also have some doubts, which are mainly about the active compounds of acupuncture treating COVID-19. The authors choose only two active compounds, which remains to be elucidated clearly with some criteria description. The 11 300 disease targets of COVID-19 were screened using the terms like the related symptoms, which might be other diseases' manifestations. So the better legends of Figures and Tables should be the terms like COVID-19-related symptoms, instead of COVID-19.