TCMIO: A Comprehensive Database of Traditional Chinese Medicine on Immuno-Oncology

Herb-CMap: a multimodal fusion framework for deciphering the mechanisms of action in traditional Chinese medicine using Suhuang antitussive capsule as a case study

Herbal medicines, particularly traditional Chinese medicines (TCMs), are a rich source of natural products with significant therapeutic potential. However, understanding their mechanisms of action is challenging due to the complexity of their multi-ingredient compositions. We introduced Herb-CMap, a multimodal fusion framework leveraging protein-protein interactions and herb-perturbed gene expression signatures. Utilizing a network-based heat diffusion algorithm, Herb-CMap creates a connectivity map linking herb perturbations to their therapeutic targets, thereby facilitating the prioritization of active ingredients. As a case study, we applied Herb-CMap to Suhuang antitussive capsule (Suhuang), a TCM formula used for treating cough variant asthma (CVA). Using in vivo rat models, our analysis established the transcriptomic signatures of Suhuang and identified its key compounds, such as quercetin and luteolin, and their target genes, including IL17A, PIK3CB, PIK3CD, AKT1, and TNF. These drug-target interactions inhibit the IL-17 signaling pathway and deactivate PI3K, AKT, and NF-κB, effectively reducing lung inflammation and alleviating CVA. The study demonstrates the efficacy of Herb-CMap in elucidating the molecular mechanisms of herbal medicines, offering valuable insights for advancing drug discovery in TCM.

Lianhua Qingwen exerts anti-liver cancer effects and synergistic efficacy with sorafenib through PI3K/AKT pathway: Integrating network pharmacology, molecular docking, and experimental validation

Liver cancer is one of the most lethal malignancies and sorafenib resistance is the main treatment obstacle for patients with advanced liver cancer. Developing drugs that sensitize liver cancer patients to sorafenib is of great importance. Lianhua Qingwen (LHQW), a sort of Traditional Chinese Medicine (TCM) approved by the Chinese Food and Drug Administration (CFDA), is reported to exert synergistic effects with oseltamivir against Influenza virus. However, whether LHQW could exhibit anti-liver cancer effects and enhance the efficacy of sorafenib against liver cancer have not been reported. In the present study, the potential anti-liver cancer effects of LHQW and its synergistic effects with sorafenib were investigated via applying network pharmacology, molecular docking, and in vitro experiments. An "ingredient-compound- target-liver cancer" network was constructed which included 12 ingredients, 164 compounds, and 402 targets. AKT1 was identified as the most hub gene and the PI3K/AKT pathway was revealed as the most enriched pathway. Subsequently, the molecular docking results showed that kaempferol, luteolin, and quercetin were screened as the top 3 compounds which showed the tightest binding to AKT1. Further, the in vitro experiments verified that LHQW significantly inhibited liver cancer cell proliferation and induced apoptosis. Western blot assays confirmed that LHQW could attenuate the PI3K/AKT pathway. Interestingly, LHQW showed a synergistic effect with sorafenib against liver cancer via reducing cell viability, inducing apoptosis, and down- regulating PI3K/AKT pathway. This study broadens the potential application of LHQW and provides insights for liver cancer treatment.

Artemisia argyi extracts overcome lapatinib resistance via enhancing TMPRSS2 activation in HER2-positive breast cancer

Breast cancer stands as the predominant malignancy and primary cause of cancer-related mortality among females globally. Approximately 25% of breast cancers exhibit HER2 overexpression, imparting a more aggressive tumor phenotype and correlating with poor prognoses. Patients with metastatic breast cancer receiving HER2 tyrosine kinase inhibitors (HER2 TKIs), such as Lapatinib, develop acquired resistance within a year, posing a critical challenge in managing this disease. Here, we explore the potential of Artemisia argyi, a Chinese herbal medicine known for its anti-cancer properties, in mitigating HER2 TKI resistance in breast cancer. Analysis of the Cancer Genome Atlas (TCGA) revealed diminished expression of transmembrane serine protease 2 (TMPRSS2), a subfamily of membrane proteolytic enzymes, in breast cancer patients, correlating with unfavorable outcomes. Intriguingly, lapatinib-responsive patients exhibited higher TMPRSS2 expression. Our study unveiled that the compounds from Artemisia argyi, eriodictyol, and umbelliferone could inhibit the growth of lapatinib-resistant HER2-positive breast cancer cells. Mechanistically, they suppressed HER2 kinase activation by enhancing TMPRSS2 activity. Our findings propose TMPRSS2 as a critical determinant in lapatinib sensitivity, and Artemisia argyi emerges as a potential agent to overcome lapatinib via activating TMPRSS2 in HER2-positive breast cancer. This study not only unravels the molecular mechanisms driving cell death in HER2-positive breast cancer cells induced by Artemisia argyi but also lays the groundwork for developing novel inhibitors to enhance therapy outcomes.

