Therapeutic target database 2020: enriched resource for facilitating research and early development of targeted therapeutics

A Genome-Wide Screen Identifies PDPK1 as a Target to Enhance the Efficacy of MEK1/2 Inhibitors in NRAS Mutant Melanoma

Melanomas frequently harbor activating NRAS mutations. However, limited advance has been made in developing targeted therapy options for patients with NRAS mutant melanoma. MEK inhibitors (MEKi) show modest efficacy in the clinic and their actions need to be optimized. In this study, we performed a genome-wide CRISPR-Cas9-based screen and demonstrated that loss of phosphoinositide-dependent kinase-1 (PDPK1) enhances the efficacy of MEKi. The synergistic effects of PDPK1 loss and MEKi was validated in NRAS mutant melanoma cell lines using pharmacologic and molecular approaches. Combined PDPK1 inhibitors (PDPK1i) with MEKi suppressed NRAS mutant xenograft growth and induced gasdermin E-associated pyroptosis. In an immune-competent allograft model, PDPK1i+MEKi increased the ratio of intratumoral CD8+ T cells, delayed tumor growth, and prolonged survival; the combination treatment was less effective against tumors in immune-deficient mice. These data suggest PDPK1i+MEKi as an efficient immunostimulatory strategy against NRAS mutant melanoma.

SIGNIFICANCE

Targeting PDPK1 stimulates antitumor immunity and sensitizes NRAS mutant melanoma to MEK inhibition, providing rationale for the clinical development of a combinatorial approach for treating patients with melanoma.

A Novel Based-Network Strategy to Identify Phytochemicals from Radix Salviae Miltiorrhizae (Danshen) for Treating Alzheimer's Disease

Alzheimer’s disease (AD) is a common age-related neurodegenerative disease that strikes millions worldwide. Herein, we demonstrate a new approach based on network target to identify anti-AD compounds from Danshen. Network pharmacology and molecular docking were employed to establish the DS-AD network, which mainly involved apoptosis of neuron cells. Then network scoring was confirmed via Connectivity Map analysis. M308 (Danshenxinkun D) was an anti-AD candidate with a high score (p < 0.01). Furthermore, we conducted ex vivo experiments with H2O2-treated PC12 cells to verify the neuroprotective effect of Salvia miltiorrhiza-containing plasma (SMP), and UPLC-Q-TOF/MS and RT-qPCR were performed to demonstrate the anti-AD activity of M308 from SMP. Results revealed that SMP could enhance cell viability and level of acetylcholine. AO/EB staining and Mitochondrial membrane potential (MMP) analysis showed that SMP significantly suppressed apoptosis, which may be due to anti-oxidative stress activity. Moreover, the effects of M308 and SMP on expressions of PSEN1, DRD2, and APP mRNA were consistent, and M308 can significantly reverse the expression of PSEN1 and DRD2 mRNA in H2O2-treated PC12 cells. The strategy based on the network could be employed to identify anti-AD compounds from Chinese herbs. Notably, M308 stands out as a promising anti-AD candidate for development.

Network Pharmacology and Bioinformatics Methods Reveal the Mechanism of Berberine in the Treatment of Ischaemic Stroke

Aim

To elucidate the mechanism of action of berberine on ischaemic stroke based on network pharmacology, bioinformatics, and experimental verification.

Methods

Berberine-related long noncoding RNAs (lncRNAs) were screened from public databases. Differentially expressed lncRNAs in ischaemic stroke were retrieved from the Gene Expression Omnibus (GEO) database. GSE102541 was comprehensively analysed using GEO2R. The correlation between lncRNAs and ischaemic stroke was evaluated by the mammalian noncoding RNA-disease repository (MNDR) database. The component-target-disease network and protein-protein interaction (PPI) network of berberine in the treatment of ischaemic stroke were constructed by using network pharmacology. We then performed gene ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) enrichment analyses. Finally, according to the molecular docking analysis and the binding probability between the lncRNA and key proteins, the effectiveness of the results was further verified by in vitro experiments.

Results

After matching stroke-related lncRNAs with berberine-related lncRNAs, four genes were selected as potential targets of berberine in the treatment of ischaemic stroke. Subsequently, lncRNA H19 was identified as the potential crucial regulatory lncRNA of berberine. Here, 52 target proteins of berberine in the treatment of ischaemic stroke were identified through database mining. Through topological analysis, 20 key targets were identified which were enriched in inflammation, apoptosis, and immunity. Molecular docking results showed that MAPK8, JUN, and EGFR were central genes. Finally, in vitro experiments demonstrated that lncRNA H19, p-JNK1/JNK1, p-c-Jun/c-Jun, and EGFR expressions were significantly increased in hypoxia-treated SH-SY5Y cells and were restored by berberine treatment.

Conclusion

The potential targets and biological effects of berberine in the treatment of ischaemic stroke were predicted in this study. The lncRNA H19/EGFR/JNK1/c-Jun signalling pathway may be a key mechanism of berberine-induced neuroprotection in ischaemic stroke.

Artificial intelligence and machine-learning approaches in structure and ligand-based discovery of drugs affecting central nervous system

CNS disorders are indications with a very high unmet medical needs, relatively smaller number of available drugs, and a subpar satisfaction level among patients and caregiver. Discovery of CNS drugs is extremely expensive affair with its own unique challenges leading to extremely high attrition rates and low efficiency. With explosion of data in information age, there is hardly any aspect of life that has not been touched by data driven technologies such as artificial intelligence (AI) and machine learning (ML). Drug discovery is no exception, emergence of big data via genomic, proteomic, biological, and chemical technologies has driven pharmaceutical giants to collaborate with AI oriented companies to revolutionise drug discovery, with the goal of increasing the efficiency of the process. In recent years many examples of innovative applications of AI and ML techniques in CNS drug discovery has been reported. Research on therapeutics for diseases such as schizophrenia, Alzheimer's and Parkinsonism has been provided with a new direction and thrust from these developments. AI and ML has been applied to both ligand-based and structure-based drug discovery and design of CNS therapeutics. In this review, we have summarised the general aspects of AI and ML from the perspective of drug discovery followed by a comprehensive coverage of the recent developments in the applications of AI/ML techniques in CNS drug discovery.

Industrializing AI-powered drug discovery: lessons learned from the Patrimony computing platform

INTRODUCTION

As a mid-size international pharmaceutical company, we initiated four years ago the launch of a dedicated high-throughput computing platform supporting drug discovery. The platform named "Patrimony" was built-up on the initial predicate to capitalize on our proprietary data while leveraging public data sources in order to foster a Computational Precision Medicine approach with the power of Artificial Intelligence.

AREAS COVERED

Specifically, Patrimony is designed to identify novel therapeutic target candidates. With several successful use cases in Immuno-inflammatory diseases, and current ongoing extension to applications to Oncology and Neurology, we document how this industrial computational platform has had a transformational impact on our R&D, making it more competitive, as well time and cost effective through a model-based educated selection of therapeutic targets and drug candidates.

EXPERT OPINION

We report our achievements, but also our challenges in implementing data access and governance processes, building-up hardware and user interfaces, and acculturing scientists to use predictive models to inform decisions.

Modeling Kaempferol as a Potential Pharmacological Agent for COVID-19/PF Co-Occurrence Based on Bioinformatics and System Pharmacological Tools

Objective: People suffering from coronavirus disease 2019 (COVID-19) are prone to develop pulmonary fibrosis (PF), but there is currently no definitive treatment for COVID-19/PF co-occurrence. Kaempferol with promising antiviral and anti-fibrotic effects is expected to become a potential treatment for COVID-19 and PF comorbidities. Therefore, this study explored the targets and molecular mechanisms of kaempferol against COVID-19/PF co-occurrence by bioinformatics and network pharmacology.

Methods: Various open-source databases and Venn Diagram tool were applied to confirm the targets of kaempferol against COVID-19/PF co-occurrence. Protein-protein interaction (PPI), MCODE, key transcription factors, tissue-specific enrichment, molecular docking, Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were used to clarify the influential molecular mechanisms of kaempferol against COVID-19 and PF comorbidities.