Advances in traditional herbal formulation based nano-vaccine for cancer immunotherapy: Unraveling the enigma of complex tumor environment and multidrug resistance

Cancer is attributed to uncontrolled cell growth and is among the leading causes of death with no known effective treatment while complex tumor microenvironment (TME) and multidrug resistance (MDR) are major challenges for developing an effective therapeutic strategy. Advancement in cancer immunotherapy has been limited by the over-activation of the host immune response that ultimately affects healthy tissues or organs and leads to a feeble response of the patient's immune system against tumor cells. Besides, traditional herbal medicines (THM) have been well-known for their essential role in the treatment of cancer and are considered relatively safe due to their compatibility with the human body. Yet, poor solubility, low bio-availability, and lack of understanding about their pathophysiological mechanism halt their clinical application. Moreover, considering the complex TME and drug resistance, the most precarious and least discussed concerns for developing THM-based nano-vaccination, are identification of specific biomarkers for drug inhibitory protein and targeted delivery of bioactive ingredients of THM on the specific sites in tumor cells. The concept of THM-based nano-vaccination indicates immunomodulation of TME by THM-based bioactive adjuvants, exerting immunomodulatory effects, via targeted inhibition of key proteins involved in the metastasis of cancer. However, this concept is at its nascent stage and very few preclinical studies provided the evidence to support clinical translation. Therefore, we attempted to capsulize previously reported studies highlighting the role of THM-based nano-medicine in reducing the risk of MDR and combating complex tumor environments to provide a reference for future study design by discussing the challenges and opportunities for developing an effective and safe therapeutic strategy against cancer.

A critical assessment of Traditional Chinese Medicine databases as a source for drug discovery

Traditional Chinese Medicine (TCM) has been used for thousands of years to treat human diseases. Recently, many databases have been devoted to studying TCM pharmacology. Most of these databases include information about the active ingredients of TCM herbs and their disease indications. These databases enable researchers to interrogate the mechanisms of action of TCM systematically. However, there is a need for comparative studies of these databases, as they are derived from various resources with different data processing methods. In this review, we provide a comprehensive analysis of the existing TCM databases. We found that the information complements each other by comparing herbs, ingredients, and herb-ingredient pairs in these databases. Therefore, data harmonization is vital to use all the available information fully. Moreover, different TCM databases may contain various annotation types for herbs or ingredients, notably for the chemical structure of ingredients, making it challenging to integrate data from them. We also highlight the latest TCM databases on symptoms or gene expressions, suggesting that using multi-omics data and advanced bioinformatics approaches may provide new insights for drug discovery in TCM. In summary, such a comparative study would help improve the understanding of data complexity that may ultimately motivate more efficient and more standardized strategies towards the digitalization of TCM.

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

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

Identification of Dual-Target Inhibitors for Epidermal Growth Factor Receptor and AKT: Virtual Screening Based on Structure and Molecular Dynamics Study

Epidermal growth factor EGFR is an important target for non-small cell lung (NSCL) cancer, and inhibitors of the AKT protein have been used in many cancer treatments, including those for NSCL cancer. Therefore, searching small molecular inhibitors which can target both EGFR and AKT may help cancer treatment. In this study, we applied a ligand-based pharmacophore model, molecular docking, and MD simulation methods to search for potential inhibitors of EGFR and then studied dual-target inhibitors of EGFR and AKT by screening the immune-oncology Chinese medicine (TCMIO) database and the human endogenous database (HMDB). It was found that TCMIO89212, TCMIO90156, and TCMIO98874 had large binding free energies with EGFR and AKT, and HMDB0012243 also has the ability to bind to EGFR and AKT. These results may provide valuable information for further experimental study.

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

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

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

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

Systems pharmacology dissection of pharmacological mechanisms of Xiaochaihu decoction against human coronavirus

BACKGROUND

Although coronavirus disease 2019 (COVID-19) pandemic is still rage worldwide, there are still very limited treatments for human coronaviruses (HCoVs) infections. Xiaochahu decoction (XCHD), which is one of the traditional Chinese medicine (TCM) prescriptions in Qingfeipaidu decoction (QFPDD), is widely used for COVID-19 treatment in China and able to relieve the symptoms of fever, fatigue, anorexia, and sore throat. To explore the role and mechanisms of XCHD against HCoVs, we presented an integrated systems pharmacology framework in this study.

METHODS

We constructed a global herb-compound-target (H-C-T) network of XCHD against HCoVs. Multi-level systems pharmacology analyses were conducted to highlight the key XCHD-regulated proteins, and reveal multiple HCoVs relevant biological functions affected by XCHD. We further utilized network-based prediction, drug-likeness analysis, combining with literature investigations to uncover the key ani-HCoV constituents in XCHD, whose effects on anit-HCoV-229E virus were validated using cytopathic effect (CPE) assay. Finally, we proposed potential molecular mechanisms of these compounds against HCoVs via subnetwork analysis.

RESULTS

Based on the systems pharmacology framework, we identified 161 XCHD-derived compounds interacting with 37 HCoV-associated proteins. An integrated pathway analysis revealed that the mechanism of XCHD against HCoVs is related to TLR signaling pathway, RIG-I-like receptor signaling pathway, cytoplasmic DNA sensing pathway, and IL-6/STAT3 pro-inflammatory signaling pathway. Five compounds from XCHD, including betulinic acid, chrysin, isoliquiritigenin, schisandrin B, and (20R)-Ginsenoside Rh1 exerted inhibitory activity against HCoV-229E virus in Huh7 cells using in vitro CPE assay.

CONCLUSION

Our work presented a comprehensive systems pharmacology approach to identify the effective molecules and explore the molecular mechanism of XCHD against HCoVs.

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.

Assessment of Diagnosis, Prognosis and Immune Infiltration Response to the Expression of the Ferroptosis-Related Molecule HAMP in Clear Cell Renal Cell Carcinoma

BACKGROUND

Hepcidin antimicrobial peptide (HAMP) is a key factor in maintaining iron metabolism, which may induce ferroptosis when upregulated. However, its prognostic value and relation to immune infiltrating cells remains unclear.

METHODS

This study analyzed the expression levels of HAMP in the Oncomine, Timer and Ualcan databases, and examined its prognostic potential in KIRC with R programming. The Timer and GEPIA databases were used to estimate the correlations between HAMP and immune infiltration and the markers of immune cells. The intersection genes and the co-expression PPI network were constructed via STRING, R programming and GeneMANIA, and the hub genes were selected with Cytoscape. In addition, we analyzed the gene set enrichment and GO/KEGG pathways by GSEA.

RESULTS

Our study revealed higher HAMP expression levels in tumor tissues including KIRC, which were related to poor prognosis in terms of OS, DSS and PFI. The expression of HAMP was positively related to the immune infiltration level of macrophages, Tregs, etc., corresponding with the immune biomarkers. Based on the intersection genes, we constructed the PPI network and used the 10 top hub genes. Further, we performed a pathway enrichment analysis of the gene sets, including Huntington's disease, the JAK-STAT signaling pathway, ammonium ion metabolic process, and so on.

CONCLUSION

In summary, our study gave an insight into the potential prognosis of HAMP, which may act as a diagnostic biomarker and therapeutic target related to immune infiltration in KIRC.

East Wind, West Wind: Toward the modernization of traditional Chinese medicine

Traditional Chinese medicine (TCM) has used herbal remedies for more than 2,000 years. The use of complimentary therapies has increased dramatically during the last years, especially in the West, and the incorporation and modernization of TCM in current medical practice is gaining momentum. We reflect on the main bottlenecks in the modernization of arcane Chinese herbal medicine: lack of standardization, safety concerns and poor quality of clinical trials, as well as the ways these are being overcome. Progress in these areas will facilitate the implementation of an efficacy approach, in which only successful clinical trials lead to the molecular characterization of active compounds and their mechanism of action. Traditional pharmacological methodologies will produce novel leads and drugs, and we describe TCM successes such as the discovery of artemisinin as well as many others still in the pipeline. Neurodegenerative diseases, such as Parkinson's and Alzheimer's disease, cancer and cardiovascular disease are the main cause of mortality in the Western world and, with an increasing old population in South East Asia, this trend will also increase in the Far East. TCM has been used for long time for treating these diseases in China and other East Asian countries. However, the holistic nature of TCM requires a paradigm shift. By changing our way of thinking, from "one-target, one-drug" to "network-target, multiple-component-therapeutics," network pharmacology, together with other system biology methodologies, will pave the way toward TCM modernization.