Results: 290 targets and 203 transcription factors of kaempferol against COVID-19/PF co-occurrence were captured. Epidermal growth factor receptor (EGFR), proto-oncogene tyrosine-protein kinase SRC (SRC), mitogen-activated protein kinase 3 (MAPK3), mitogen-activated protein kinase 1 (MAPK1), mitogen-activated protein kinase 8 (MAPK8), RAC-alpha serine/threonine-protein kinase (AKT1), transcription factor p65 (RELA) and phosphatidylinositol 4,5-bisphosphate 3-kinase catalytic subunit alpha isoform (PIK3CA) were identified as the most critical targets, and kaempferol showed effective binding activities with the above critical eight targets. Further, anti-COVID-19/PF co-occurrence effects of kaempferol were associated with the regulation of inflammation, oxidative stress, immunity, virus infection, cell growth process and metabolism. EGFR, interleukin 17 (IL-17), tumor necrosis factor (TNF), hypoxia inducible factor 1 (HIF-1), phosphoinositide 3-kinase/AKT serine/threonine kinase (PI3K/AKT) and Toll-like receptor signaling pathways were identified as the key anti-COVID-19/PF co-occurrence pathways.

Conclusion: Kaempferol is a candidate treatment for COVID-19/PF co-occurrence. The underlying mechanisms may be related to the regulation of critical targets (EGFR, SRC, MAPK3, MAPK1, MAPK8, AKT1, RELA, PIK3CA and so on) and EGFR, IL-17, TNF, HIF-1, PI3K/AKT and Toll-like receptor signaling pathways. This study contributes to guiding development of new drugs for COVID-19 and PF comorbidities.

Most Pathways Can Be Related to the Pathogenesis of Alzheimer’s Disease

Alzheimer’s disease (AD) is a complex neurodegenerative disorder. The relative contribution of the numerous underlying functional mechanisms is poorly understood. To comprehensively understand the context and distribution of pathways that contribute to AD, we performed text-mining to generate an exhaustive, systematic assessment of the breadth and diversity of biological pathways within a corpus of 206,324 dementia publication abstracts. A total of 91% (325/335) of Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways have publications containing an association via at least 5 studies, while 63% of pathway terms have at least 50 studies providing a clear association with AD. Despite major technological advances, the same set of top-ranked pathways have been consistently related to AD for 30 years, including AD, immune system, metabolic pathways, cholinergic synapse, long-term depression, proteasome, diabetes, cancer, and chemokine signaling. AD pathways studied appear biased: animal model and human subject studies prioritize different AD pathways. Surprisingly, human genetic discoveries and drug targeting are not enriched in the most frequently studied pathways. Our findings suggest that not only is this disorder incredibly complex, but that its functional reach is also nearly global. As a consequence of our study, research results can now be assessed in the context of the wider AD literature, supporting the design of drug therapies that target a broader range of mechanisms. The results of this study can be explored at www.adpathways.org.

Multi-Level Biological Network Analysis and Drug Repurposing Based on Leukocyte Transcriptomics in Severe COVID-19: In Silico Systems Biology to Precision Medicine

The coronavirus disease 2019 (COVID-19) pandemic causes many morbidity and mortality cases. Despite several developed vaccines and antiviral therapies, some patients experience severe conditions that need intensive care units (ICU); therefore, precision medicine is necessary to predict and treat these patients using novel biomarkers and targeted drugs. In this study, we proposed a multi-level biological network analysis framework to identify key genes via protein–protein interaction (PPI) network analysis as well as survival analysis based on differentially expressed genes (DEGs) in leukocyte transcriptomic profiles, discover novel biomarkers using microRNAs (miRNA) from regulatory network analysis, and provide candidate drugs targeting the key genes using drug–gene interaction network and structural analysis. The results show that upregulated DEGs were mainly enriched in cell division, cell cycle, and innate immune signaling pathways. Downregulated DEGs were primarily concentrated in the cellular response to stress, lysosome, glycosaminoglycan catabolic process, and mature B cell differentiation. Regulatory network analysis revealed that hsa-miR-6792-5p, hsa-let-7b-5p, hsa-miR-34a-5p, hsa-miR-92a-3p, and hsa-miR-146a-5p were predicted biomarkers. CDC25A, GUSB, MYBL2, and SDAD1 were identified as key genes in severe COVID-19. In addition, drug repurposing from drug–gene and drug–protein database searching and molecular docking showed that camptothecin and doxorubicin were candidate drugs interacting with the key genes. In conclusion, multi-level systems biology analysis plays an important role in precision medicine by finding novel biomarkers and targeted drugs based on key gene identification.

Bioinformatics and System Biology Approach to Reveal the Interaction Network and the Therapeutic Implications for Non-Small Cell Lung Cancer Patients With COVID-19

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the leading cause of coronavirus disease-2019 (COVID-19), is an emerging global health crisis. Lung cancer patients are at a higher risk of COVID-19 infection. With the increasing number of non-small-cell lung cancer (NSCLC) patients with COVID-19, there is an urgent need of efficacious drugs for the treatment of COVID-19/NSCLC.

Methods: Based on a comprehensive bioinformatic and systemic biological analysis, this study investigated COVID-19/NSCLC interactional hub genes, detected common pathways and molecular biomarkers, and predicted potential agents for COVID-19 and NSCLC.

Results: A total of 122 COVID-19/NSCLC interactional genes and 21 interactional hub genes were identified. The enrichment analysis indicated that COVID-19 and NSCLC shared common signaling pathways, including cell cycle, viral carcinogenesis, and p53 signaling pathway. In total, 10 important transcription factors (TFs) and 44 microRNAs (miRNAs) participated in regulations of 21 interactional hub genes. In addition, 23 potential candidates were predicted for the treatment of COVID-19 and NSCLC.

Conclusion: This study increased our understanding of pathophysiology and screened potential drugs for COVID-19 and NSCLC.

Mechanisms of Quercetin against atrial fibrillation explored by network pharmacology combined with molecular docking and experimental validation

Atrial fibrillation (AF) is a common atrial arrhythmia for which there is no specific therapeutic drug. Quercetin (Que) has been used to treat cardiovascular diseases such as arrhythmias. In this study, we explored the mechanism of action of Que in AF using network pharmacology and molecular docking. The chemical structure of Que was obtained from Pubchem. TCMSP, Swiss Target Prediction, Drugbank, STITCH, Pharmmapper, CTD, GeneCards, DISGENET and TTD were used to obtain drug component targets and AF-related genes, and extract AF and normal tissue by GEO database differentially expressed genes by GEO database. The top targets were IL6, VEGFA, JUN, MMP9 and EGFR, and Que for AF treatment might involve the role of AGE-RAGE signaling pathway in diabetic complications, MAPK signaling pathway and IL-17 signaling pathway. Molecular docking showed that Que binds strongly to key targets and is differentially expressed in AF. In vivo results showed that Que significantly reduced the duration of AF fibrillation and improved atrial remodeling, reduced p-MAPK protein expression, and inhibited the progression of AF. Combining network pharmacology and molecular docking approaches with in vivo studies advance our understanding of the intensive mechanisms of Quercetin, and provide the targeted basis for clinical Atrial fibrillation treatment.

Pharmacological mechanisms of sodium-glucose co-transporter 2 inhibitors in heart failure with preserved ejection fraction

BACKGROUND

More and more evidence indicates sodium-glucose co-transporter 2 inhibitors (SGLT2is) may display clinical benefits for heart failure with preserved ejection fraction (HFpEF). However, the mechanisms of the action remain unclear.

METHODS

A systematic pharmacology-based strategy was applied for predicting the potential molecular mechanisms of SGLT2is in HFpEF. The potential targets of SGLT2is and HFpEF were contained from diverse databases. After networks were constructed, Metascape was applied to functional enrichment. Moreover, the key findings were validated through molecular docking.