Methodology of network pharmacology for research on Chinese herbal medicine against COVID-19: A review

Traditional Chinese medicine, as a complementary and alternative medicine, has been practiced for thousands of years in China and possesses remarkable clinical efficacy. Thus, systematic analysis and examination of the mechanistic links between Chinese herbal medicine (CHM) and the complex human body can benefit contemporary understandings by carrying out qualitative and quantitative analysis. With increasing attention, the approach of network pharmacology has begun to unveil the mystery of CHM by constructing the heterogeneous network relationship of "herb-compound-target-pathway," which corresponds to the holistic mechanisms of CHM. By integrating computational techniques into network pharmacology, the efficiency and accuracy of active compound screening and target fishing have been improved at an unprecedented pace. This review dissects the core innovations to the network pharmacology approach that were developed in the years since 2015 and highlights how this tool has been applied to understanding the coronavirus disease 2019 and refining the clinical use of CHM to combat it.

Network Pharmacology-Based Strategy Combined with Molecular Docking and in vitro Validation Study to Explore the Underlying Mechanism of Huo Luo Xiao Ling Dan in Treating Atherosclerosis

Background

Huo Luo Xiao Ling Dan (HLXLD), a famous Traditional Chinese Medicine (TCM) classical formula, possesses anti-atherosclerosis (AS) activity. However, the underlying molecular mechanisms remain obscure.

Aim

The network pharmacology approach, molecular docking strategy, and in vitro validation experiment were performed to explore the potential active compounds, key targets, main signaling pathways, and underlying molecular mechanisms of HLXLD in treating AS.

Methods

Several public databases were used to search for active components and targets of HLXLD, as well as AS-related targets. Crucial bioactive ingredients, potential targets, and signaling pathways were acquired through bioinformatics analysis. Subsequently, the molecular docking strategy and molecular dynamics simulation were carried out to predict the affinity and stability of active compounds and key targets. In vitro cell experiment was performed to verify the findings from bioinformatics analysis.

Results

A total of 108 candidate compounds and 321 predicted target genes were screened. Bioinformatics analysis suggested that quercetin, dihydrotanshinone I, pelargonidin, luteolin, guggulsterone, and β-sitosterol may be the main ingredients. STAT3, HSP90AA1, TP53, and AKT1 could be the key targets. MAPK signaling pathway might play an important role in HLXLD against AS. Molecular docking and molecular dynamics simulation results suggested that the active compounds bound well and stably to their targets. Cell experiments showed that the intracellular accumulation of lipid and increased secretory of TNF-α, IL-1β, and MCP-1 in ox-LDL treated RAW264.7 cells, which can be significantly suppressed by pretreating with dihydrotanshinone I. The up-regulation of STAT3, ERK, JNK, and p38 phosphorylation induced by ox-LDL can be inhibited by pretreating with dihydrotanshinone I.

Conclusion

Our findings comprehensively demonstrated the active compounds, key targets, main signaling pathways, and underlying molecular mechanisms of HLXLD in treating AS. These findings would provide a scientific basis for the study of the complex mechanisms underlying disease and drug action.

The Research and Development Thinking on the Status of Artificial Intelligence in Traditional Chinese Medicine

With the rapid development and application of artificial intelligence (AI) in medical field, the diagnostic ways of human health and the social medical structures have changed. Based on the concept of holism and the theory of syndrome differentiation and treatment, TCM realizes comprehensive informatization and intelligence with the help of AI technology in data mining, intelligent diagnosis and treatment, intelligent learning, and decision-making. Furthermore, the intelligent research of TCM technology will further promote the improvement in TCM diagnosis and treatment rules and the leaping development of TCM intelligent instruments. In this article, we performed a systematic review of scientific literature about TCM and AI. Moreover, the practical problems of TCM intellectualization, the current situation and demand of TCM, and the influence of AI in the TCM field are discussed by searching for literature using TCM scientific databases, reference lists, expert consultation, and targeted websites. Finally, we look forward to the application prospects of AI and propose a possible future direction of intelligent TCM in the current health-care system in China.

The effect and apoptosis mechanism of 6-methoxyflavone in HeLa cells

INTRODUCTION

Tumor cell apoptosis is a crucial indicator for judging the antiproliferative effects of anti-cancer drugs. The detection of optical and macromolecular biomarkers is the most common method for assessing the level of apoptosis. We aimed to explore the anti-tumor mechanisms of 6-methoxyflavone.

MATERIAL AND METHODS

Three optical methods, including the percentage of apoptotic cells, cell morphology, and subcellular ultrastructure changes, were obtained using flow cytometry, inverted fluorescence microscopy, and transmission electron microscope imaging. The mRNA or protein expression of macromolecular biomarkers related to common apoptotic pathways was determined via polymerase chain reactions or western blot assays. The functional role of the core gene biomarker was investigated through overexpression, knockdown, and phosphorylation inhibitor (GSK2656157).

RESULTS

Transcriptome sequencing and the optical biomarkers assays demonstrated that 6-methoxyflavone could induce apoptosis in HeLa cells. The expression of macromolecular biomarkers indicated that 6-methoxyflavone induced apoptosis through the PERK/EIF2α/ATF4/CHOP pathway. Phosphorylated PERK was identified as the core biomarker of this pathway. Both overexpression and GSK2656157 significantly altered the expression level of phosphorylated PERK in 6-methoxyflavone-treated HeLa cells.

DISCUSSION AND CONCLUSION

Macromolecular biomarkers such as phosphorylated PERK and phosphorylated EIF2α are of great significance for assessing the therapeutic effects of 6-methoxyflavone.

In Silico Identification and Mechanism Exploration of Active Ingredients against Stroke from An-Gong-Niu-Huang-Wan (AGNHW) Formula

An-Gong-Niu-Huang-Wan (AGNHW) is a well-known formula for treating cerebrovascular diseases, with roles including clearing away heat, detoxification, and wake-up consciousness. In recent years, AGNHW has been commonly used for the treatment of ischemic stroke, but the mechanism by which AGNHW relieves stroke has not been clearly elucidated. In the current study, we developed a multiple systems pharmacology-based framework to identify the potential antistroke ingredients in AGNHW and explore the underlying mechanisms of action (MOA) of AGNHW against stroke from a holistic perspective. Specifically, we performed a network-based method to identify the potential antistroke ingredients in AGNHW by integrating the drug-target network and stroke-associated genes. Furthermore, the oxygen-glucose deprivation/reoxygenation (OGD/R) model was used to validate the anti-inflammatory effects of the key ingredients by determining the levels of inflammatory cytokines, including interleukin (IL)-6, IL-1β, and tumor necrosis factor (TNF)-α. The antiapoptotic effects of the key ingredients were also confirmed in vitro. Integrated pathway analysis of AGNHW revealed that it might regulate three biological signaling pathways, including IL-17, TNF, and PI3K-AKT, to play a protective role in stroke. Moreover, 30 key antistroke ingredients in AGNHW were identified via network-based in silico prediction and were confirmed to have known neuroprotective effects. After drug-like property evaluation and pharmacological validation in vitro, scutellarein (SCU) and caprylic acid (CA) were selected for further antistroke investigation. Finally, systems pharmacology-based analysis of CA and SCU indicated that they might exert antistroke effects via the apoptotic signaling pathway and inflammatory response, which was further validated in an in vitro stroke model. Overall, the current study proposes an integrative systems pharmacology approach to identify antistroke ingredients and demonstrate the underlying pharmacological MOA of AGNHW in stroke, which provides an alternative strategy to investigate novel traditional Chinese medicine formulas for complex diseases.

Synergistic anticancer effects of everolimus (RAD001) and Rhein on gastric cancer cells via phosphoinositide-3-kinase (PI3K)/protein kinase B (AKT)/mammalian target of rapamycin (mTOR) pathway

Everolimus (RAD001) is a mTOR inhibitor and is widely used for the treatment of gastric cancer (GC). Evidence suggests that Rhein has anticancer effect on GC. But the synergistic effect and mechanism of RAD001 and Rhein combination on GC is not clear. The current study aims to clarify the combination of RAD001 and Rhein in GC treatment. We found Rhein dose-dependently repressed MGC-803 cell viability (50% inhibition concentration (IC50) value = 94.26 μM). Rhein (80 μM) significantly suppressed GC cell proliferation and invasion. RAD001 dose-dependently repressed MGC-803 cells viability (IC50 value = 45.41 nM). The combination of Rhein and RAD001 repressed MGC-803 cells viability, invasion, and proliferation compared to the administration of Rhein or RAD001 alone. Protein levels of epithelial-mesenchymal transition (EMT)-related molecules E-cadherin, N-cadherin and Vimentin expressions were significantly affected by the combination of Rhein and RAD001. The combination of Rhein and RAD001 significantly facilitated cell apoptosis and up-regulated expressions of cell apoptosis and cycle-related protein p53, cyclin-dependent kinase 4 (CDK4) and cyclin D1 compared to the administration of Rhein or RAD001 alone. Moreover, the combination of Rhein and RAD001 repressed the expressions of phosphorylation-phosphoinositide-3-kinase (p-PI3K), p-protein kinase B (p-AKT) and p-mammalian target of rapamycin (p-mTOR). Finally, the combination of RAD001 and Rhein significantly decreased tumor weight and volume, suppressed the expressions of p-PI3K, p-Akt and p-mTOR, and repressed cell proliferation marker Ki-67 expression, which exerted synergistic cancer prevention in GC in vivo. Overall, the combination of Rhein and RAD001 exert synergistic cancer prevention in GC via PI3K/Akt/mTOR pathway.