RESULTS

We obtained 487 SGLT2is related targets and 1505 HFpEF related targets. The networks showed the complex relationship of HFpEF-target-HFpEF. The results of functional enrichment analysis suggested that several biological processes, including muscle system process, inflammatory response, vasculature development, heart development, regulation of MAPK cascade, positive regulation of ion transport, negative regulation of cell population proliferation, cellular response to nitrogen compound, apoptotic signaling pathway, multicellular organismal homeostasis, response to oxidative stress, regulation of cell adhesion, positive regulation of cell death, response to growth factor, and cellular response to lipid, and signaling pathways, such as cardiomyopathy, cAMP signaling pathway, cytokine-cytokine receptor interaction, apoptosis, MAPK signaling pathway, HIF-1 signaling pathway, calcium signaling pathway, and NF-kappa B signaling pathway. Finally, we validated the interactions and combinations of SGLT2is and core targets.

CONCLUSION

SGLT2is play the potential role of anti-HFpEF through the direct or indirect synergy of multiple targets and pathways. Our study promotes the explanation of the molecular mechanisms of SGLT2is in HFpEF.

The integrative analysis of competitive endogenous RNA regulatory networks in osteoporosis

Osteoporosis (OP) is a common bone disease of old age resulting from the imbalance between bone resorption and bone formation. CircRNAs are a class of endogenous non-coding RNAs (ncRNAs) involved in gene regulation and may play important roles in the development of OP. Here, we aimed to discover the OP‑related circRNA-miRNA-mRNA (ceRNA) network and the potential mechanisms. Six microarray datasets were obtained from the GEO database and the OP‑related differentially expressed genes (DEGs), circRNAs (DECs), and miRNAs (DEMs) were screened out from these datasets. Then, combined with the prediction of the relationships between DEGs, DEMs, and DECs, a ceRNA network containing 7 target circRNAs, 5 target miRNAs, and 38 target genes was constructed. Then the RNA-seq verification by using total RNAs isolated from the femurs of normal and ovariectomized Wistar rats indicated that MFAP5, CAMK2A, and RGS4 in the ceRNA network were closely associated with osteoporosis. Function enrichment analysis indicated that the target circRNAs, miRNAs, and genes were involved in the process of MAPK cascade, hormone stimulus, cadherin binding, rRNA methyltransferase, PI3K-Akt signaling pathway, and Vitamin digestion and absorption, etc. Then a circRNA-miRNA-hub gene subnetwork was constructed and the qRT-PCR analysis of human bone tissues from the femoral head was used to confirm that the transcription of hsa_circR_0028877, hsa_circR_0082916, DIRAS2, CAMK2A, and MAPK4 showed a significant correlation with osteogenic genes. Besides, the two axes of hsa_circR_0028877/hsa-miR-1273f/CAMK2A and hsa_circR_0028877/hsa-miR-1273f/DIRAS2 conformed to be closely associated with OP. Additionally, by constructing a drug-target gene network, RKI-1447, FRAX486, Hyaluronic, and Fostamatinib were identified as therapeutic options for OP. Our study revealed the potential links between circRNAs, miRNAs, and mRNAs in OP, suggesting that the ceRNA mechanism might contribute to the occurrence of OP.

Repurposing Histaminergic Drugs in Multiple Sclerosis

Multiple sclerosis is an autoimmune disease with a strong neuroinflammatory component that contributes to severe demyelination, neurodegeneration and lesions formation in white and grey matter of the spinal cord and brain. Increasing attention is being paid to the signaling of the biogenic amine histamine in the context of several pathological conditions. In multiple sclerosis, histamine regulates the differentiation of oligodendrocyte precursors, reduces demyelination, and improves the remyelination process. However, the concomitant activation of histamine H1–H4 receptors can sustain either damaging or favorable effects, depending on the specifically activated receptor subtype/s, the timing of receptor engagement, and the central versus peripheral target district. Conventional drug development has failed so far to identify curative drugs for multiple sclerosis, thus causing a severe delay in therapeutic options available to patients. In this perspective, drug repurposing offers an exciting and complementary alternative for rapidly approving some medicines already approved for other indications. In the present work, we have adopted a new network-medicine-based algorithm for drug repurposing called SAveRUNNER, for quantifying the interplay between multiple sclerosis-associated genes and drug targets in the human interactome. We have identified new histamine drug-disease associations and predicted off-label novel use of the histaminergic drugs amodiaquine, rupatadine, and diphenhydramine among others, for multiple sclerosis. Our work suggests that selected histamine-related molecules might get to the root causes of multiple sclerosis and emerge as new potential therapeutic strategies for the disease.

Pharmacological Mechanism of Shen Huang Chong Ji for Treating Alzheimer's Disease Based on Network Pharmacology and Experimental Validation

The traditional Chinese medicine (TCM) formula, Sheng Huang Chong Ji (SHCJ) is largely applied for treating Alzheimer's disease (AD), but not much is known regarding its active compounds, molecular targets, and mechanism of action. The current study aimed to predict the potential molecular mechanism of SHCJ against AD based on network pharmacology combined with in vitro validation. Using public databases, SHCJ's active compounds, their potential targets, and AD-related genes were screened, while Cytoscape Version 3.7.2 was used to build protein-protein interaction (PPI) and compound-disease-target (C-D-T) networks. Analysis of enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and Gene Ontology (GO) terms was then carried out in R 4.0.2, including associated packages. Subsequently, molecular docking analysis was performed with AutoDock Vina 1.1.2, with intro experiments involving SH-SY5Y cells used to further investigate the mechanism of SHCJ against AD. Finally, a total of 56 active compounds of SHCJ and 192 SHCJ-AD-related targets were identified. Quercetin was identified as the top potential candidate agent. HSP90AA1, AKT1, and MAPK1 represent potential therapeutic targets. The PI3K-Akt signaling pathway potentially represents a core one mediating the effects of SHCJ against AD. Additionally, molecular docking analysis indicated that quercetin could combine well with AKT1 and multiple apoptosis-related target genes. During cell experiments, a significant increase in cell viability along with a decrease in Aβ _25-35-induced apoptosis was observed after treatment with SHCJ. Furthermore, SHCJ significantly increased the phosphorylation of PI3K and Akt while reversing Aβ _25-35-induced apoptosis-related protein expression downregulation.

Sleep and Late-Onset Alzheimer's Disease: Shared Genetic Risk Factors, Drug Targets, Molecular Mechanisms, and Causal Effects

Late-onset Alzheimer's disease (AD) is associated with sleep-related phenotypes (SRPs). The fact that whether they share a common genetic etiology remains largely unknown. We explored the shared genetics and causality between AD and SRPs by using high-definition likelihood (HDL), cross-phenotype association study (CPASSOC), transcriptome-wide association study (TWAS), and bidirectional Mendelian randomization (MR) in summary-level data for AD (N = 455,258) and summary-level data for seven SRPs (sample size ranges from 359,916 to 1,331,010). AD shared a strong genetic basis with insomnia (r _g = 0.20; p = 9.70 × 10^-5), snoring (r _g = 0.13; p = 2.45 × 10^-3), and sleep duration (r _g = -0.11; p = 1.18 × 10^-3). The CPASSOC identifies 31 independent loci shared between AD and SRPs, including four novel shared loci. Functional analysis and the TWAS showed shared genes were enriched in liver, brain, breast, and heart tissues and highlighted the regulatory roles of immunological disorders, very-low-density lipoprotein particle clearance, triglyceride-rich lipoprotein particle clearance, chylomicron remnant clearance, and positive regulation of T-cell-mediated cytotoxicity pathways. Protein-protein interaction analysis identified three potential drug target genes (APOE, MARK4, and HLA-DRA) that interacted with known FDA-approved drug target genes. The CPASSOC and TWAS demonstrated three regions 11p11.2, 6p22.3, and 16p11.2 may account for the shared basis between AD and sleep duration or snoring. MR showed insomnia had a causal effect on AD (OR_IVW = 1.02, P _IVW = 6.7 × 10^-6), and multivariate MR suggested a potential role of sleep duration and major depression in this association. Our findings provide strong evidence of shared genetics and causation between AD and sleep abnormalities and advance our understanding of the genetic overlap between them. Identifying shared drug targets and molecular pathways can be beneficial for treating AD and sleep disorders more efficiently.