Chemical Distance Measurement and System Pharmacology Approach Uncover the Novel Protective Effects of Biotransformed Ginsenoside C-Mc against UVB-Irradiated Photoaging

Long-term exposure to ultraviolet light induces photoaging and may eventually increase the risk of skin carcinogenesis. Rare minor ginsenosides isolating from traditional medicine Panax (ginseng) have shown biomedical efficacy as antioxidation and antiphotodamage agents. However, due to the difficulty of component extraction and wide variety of ginsenoside, the identification of active antiphotoaging ginsenoside remains a huge challenge. In this study, we proposed a novel in silico approach to identify potential compound against photoaging from 82 ginsenosides. Specifically, we calculated the shortest distance between unknown and known antiphotoaging ginsenoside set in the chemical space and applied chemical structure similarity assessment, drug-likeness screening, and ADMET evaluation for the candidates. We highlighted three rare minor ginsenosides (C-Mc, Mx, and F2) that possess high potential as antiphotoaging agents. Among them, C-Mc deriving from American ginseng (Panax quinquefolius L.) was validated by wet-lab experimental assays and showed significant antioxidant and cytoprotective activity against UVB-induced photodamage in human dermal fibroblasts. Furthermore, system pharmacology analysis was conducted to explore the therapeutic targets and molecular mechanisms through integrating global drug-target network, high quality photoaging-related gene profile from multiomics data, and skin tissue-specific expression protein network. In combination with in vitro assays, we found that C-Mc suppressed MMP production through regulating the MAPK/AP-1/NF-κB pathway and expedited collagen synthesis via the TGF-β/Smad pathway, as well as enhanced the expression of Nrf2/ARE to hold a balance of endogenous oxidation. Overall, this study offers an effective drug discovery framework combining in silico prediction and in vitro validation, uncovering that ginsenoside C-Mc has potential antiphotoaging properties and might be a novel natural agent for use in oral drug, skincare products, or functional food.

In Silico Prediction and Bioactivity Evaluation of Chemical Ingredients Against Influenza A Virus From Isatis tinctoria L

Influenza A virus (IAV) is one of the major causes of seasonal endemic diseases and unpredictable periodic pandemics. Due to the high mutation rate and drug resistance, it poses a persistent threat and challenge to public health. Isatis tinctoria L. (Banlangen, BLG), a traditional herbal medicine widely used in Asian countries, has been reported to possess strong efficacy on respiratory viruses, including IAV. However, its effective anti-IAV components and the mechanism of actions (MOAs) are not yet fully elucidated. In this study, we first summarized the chemical components and corresponding contents in BLG according to current available chemical analysis literature. We then presented a network-based in silico framework for identifying potential drug candidates against IAV from BLG. A total of 269 components in BLG were initially screened by drug-likeness and ADME (absorption, distribution, metabolism, and excretion) evaluation. Thereafter, network predictive models were built via the integration of compound–target networks and influenza virus–host proteins. We highlighted 23 compounds that possessed high potential as anti-influenza virus agents. Through experimental evaluation, six compounds, namely, eupatorin, dinatin, linarin, tryptanthrin, indirubin, and acacetin, exhibited good inhibitory activity against wild-type H1N1 and H3N2. Particularly, they also exerted significant effects on drug-resistant strains. Finally, we explored the anti-IAV MOAs of BLG and showcased the potential biological pathways by systems pharmacology analysis. In conclusion, this work provides important information on BLG regarding its use in the development of anti-IAV drugs, and the network-based prediction framework proposed here also offers a powerfulful strategy for the in silico identification of novel drug candidates from complex components of herbal medicine.

In silico tools and databases for designing cancer immunotherapy

Immunotherapy is a rapidly growing therapy for cancer which have numerous benefits over conventional treatments like surgery, chemotherapy, and radiation. Overall survival of cancer patients has improved significantly due to the use of immunotherapy. It acts as a novel pillar for treating different malignancies from their primary to the metastatic stage. Recent preferments in high-throughput sequencing and computational immunology leads to the development of targeted immunotherapy for precision oncology. In the last few decades, several computational methods and resources have been developed for designing immunotherapy against cancer. In this review, we have summarized cancer-associated genomic, transcriptomic, and mutation profile repositories. We have also enlisted in silico methods for the prediction of vaccine candidates, HLA binders, cytokines inducing peptides, and potential neoepitopes. Of note, we have incorporated the most important bioinformatics pipelines and resources for the designing of cancer immunotherapy. Moreover, to facilitate the scientific community, we have developed a web portal entitled ImmCancer (https://webs.iiitd.edu.in/raghava/immcancer/), comprises cancer immunotherapy tools and repositories.