CDCDB: A large and continuously updated drug combination database

In recent years, due to the complementary action of drug combinations over mono-therapy, the multiple-drugs for multiple-targets paradigm has received increased attention to treat bacterial infections and complex diseases. Although new drug combinations screening has benefited from experimental tests like automated high throughput screening, it is limited due to the large number of possible drug combinations. The task of drug combination screening can be streamlined through computational methods and models. Such models require up-to-date databases; however, existing databases are static and consist of the data collected at the time of their creation. This paper introduces the Continuous Drug Combination Database (CDCDB), a continuously updated drug combination database. The CDCDB includes over 40,795 drug combinations, of which 17,107 are unique combinations consisting of more than 4,129 individual drugs, curated from ClinicalTrials.gov, the FDA Orange Book^®, and patents. To create CDCDB, we use various methods, including natural language processing techniques, to improve the process of drug combination discovery, ensuring that our database can be used for drug synergy prediction. Website: https://icc.ise.bgu.ac.il/medical_ai/CDCDB/.

Measurement(s)	drug combination effect modeling • drug combination effect modeling
Technology Type(s)	Text mining • Clinical Trials Informatics System
Factor Type(s)	Medicine
Sample Characteristic - Organism	Homo sapiens

Exploring targets and signaling pathways of paeonol involved in relieving inflammation based on modern technology

Paeonol, derived from natural plants (Moutan Cortex), has a wide range of biological effects, including anti-inflammatory and antitumor effects as well as favorable effects against cardiovascular and neurodegenerative diseases. The anti-inflammatory action is the main pharmacological activity of paeonol and has the greatest clinical relevance. However, the anti-inflammatory mechanism of paeonol has not been reported in sufficient detail. We systematically analyzed the anti-inflammatory mechanism of paeonol using network pharmacological databases and platforms, including TCMSP, Swiss TargetPrediction, OMIM, DrugBank, TTD, Jevnn, STRING11.0, and Metascape. Furthermore, we used high-throughput molecular docking method to prove the results of the above analyses, providing a reference for exploring the mechanism of paeonol and developing targeted drugs.

The potential mechanism of Bupleurum against anxiety was predicted by network pharmacology study and molecular docking

Bupleurum chinense DC. (Chaihu) is a traditional Chinese medicine (TCM) used in the treatment of anxiety. But the anxiolytic mechanisms of bupleurum are still unclear. Therefore, this unknown is predicted by network pharmacology study with molecular docking in the present study. The components of bupleurum were obtained from the databases. Genes associated with components and disease were also provided by databases. Overlapping genes between components and disease were analyzed. The network of medicine-components-targets-disease was constructed, visualized, and analyzed. Protein-protein interaction (PPI), gene ontology (GO), pathway enrichment (KEGG) and molecular docking were conducted to predict the potential mechanisms of bupleurum on anxiety. A total of 9 bioactive components derived from bupleurum with 80 target genes were involved in anxiety. Neurotransmitter receptor activity, G protein-coupled amine receptor activity, regulation of blood circulation, neuroactive ligand-receptor interaction, calcium signaling pathway and salivary secretion may play significant roles in the anxiolytic of bupleurum. Molecular docking implicated that ACHE and MAOA showed high affinity for stigmasterol. Based on network pharmacology study with molecular docking, multi-component-multi-target-multi-pathway action mode of bupleurum on anxiety was elaborated. Stigmasterol might be the core bioactive component, while ACHE and MAOA might be the core target genes in the pharmacological profile of bupleurum on anxiety.

Identification of hub pathways and drug candidates in gastric cancer through systems biology

Gastric cancer is the fourth cause of cancer death globally, and gastric adenocarcinoma is its most common type. Efforts for the treatment of gastric cancer have increased its median survival rate by only seven months. Due to the relatively low response of gastric cancer to surgery and adjuvant therapy, as well as the complex role of risk factors in its incidences, such as protein-pomp inhibitors (PPIs) and viral and bacterial infections, we aimed to study the pathological pathways involved in gastric cancer development and investigate possible medications by systems biology and bioinformatics tools. In this study, the protein-protein interaction network was analyzed based on microarray data, and possible effective compounds were discovered. Non-coding RNA versus coding RNA interaction network and gene-disease network were also reconstructed to better understand the underlying mechanisms. It was found that compounds such as amiloride, imatinib, omeprazole, troglitazone, pantoprazole, and fostamatinib might be effective in gastric cancer treatment. In a gene-disease network, it was indicated that diseases such as liver carcinoma, breast carcinoma, liver fibrosis, prostate cancer, ovarian carcinoma, and lung cancer were correlated with gastric adenocarcinoma through specific genes, including hgf, mt2a, mmp2, fbn1, col1a1, and col1a2. It was shown that signaling pathways such as cell cycle, cell division, and extracellular matrix organization were overexpressed, while digestion and ion transport pathways were underexpressed. Based on a multilevel systems biology analysis, hub genes in gastric adenocarcinoma showed participation in the pathways such as focal adhesion, platelet activation, gastric acid secretion, HPV infection, and cell cycle. PPIs are hypothesized to have a therapeutic effect on patients with gastric cancer. Fostamatinib seems a potential therapeutic drug in gastric cancer due to its inhibitory effect on two survival genes. However, these findings should be confirmed through experimental investigations.

In silico Methods for Identification of Potential Therapeutic Targets

At the initial stage of drug discovery, identifying novel targets with maximal efficacy and minimal side effects can improve the success rate and portfolio value of drug discovery projects while simultaneously reducing cycle time and cost. However, harnessing the full potential of big data to narrow the range of plausible targets through existing computational methods remains a key issue in this field. This paper reviews two categories of in silico methods—comparative genomics and network-based methods—for finding potential therapeutic targets among cellular functions based on understanding their related biological processes. In addition to describing the principles, databases, software, and applications, we discuss some recent studies and prospects of the methods. While comparative genomics is mostly applied to infectious diseases, network-based methods can be applied to infectious and non-infectious diseases. Nonetheless, the methods often complement each other in their advantages and disadvantages. The information reported here guides toward improving the application of big data-driven computational methods for therapeutic target discovery.

Graphical abstract

Wuzi Yanzong pill attenuates MPTP-induced Parkinson's Disease via PI3K/Akt signaling pathway

Wuzi Yanzong Pill (WYP) was found to play a protective role on nerve cells and neurological diseases, however the molecular mechanism is unclear. To understand the molecular mechanisms that underly the neuroprotective effect of WYP on dopaminergic neurons in Parkinson's disease (PD). PD mouse model was induced by the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP). Gait and hanging tests were used to assess motor behavioral function. Immunofluorescence assay was used to determine TH-positive neurons in substantia nigra (SN). Apoptosis, dopamine and neurotrophic factors as well as expression of PI3K/Akt pathway were detected by TUNEL staining, ELISA and western blotting, respectively. First, it was observed that WYP intervention improved abnormal motor function in MPTP-induced PD model, alleviated the loss of TH⁺ neurons in SN, and increased dopamine content in brain, revealing a potential protective effect. Second, network pharmacology was used to analyze the possible targets and pathways of WYP action in the treatment of PD. A total of 126 active components related to PD were screened in WYP, and the related core targets included ALB, GAPDH, Akt1, TP53, IL6 and TNF. Particularly, the effect of WYP on PD may be medicate through PI3K/Akt signaling pathway and apoptotic regulation. The WYP treated PD mice had higher expression of p-PI3K, p-Akt and Bcl-2 but lower expression of Bax and cleaved caspase-3 than the non-WYP treated PD mice. Secretion of brain-derived neurotrophic factor (BDNF) and cerebral dopamine neurotrophic factor (CDNF) were also increased in the treated mice. WYP may inhibit apoptosis and increase the secretion of neurotrophic factor via activating PI3K/ Akt signaling pathway, thus protecting the loss of dopamine neurons in MPTP-induced PD mice.