Immune Effect of Active Components of Traditional Chinese Medicine on Triple-Negative Breast Cancer

Triple-negative breast cancers are heterogeneous, poorly prognostic, and metastatic malignancies that result in a high risk of death for patients. Targeted therapy for triple-negative breast cancer has been extremely challenging due to the lack of expression of estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2. Clinical treatment regimens for triple-negative breast cancer are often based on paclitaxel and platinum drugs, but drug resistance and side effects from the drugs frequently lead to treatment failure, thus requiring the development of new therapeutic platforms. In recent years, research on traditional Chinese medicine in modulating the immune function of the body has shown that it has the potential to be an effective treatment option against triple-negative breast cancer. Active components of herbal medicines such as alkaloids, flavonoids, polyphenols, saponins, and polysaccharides have been shown to inhibit cancer cell proliferation and metastasis by activating inflammatory immune responses and can modulate tumor-related signaling pathways to further inhibit the invasion of triple-negative breast cancer. This paper reviews the immunomodulatory mechanisms of different herbal active ingredients against triple-negative breast cancer and provides an outlook on the challenges and directions of development for the treatment of triple-negative breast cancer with herbal active ingredients.

Integrative Analysis to Uncover the Molecular Mechanisms of Caesalpinia sappan L. for Anti-Cancer Activity

Objectives: Caesalpinia Sappan L. is a traditional Chinese medicine with a long history. Recent studies have confirmed that Sappan has an antitumor effect, but its specific mechanism is still unclear. Methods: In this study, we used network pharmacology to predict the target and signal pathway of Sappan. In addition, the Cancer Genome Atlas and cancer cell lines encyclopedia large-scale genomic databases were used to analyze the relationship between different subtypes of Akt. Based on molecular docking technology, the interaction mode between small molecule compounds and protein targets was explored. Finally, we studied the effect of Sappan on Akt protein expression by Western blot in vitro. Results: AKT1 and AKT2 were significantly expressed in breast cancer cells, but they were significantly different from AKT3. Finally, molecular docking analysis showed that (3R,5R)-1,3,4,5-tetrakis(((E)-3-(3,4-dihydroxyphenyl)acryloyl)oxy)cyclohexane-1-carboxylic acid had a very ideal binding mode with Akt. Subsequent experiments showed that Sappan extract could induce apoptosis of HepG2 cells in a dose-dependent manner, and down regulate the phosphorylation level of Akt protein thr308 in a dose-dependent manner. Conclusions: This study provides new ideas for Sappan's anticancer research through the strategy of system pharmacology.

Schisandrin B promotes TH1 cell differentiation by targeting STAT1

Schisandrin B (Sch B) is the major active ingredient of the traditional Chinese medicine Schisandra chinensis and has antitumor activity, anti-inflammatory activity. CD4⁺ Th subsets orchestrate immune responses to plenty of pathogen infections and participate in the pathogenesis of many immune-related diseases. However, little is known about the relationship between Sch B and T cell differentiation. Here, we showed that Sch B might participate in T cell receptor signaling pathway by using the TCMIO database. Importantly, Sch B promoted T_H1 cell differentiation. Furthermore, Sch B did not affect T_H2 cell and Treg differentiation. Mechanismly, Sch B increased the level of IFN-γ of CD4⁺ T cells by upregulating the phosphorylation of STAT1 protein. Then, STAT1 promoted T-bet expression in CD4⁺ T cells. In conclusion, Sch B modulates the differentiation of naïve CD4⁺ T cells into T_H1 subset by STAT1/T-bet signaling, which may have the potential for the treatment of T cell-mediated-immune diseases.

CanImmunother: a manually curated database for identification of cancer immunotherapies associating with biomarkers, targets, and clinical effects

As immunotherapy is evolving into an essential armamentarium against cancers, numerous translational studies associated with relevant biomarkers, targets, and clinical effects have been reported in recent years. However, a large amount of associated experimental data remains unexplored due to the difficulty in accessibility and utilization. Here, we established a comprehensive high-quality database for cancer immunotherapy called CanImmunother (http://www.biomedical-web.com/cancerit/) through manual curation on 4515 publications. CanImmunother contains 3267 experimentally validated associations between 218 cancer sub-types across 34 body parts and 484 immunotherapies with 642 biomarkers, 108 targets, and 121 control therapies. Each association was manually curated by professional curators, incorporated with valuable annotation and cross references, and assigned with an association score for prioritization. To help clinicians and researchers in identifying and discovering better cancer immunotherapy and their respective biomarkers and targets, CanImmunother offers user-friendly web applications including search, browse, excel table, association prioritization, and network visualization. CanImmunother presents a landscape of experimental cancer immunotherapy association data, serving as a useful resource to improve our insight and to facilitate further discovery of advanced immunotherapy options for cancer patients.