The potential effects and mechanisms of hispidulin in the treatment of diabetic retinopathy based on network pharmacology

Background

Diabetic retinopathy (DR), one of the most common and severe microvascular complication of diabetes mellitus (DM), is mainly caused by diabetic metabolic disorder. So far, there is no effective treatment for DR. Eriocauli Flos, a traditional Chinese herb, has been used in treating the ophthalmic diseases including DR. However, the active ingredients and molecular mechanisms of Eriocauli Flos to treat diabetic retinopathy remain elusive.

Methods

Here, the systems pharmacology model was developed via constructing network approach. 8 active components which were screened by oral bioavailability (OB ≥ 30%) and drug-likeness (DL ≥ 0.18) and 154 targets were selected from Eriocauli Flos through TCMSP database. Another 3593 targets related to DR were obtained from Genecards, OMIM, TTD, and Drugbank databases. The 103 intersecting targets of DR and Eriocauli Flos were obtained by Draw Venn Diagram. In addition, protein-protein interaction network was established from STRING database and the compound-target network was constructed by Cytoscape which screened top 12 core targets with cytoNCA module. Then the overlapping targets were analyzed by GO and KEGG enrichment. Moreover, two core targets were selected to perform molecular docking simulation. Subsequently, CCK8 assay, RT-PCR and Western blotting were applied to further reveal the mechanism of new candidate active component from Eriocauli Flos in high glucose-induced HRECs.

Results

The results showed that the overlapping targets by GO analysis were enriched in cellular response to chemical stress, response to oxidative stress, response to reactive oxygen species, reactive oxygen species metabolic process and so on. Besides, the overlapping targets principally regulated pathways such as AGE-RAGE signaling pathway in diabetic complications, lipid atherosclerosis, fluid shear stress and atherosclerosis, and PI3K-Akt signaling pathway. Molecular docking exhibited that VEGFA and TNF-α, had good bindings to the great majority of compounds, especially the compound hispidulin. In vitro, hispidulin ameliorated high-glucose induced proliferation by down-regulating the expression of p-ERK, p-Akt, and VEGFA; meanwhile inhibited the mRNA levels of TNF-α.

Conclusions

In this study, through network pharmacology analysis and experimental validation, we found that hispidulin maybe has a potential targeted therapy effect for DR by decreasing the expression of p-Akt, p-ERK, and VEGFA, which resulted in ameliorating the proliferation in HRECs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12906-022-03593-2.

Identification of Candidate Therapeutic Genes for More Precise Treatment of Esophageal Squamous Cell Carcinoma and Adenocarcinoma

The standard therapy administered to patients with advanced esophageal cancer remains uniform, despite its two main histological subtypes, namely esophageal squamous cell carcinoma (SCC) and esophageal adenocarcinoma (AC), are being increasingly considered to be different. The identification of potential drug target genes between SCC and AC is crucial for more effective treatment of these diseases, given the high toxicity of chemotherapy and resistance to administered medications. Herein we attempted to identify and rank differentially expressed genes (DEGs) in SCC vs. AC using ensemble feature selection methods. RNA-seq data from The Cancer Genome Atlas and the Fudan-Taizhou Institute of Health Sciences (China). Six feature filters algorithms were used to identify DEGs. We built robust predictive models for histological subtypes with the random forest (RF) classification algorithm. Pathway analysis also be performed to investigate the functional role of genes. 294 informative DEGs (87 of them are newly discovered) have been identified. The areas under receiver operator curve (AUC) were higher than 99.5% for all feature selection (FS) methods. Nine genes (i.e., ERBB3, ATP7B, ABCC3, GALNT14, CLDN18, GUCY2C, FGFR4, KCNQ5, and CACNA1B) may play a key role in the development of more directed anticancer therapy for SCC and AC patients. The first four of them are drug targets for chemotherapy and immunotherapy of esophageal cancer and involved in pharmacokinetics and pharmacodynamics pathways. Research identified novel DEGs in SCC and AC, and detected four potential drug targeted genes (ERBB3, ATP7B, ABCC3, and GALNT14) and five drug-related genes.

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

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

Network Pharmacology and Molecular Docking-Based Strategy to Investigate the Multitarget Mechanisms of Shenqi Yizhi Granule on Alzheimer's Disease

Background

Traditional Chinese herbal medicine draws more attention to explore an effective therapeutic strategy for Alzheimer's disease (AD). Shenqi Yizhi granule (SQYG), a Chinese herbal recipe, has been applied to ameliorate cognitive impairment in mild-to-moderate AD patients. However, the overall molecular mechanism of SQYG in treating AD has not been clarified.

Objective

This study aimed to investigate the molecular mechanism of SQYG on AD using an integration strategy of network pharmacology and molecular docking.

Methods

The active compounds of SQYG and common targets between SQYG and AD were screened from databases. The herb-compound network, compound-target network, and protein-protein interaction network were constructed. The enrichment analysis of common targets and molecular docking were performed.

Results

816 compounds and 307 common targets between SQYG and AD were screened. KEGG analysis revealed that common targets were mainly enriched in lipid metabolism, metal ion metabolism, IL-17 signaling pathway, GABA receptor signaling, and neuroactive ligand-receptor interaction. Molecular docking analysis showed high binding affinity between ginsenoside Rg1 and Aβ _1-42, tanshinone IIA and BACE1, baicalin, and AchE.

Conclusions

The therapeutic mechanisms of SQYG on AD were associated with regulating lipid metabolism, metal ion metabolism, IL-17 signaling pathway, and GABA receptor signaling. Ginsenoside Rg1, tanshinone IIA, baicalin, astragaloside IV, and folic acid may play an important role in AD treatment.

Clinical Evidence and Potential Mechanisms of Complementary Treatment of Ling Gui Zhu Gan Formula for the Management of Serum Lipids and Obesity

Objective. This study aims to evaluate the clinical effects of Ling Gui Zhu Gan formula (LGZG), a famous TCM formula, for the management of serum lipids and obesity and preliminarily elucidates the bioactive components and the potential mechanism. Methods. Cluster analysis was adopted to investigate the TCM herbs and their frequency of occurrence for treating hyperlipidemia and obesity in an academic experience database of Chinese famous TCM doctors (http://www.gjmlzy.com:83). Then, relevant randomized controlled trials (RCTs) about LGZG supplementation in improving lipid levels and obesity were retrieved and analyzed. Lastly, the integration of network pharmacology, as well as greedy algorithms, which are theoretically well founded for the set cover in computer science, was exploited to identify the bioactive components of LGZG and to reveal potential mechanisms for attenuation or reversal of hyperlipidemia and obesity. Results. Based on the cluster analysis of 104 cases in TCM academic experience database, four TCM herbs in LGZG showed high-use frequency for treating hyperlipidemia and obesity. Meta-analysis on 19 randomized controlled trials (RCTs) with 1716 participants indicated that LGZG supplementation significantly decreased the serum levels of total triglycerides, total cholesterol, low-density lipoprotein cholesterol, BMI, and body weight and increased high-density lipoprotein cholesterol, compared with clinical control groups. No serious adverse effect was detected in all studies. Twenty-one bioactive components of LGZG, mainly flavonoids (i.e., naringenin, kaempferol, and kumatakenin), saponins (i.e., hederagenin), and fatty acids (i.e., eicosenoic acid), had the potential benefits possibly by regulating multiple targets such as PTPN1, CYP19A1, and ESR2, as well as a few complex pathways including the TNF signaling pathway, PPAR signaling pathway, arachidonic acid metabolism, fat digestion, and absorption. Conclusion. The present study has proved the clinical value of LGZG as a complementary treatment for attenuation or reversal of hyperlipidemia and obesity. More high-quality clinical and experimental studies in the future are demanded to verify its effects and the precise mechanism of action.

Mechanism of Peitu Shengjin Formula Shenlingbaizhu Powder in Treating Bronchial Asthma and Allergic Colitis through Different Diseases with Simultaneous Treatment Based on Network Pharmacology and Molecular Docking

BACKGROUND

Shenlingbaizhu powder (SLBZP), one of the classic Earth-cultivating and gold-generating prescriptions of traditional Chinese medicine, is widely used to treat various diseases. However, the pharmacological mechanisms of SLBZP on bronchial asthma (BA) and allergic colitis (AC) remain to be elucidated.

METHODS

Network pharmacology and molecular docking technology were used to explore the potential mechanism of SLBZP in treating BA and AC with the simultaneous treatment of different diseases. The potential active compounds of SLBZP and their corresponding targets were obtained from BATMAN-TCM, ETCM, SymMap TCM@TAIWAN, and TCMSP databases. BA and AC disease targets were collected through DisGeNET, TTD, GeneCards, PharmGKB, OMIM, NCBI, The Human Phenotype Ontology, and DrugBank databases. Common targets for drugs and diseases were screened by using the bioinformatics and evolutionary genomics platform. The analyses and visualizations of Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment of common targets were carried out by R software. The key targets were screened by using the plug-in "cytoHubba" of Cytoscape software, and the "active compound-key target" network was constructed. Molecular docking analysis was performed using AutoDock software. The miRTarBase database was used to predict microRNAs (miRNAs) targeting key targets, and the key target-miRNA network was constructed.

RESULT

Through screening, 246 active compounds and 281 corresponding targets were obtained. Common targets were mainly enriched in 2933 biological processes and 182 signal pathways to play the role of treating BA and AC. There were 131 active compounds related to key targets. The results of molecular docking showed that the important active compounds in SLBZP had good binding ability with the key targets. The key target-miRNA network showed that 94 miRNAs were predicted.

CONCLUSION

SLBZP has played the role of treating different diseases with the same treatment on BA and AC through the characteristics of multicompound, multitarget, and multipathway of traditional Chinese medicine, which provides a theoretical basis for explaining the mechanism and clinical application of SLBZP treating different diseases with the same treatment in BA and AC.

Network Pharmacology and Absolute Bacterial Quantification-Combined Approach to Explore the Mechanism of Tianqi Pingchan Granule Against 6-OHDA-Induced Parkinson’s Disease in Rats

Parkinson’s disease (PD) is the second most common neurodegenerative disease. Tianqi Pingchan Granule (TPG) is a clinically effective formula of traditional Chinese medicine to treat PD. However, the therapeutic effect and underlying mechanisms of TPG in PD remain unclear. Based on network pharmacology, the corresponding targets of TPG were identified using the Traditional Chinese Medicine Database and Analysis Platform Database. Differentially expressed genes in PD were obtained from the Therapeutic Target Database, Online Mendelian Inheritance in Man, GeneCards, and DrugBank databases. The protein-protein interaction (PPI) networks of intersected targets were constructed using the STRING database and visualized using Cytoscape. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed, and the pathways directly related to the pathogenesis of PD were integrated manually. Furthermore, in vivo studies were carried out based on network pharmacology. The gut microbiota, peripheral inflammatory cytokines, and glia-mediated neuroinflammation in substantia nigra were evaluated. A total of 99 target genes were intersected between targets of TPG and deferentially expressed genes in PD. The PPI network analysis indicated the proinflammatory cytokine as essential targets. GO and KEGG analyses indicated that inflammatory response and its related signaling pathways were closely associated with TPG-mediated PD treatment. In vivo studies revealed that class Negativicutes and order Selenomonadales decreased, whereas class Mollicutes, order Enterobacteriales, and Mycoplasmatales increased in fecal samples of PD rats via 16S rRNA sequence analysis. Furthermore, the function prediction methods purposely revealed that TPG therapy may be involved in flavonoid biosynthesis, which have anti-inflammatory properties. In addition, in vivo studies revealed that TPG exposure was found to not only attenuate the production of peripheral inflammatory cytokines but also inhibit the activation of microglia and astrocytes in substantia nigra of PD rats. Through network pharmacology and in vivo experiment-combined approach, the mechanisms of TPG in the treatment of PD were revealed, and the role of TPG in the regulation of gut microbiota and inflammatory response was confirmed.

Rules of Chinese Herbal Intervention of Radiation Pneumonia Based on Network Pharmacology and Data Mining

Objective

To explore the mechanism and principles of traditional Chinese medicine (TCM) in the management of radiation pneumonia.

Methods

The targets of radiation pneumonia were obtained by screening the GeneCards, OMIM, TTD, DrugBank, and HERB databases, analyzing ADME parameters. In addition, compounds and Chinese herbs that can act on the targets were screened from the TCMSP database. The core target compounds for TCM were used to construct the target-compound, compound-traditional Chinese medicine, and target-compound-traditional Chinese medicine networks. These networks were further used to select the core targets, compounds, and TCM. The binding strength between the core targets and compounds was determined using AutoDock Vina. The trajectory for the molecular dynamics simulation was completed by Desmond version 2020.

Results

A total of 55 active targets in radiation pneumonia were identified. Subsequently, 137 candidate compounds and 469 Chinese herbs were matched. Frequency statistics showed that the Chinese herbs that could interfere with radiation pneumonia were mainly bitter, spicy, and sweet, with both cold and warm properties. Moreover, they mainly belonged to liver and lung channels. The core targets included TNF, IL-6, TGF-β1, and TP53. The most important components were quercetin, resveratrol, and (-)-epigallocatechin-3-gallate. Moreover, the most significant traditional Chinese herbs were Perilla pueraria, ephedra, Lonicerae japonicae, and sea buckthorn. Furthermore, analysis of 222 sets of receptor-ligand docking results suggested that the compounds had good docking activity to their core targets. By combining the docking binding energy, we determined that the chemical compounds had strong binding energy to the targets.

Conclusion

Using network pharmacology, we explored the potential mechanism of TCM in the treatment of radiation pneumonia. The general rules for application of TCM in the treatment of radiation pneumonia were summarized. This study provides baseline information for future research on the development of TCM for the management of radiation pneumonia.

Mechanism of Fructus Mume Pills Underlying Their Protective Effects in Rats with Acetic Acid-Inducedulcerative Colitis via the Regulation of Inflammatory Cytokines and the VEGF-PI3K/Akt-eNOS Signaling Pathway

Background

Fructus mume pills (FMPs) have been clinically proven to be effective for treating ulcerative colitis (UC). However, the therapeutic and protective mechanisms have not been fully studied.

Aim

We aimed to explore the mechanism of FMPs in an acetic acid (AA)-induced ulcerative colitis rat model.

Methods

The targets, GO terms, and KEGG pathways for the FMPs and UC were screened and constructed using network pharmacology. A possible mechanism was verified in a 4% AA-induced colitis rat model. Colitis activity and state were evaluated using the disease activity index, and colon ulceration and intestinal mucosal damage were determined by histopathological observation through HE, AB-PAS, and Masson pathological staining. The concentrations of TNF-α, IL-6, IL-8, IL-10, MPO, MMP9, CXCR1, eNOS, and VEGF were measured to evaluate vascular permeability effects.

Results

The network pharmacology results showed 108 active compounds, and 139 FMP-related targets were identified. Twenty-nine targets were identified for FMPs against UC, which included MMP9, MMP3, ESR1, PTGS1, PPARA, MPO, and NOS2. A total of 1,536 GO terms and 41 pathways were associated with FMP treatment of UC. The pharmacological evaluation showed that FMPs attenuated inflammation in AA-induced colitis by reducing the serum concentrations of TNF-α, IL-6, IL-8, and IL-10 and the colonic concentrations of MPO, MMP9, and CXCR1. FMPs ameliorated hyperpermeability by reducing the colonic VEGF and eNOS concentrations. FMPs also significantly decreased the VEGFA, VEGFR2, Src, and eNOS protein expressions in colon tissue through the VEGF-PI3K/Akt-eNOS signaling pathway.