Hansenia weberbaueriana (Fedde ex H.Wolff) Pimenov & Kljuykov Extract Suppresses Proliferation of HepG2 Cells via the PTEN-PI3K-AKT Pathway Uncovered by Integrating Network Pharmacology and Iin Vitro Experiments

Previous studies have shown that Hansenia weberbaueriana (Fedde ex H.Wolff) Pimenov & Kljuykov extracts (HWEs) have antitumor activity, but their mechanism in vitro is still unclear. In this study, we first combined network pharmacology with experimental evaluation and applied a comprehensive strategy to explore and prove the therapeutic potential and potential mechanism of HWE. The mRNA expression profiles of PTEN, PIK3A, and AKT1 are from the Cancer Cell Line Encyclopedia (CCLE) of the Broad Institute. Our results showed that HWE has a good inhibition on HepG2 cells, and a slight inhibition on other cells. The results of the CCLE database showed that PTEN/PIK3A/AKT1 mRNA expression was up-regulated in HepG2 cells. Through further study, it was found that HWE increased the release of LDH, induced early and late apoptosis, and increased ROS levels in HepG2 cells. Western blot showed that HWE regulates the expression of mitochondrial apoptosis-related proteins. Meanwhile, the expression of PTEN was increased, and the expression of phosphorylated PI3K and Akt was down-regulated after HWE treatment. Our results show that HWE promotes HepG2 cell apoptosis via the PTEN-PI3K-Akt signaling pathway. This study is the first to report the potential role of HWE in the treatment of liver cancer.

In silico identification of natural products from Traditional Chinese Medicine for cancer immunotherapy

Advances in immunotherapy have revolutionized treatments in many types of cancer. Traditional Chinese Medicine (TCM), which has a long history of clinical adjuvant application against cancer, is emerging as an important medical resource for developing innovative cancer treatments, including immunotherapy. In this study, we developed a quantitative and systems pharmacology-based framework to identify TCM-derived natural products for cancer immunotherapy. Specifically, we integrated 381 cancer immune response-related genes and a compound-target interaction network connecting 3273 proteins and 766 natural products from 66 cancer-related herbs based on literature-mining. Via systems pharmacology-based prediction, we uncovered 182 TCM-derived natural products having potential anti-tumor immune responses effect. Importantly, 32 of the 49 most promising natural products (success rate = 65.31%) are validated by multiple evidence, including published experimental data from clinical studies, in vitro and in vivo assays. We further identified the mechanism-of-action of TCM in cancer immunotherapy using network-based functional enrichment analysis. We showcased that three typical natural products (baicalin, wogonin, and oroxylin A) in Huangqin (Scutellaria baicalensis Georgi) potentially overcome resistance of known oncology agents by regulating tumor immunosuppressive microenvironments. In summary, this study offers a novel and effective systems pharmacology infrastructure for potential cancer immunotherapeutic development by exploiting the medical wealth of natural products in TCM.

HERB: a high-throughput experiment- and reference-guided database of traditional Chinese medicine

Pharmacotranscriptomics has become a powerful approach for evaluating the therapeutic efficacy of drugs and discovering new drug targets. Recently, studies of traditional Chinese medicine (TCM) have increasingly turned to high-throughput transcriptomic screens for molecular effects of herbs/ingredients. And numerous studies have examined gene targets for herbs/ingredients, and link herbs/ingredients to various modern diseases. However, there is currently no systematic database organizing these data for TCM. Therefore, we built HERB, a high-throughput experiment- and reference-guided database of TCM, with its Chinese name as BenCaoZuJian. We re-analyzed 6164 gene expression profiles from 1037 high-throughput experiments evaluating TCM herbs/ingredients, and generated connections between TCM herbs/ingredients and 2837 modern drugs by mapping the comprehensive pharmacotranscriptomics dataset in HERB to CMap, the largest such dataset for modern drugs. Moreover, we manually curated 1241 gene targets and 494 modern diseases for 473 herbs/ingredients from 1966 references published recently, and cross-referenced this novel information to databases containing such data for drugs. Together with database mining and statistical inference, we linked 12 933 targets and 28 212 diseases to 7263 herbs and 49 258 ingredients and provided six pairwise relationships among them in HERB. In summary, HERB will intensively support the modernization of TCM and guide rational modern drug discovery efforts. And it is accessible through http://herb.ac.cn/.