Conclusion

These results suggest that FMPs control UC inflammation by regulating inflammatory cytokine concentrations. FMPs alleviate AA-induced UC by regulating microvascular permeability through the VEGF-PI3K/Akt-eNOS signaling pathway.

Plasma proteome analyses in individuals of European and African ancestry identify cis-pQTLs and models for proteome-wide association studies

Improved understanding of genetic regulation of the proteome can facilitate identification of the causal mechanisms for complex traits. We analyzed data on 4,657 plasma proteins from 7,213 European American (EA) and 1,871 African American (AA) individuals from the Atherosclerosis Risk in Communities study, and further replicated findings on 467 AA individuals from the African American Study of Kidney Disease and Hypertension study. Here, we identified 2,004 proteins in EA and 1,618 in AA, with most overlapping, which showed associations with common variants in cis-regions. Availability of AA samples led to smaller credible sets and notable number of population-specific cis-protein quantitative trait loci. Elastic Net produced powerful models for protein prediction in both populations. An application of proteome-wide association studies to serum urate and gout implicated several proteins, including IL1RN, revealing the promise of the drug anakinra to treat acute gout flares. Our study demonstrates the value of large and diverse ancestry study to investigate the genetic mechanisms of molecular phenotypes and their relationship with complex traits.

Feasibility analysis and mechanism exploration of Rhei Radix et Rhizome-Schisandrae Sphenantherae Fructus (RS) against COVID-19

Introduction. As a novel global epidemic, corona virus disease 2019 (COVID-19) caused by SARS-CoV-2 brought great suffering and disaster to mankind. Recently, although significant progress has been made in vaccines against SARS-CoV-2, there are still no drugs for treating COVID-19. It is well known that traditional Chinese medicine (TCM) has achieved excellent efficacy in the treatment of COVID-19 in China. As a treasure-house of natural drugs, Chinese herbs offer a promising prospect for discovering anti-COVID-19 drugs.Hypothesis/Gap Statement. We proposed that Rhei Radix et Rhizome-Schisandrae Sphenantherae Fructus (RS) may have potential value in the treatment of COVID-19 patients by regulating immune response, protecting the cardiovascular system, inhibiting the production of inflammatory factors, and blocking virus invasion and replication processes.Aim. We aimed to explore the feasibility and molecular mechanisms of RS against COVID-19, to provide a reference for basic research and clinical applications.Methodology. Through literature mining, it is found that a Chinese herbal pair, RS, has potential anti-COVID-19 activity. In this study, we analysed the feasibility of RS against COVID-19 by high-throughput molecular docking and molecular dynamics simulations. Furthermore, we predicted the molecular mechanisms of RS against COVID-19 based on network pharmacology.Results. We proved the feasibility of RS anti-COVID-19 by literature mining, virtual docking and molecular dynamics simulations, and found that angiotensin converting enzyme 2 (ACE2) and 3C-like protease (3 CL pro) were also two critical targets for RS against COVID-19. In addition, we predicted the molecular mechanisms of RS in the treatment of COVID-19, and identified 29 main ingredients, 21 potential targets and 16 signalling pathways. Rhein, eupatin, (-)-catechin, aloe-emodin may be important active ingredients in RS. ALB, ESR1, EGFR, HMOX1, CTSL, and RHOA may be important targets against COVID-19. Platelet activation, renin secretion, ras signalling pathway, chemokine signalling pathway, and human cytomegalovirus infection may be important signalling pathways against COVID-19.Conclusion. RS plays a key role in the treatment of COVID-19, which may be closely related to immune regulation, cardiovascular protection, anti-inflammation, virus invasion and replication processes.

Icariin: A Potential Molecule for Treatment of Knee Osteoarthritis

Background: Knee osteoarthritis (KOA) is a degenerative disease that develops over time. Icariin (ICA) has a positive effect on KOA, although the mechanism is unknown. To investigate drug-disease connections and processes, network pharmacology is commonly used. The molecular mechanisms of ICA for the treatment of KOA were investigated using network pharmacology, molecular docking and literature research approaches in this study.

Methods: We gathered KOA-related genes using the DisGeNET database, the OMIM database, and GEO microarray data. TCMSP database, Pubchem database, TTD database, SwissTargetPrediction database, and Pharmmapper database were used to gather ICA-related data. Following that, a protein-protein interaction (PPI) network was created. Using the Metascape database, we performed GO and KEGG enrichment analyses. After that, we built a targets-pathways network. Furthermore, molecular docking confirms the prediction. Finally, we looked back over the last 5 years of literature on icariin for knee osteoarthritis to see if the findings of this study were accurate.

Results: core targets relevant to KOA treatment include TNF, IGF1, MMP9, PTGS2, ESR1, MMP2 and so on. The main biological process involved regulation of inflammatory response, collagen catabolic process, extracellular matrix disassembly and so on. The most likely pathways involved were the IL-17 signaling pathway, TNF signaling pathway, Estrogen signaling pathway.

Conclusion: ICA may alleviate KOA by inhibiting inflammation, cartilage breakdown and extracellular matrix degradation. Our study reveals the molecular mechanism of ICA for the treatment of KOA, demonstrating its potential value for further research and as a new drug.

Study on the Potential Molecular Mechanism of Xihuang Pill in the Treatment of Pancreatic Cancer Based on Network Pharmacology and Bioinformatics

Objective

We aimed to analyze the possible molecular mechanism of Xihuang pill (XHP) in the treatment of pancreatic cancer based on methods of network pharmacology, molecular docking, and bioinformatics.

Methods

The main active components and targets were obtained through the TCMSP database, the BATMAN-TCM database, and the Chemistry database. The active ingredients were screened according to the “Absorption, Distribution, Metabolism, Excretion” (ADME) principle and supplemented with literature. We searched GeneCards, OMIM, TTD, and DrugBank databases for pancreatic cancer targets. The targets of disease and ingredients were intersected to obtain candidate key targets. Then, we constructed a protein-protein interaction (PPI) network for protein interaction analysis and a composition-key target map to obtain essential effective ingredients. Metascape was used to perform functional enrichment analysis to screen critical targets and pathways. The expression and prognosis of key targets were examined and analyzed, and molecular docking was carried out.

Results

A total of 52 active ingredients of XHP, 121 candidate targets, and 52 intersecting targets were obtained. The core active ingredients of XHP for the treatment of pancreatic cancer were quercetin, 17-β-estradiol, ursolic acid, and daidzein. The core targets were EGFR, ESR1, MAPK1, MAPK8, MAPK14, TP53, and JUN, which were highly expressed genes of pancreatic cancer. Among them, EGFR and MAPK1 were significantly correlated with the survival of pancreatic cancer patients. The key pathway was the EGFR/MAPK pathway. The molecular docking results indicated that four active compositions had good binding ability to key targets.

Conclusion

The molecular mechanism of XHP for the treatment of pancreatic cancer involved multiple components, multiple targets, and multiple pathways. This research theoretically elucidated the ameliorative effect of XHP against pancreatic cancer and might provide new ideas for further research on the treatment of pancreatic cancer.

Comprehensive network medicine-based drug repositioning via integration of therapeutic efficacy and side effects

Despite advances in modern medicine that led to improvements in cardiovascular outcomes, cardiovascular disease (CVD) remains the leading cause of mortality and morbidity globally. Thus, there is an urgent need for new approaches to improve CVD drug treatments. As the development time and cost of drug discovery to clinical application are excessive, alternate strategies for drug development are warranted. Among these are included computational approaches based on omics data for drug repositioning, which have attracted increasing attention. In this work, we developed an adjusted similarity measure implemented by the algorithm SAveRUNNER to reposition drugs for cardiovascular diseases while, at the same time, considering the side effects of drug candidates. We analyzed nine cardiovascular disorders and two side effects. We formulated both disease disorders and side effects as network modules in the human interactome, and considered those drug candidates that are proximal to disease modules but far from side-effects modules as ideal. Our method provides a list of drug candidates for cardiovascular diseases that are unlikely to produce common, adverse side-effects. This approach incorporating side effects is applicable to other diseases, as well.

Network Pharmacology and Comparative Transcriptome Reveals Biotargets and Mechanisms of Curcumol Treating Lung Adenocarcinoma Patients With COVID-19

The coronavirus disease 2019 (COVID-19) pandemic has led to 4,255,892 deaths worldwide. Although COVID-19 vaccines are available, mutant forms of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have reduced the effectiveness of vaccines. Patients with cancer are more vulnerable to COVID-19 than patients without cancer. Identification of new drugs to treat COVID-19 could reduce mortality rate, and traditional Chinese Medicine(TCM) has shown potential in COVID-19 treatment. In this study, we focused on lung adenocarcinoma (LUAD) patients with COVID-19. We aimed to investigate the use of curcumol, a TCM, to treat LUAD patients with COVID-19, using network pharmacology and systematic bioinformatics analysis. The results showed that LUAD and patients with COVID-19 share a cluster of common deregulated targets. The network pharmacology analysis identified seven core targets (namely, AURKA, CDK1, CCNB1, CCNB2, CCNE1, CCNE2, and TTK) of curcumol in patients with COVID-19 and LUAD. Clinicopathological analysis of these targets demonstrated that the expression of these targets is associated with poor patient survival rates. The bioinformatics analysis further highlighted the involvement of this target cluster in DNA damage response, chromosome stability, and pathogenesis of LUAD. More importantly, these targets influence cell-signaling associated with the Warburg effect, which supports SARS-CoV-2 replication and inflammatory response. Comparative transcriptomic analysis on in vitro LUAD cell further validated the effect of curcumol for treating LUAD through the control of cell cycle and DNA damage response. This study supports the earlier findings that curcumol is a potential treatment for patients with LUAD and COVID-19.

PregTox: A Resource of Knowledge about Drug Fetal Toxicity

Background

It is of vital importance to determine the safety of drugs. Pregnant women, as a special group, need to evaluate the effects of drugs on pregnant women as well as the fetus. The use of drugs during pregnancy may be subject to fetal toxicity, thus affecting the development of the fetus or even leading to stillbirth. The U.S. Food and Drug Administration (FDA) issued a toxicity rating for drugs used during pregnancy in 1979. These toxicity ratings are denoted by the letters A, B, C, D, and X. However, the query of drug pregnancy category has yet to be well established as electronic service.

Results

Here, we presented PregTox, a publicly accessible resource for pregnancy category information of 1114 drugs. The PregTox database also included chemical structures, important physico-chemical properties, protein targets, and relevant signaling pathways. An advantage of the database is multiple search options which allow systematic analyses. In a case study, we demonstrated that a set of chemical descriptors could effectively discriminate high-risk drugs from others (area under ROC curve reached 0.81).

Conclusions

PregTox can serve as a unique drug safety data source for drug development and pharmacological research.

Text-Mining Approach to Identify Hub Genes of Cancer Metastasis and Potential Drug Repurposing to Target Them

Metastasis accounts for the majority of cancer-related deaths. Despite decades of research, the prevention and suppression of metastasis remain an elusive goal, and to date, only a few metastasis-related genes have been targeted therapeutically. Thus, there is a strong need to find potential genes involved in key driver traits of metastasis and their available drugs. In this study, we identified genes associated with metastasis and repurposable drugs that potentially target them. First, we use text mining of PubMed citations to identify candidate genes associated with metastatic processes, such as invadopodia, motility, movement, metastasis, invasion, wound healing, EMT (epithelial to mesenchymal transition), and podosome. Next, we annotated the top genes involved in each process as a driver, tumor suppressor, or oncogene. Then, a total of 185 unique cancer genes involved in metastasis-related processes were used for hub gene analysis using bioinformatics tools. Notably, a total of 77 hub genes were identified. Further, we used virtual screening data of druggable candidate hub genes involved in metastasis and identified potential drugs that can be repurposed as anti-metastatic drugs. Remarkably, we found a total of 50 approved drugs that have the potential to be repurposed against 19 hub genes involved in metastasis-related processes. These 50 drugs were also found to be validated in different cancer cell lines, such as dasatinib, captopril, leflunomide, and dextromethorphan targeting SRC, MMP2, PTK2B, and RAC1 hub genes, respectively. These repurposed drugs potentially target metastasis, provide pharmacodynamic insight, and offer a window of opportunity for the development of much-needed antimetastatic drugs.

Molecular Mechanism Underlying Effects of Wumeiwan on Steroid-Dependent Asthma: A Network Pharmacology, Molecular Docking, and Experimental Verification Study

Background

Steroid-dependent asthma (SDA) is characterized by oral corticosteroid (OCS) resistance and dependence. Wumeiwan (WMW) showed potentials in reducing the dose of OCS of SDA patients based on our previous studies.

Methods

Network pharmacology was conducted to explore the molecular mechanism of WMW against SDA with the databases of TCMSP, STRING, etcetera. GO annotation and KEGG functional enrichment analysis were conducted by metascape database. Pymol performed the molecular docking. In the experiment, the OVA-induced plus descending dexamethasone intervention chronic asthmatic rat model was conducted. Lung pathological changes were analyzed by H&E, Masson, and IHC staining. Relative expressions of the gene were performed by real-time PCR.

Results

A total of 102 bioactive ingredients in WMW were identified, as well as 191 common targets were found from 241 predicted targets in WMW and 3539 SDA-related targets. The top five bioactive ingredients were identified as pivotal ingredients, which included quercetin, candletoxin A, palmidin A, kaempferol, and beta-sitosterol. Besides, 35 HUB genes were obtained from the PPI network, namely, TP53, AKT1, MAPK1, JUN, HSP90AA1, TNF, RELA, IL6, CXCL8, EGFR, etcetera. GO biological process analysis indicated that HUB genes were related to bacteria, transferase, cell differentiation, and steroid. KEGG pathway enrichment analysis indicated that the potential mechanism might be associated with IL-17 and MAPK signaling pathways. Molecular docking results supported these findings. H&E and Masson staining proved that WMW could reduce airway inflammation and remodeling of model rats, which might be related to the downward expression of IL-8 proved by IHC staining and real-time PCR.

Conclusion

WMW could be a complementary and alternative therapy for SDA by reducing airway inflammation.

Proprietary Medicines Containing Bupleurum chinense DC. (Chaihu) for Depression: Network Meta-Analysis and Network Pharmacology Prediction

Background and Aims: The rapid development of society has resulted in great competitive pressures, leading to the increase in suicide rates as well as incidence and recurrence of depression in recent years. Proprietary Chinese medicines containing Bupleurum chinense DC. (Chaihu) are widely used in clinical practice. This study aimed at evaluating the efficacy and safety of oral proprietary Chinese medicines containing Chaihu for treating depression by network meta-analysis (NMA) and exploring the potential pharmacological mechanisms of the optimal drugs obtained based on NMA.

Methods: This study searched for clinical randomized controlled trial studies (RCTs) about Chaihu-containing products alone or in combination with selective serotonin reuptake inhibitors (SSRI), serotonin-norepinephrine reuptake inhibitors (SNRI), and cyclic antidepressants (CAS) for depression in eight databases. The search deadline is from data inception to April 2021. For efficacy assessment, the clinical response rate, the Hamilton Depression Scale-17 (HAMD-17), and adverse reactions were calculated. The methodological quality of the included studies was assessed for risk of bias following the Cochrane Handbook for Systematic Reviews of Interventions, and the data were subjected to NMA via the Stata version 16.0 software. Subsequently, the optimal drug obtained from the NMA results, Danzhi Xiaoyao pill (DZXY), was used to conduct network pharmacology analysis. We searched databases to acquire bioactive and potential targets of DZXY and depression-related targets. The protein-protein interaction (PPI) network, component-target network, the Gene Ontology (GO), and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed by the STRING database, Cytoscape 3.9.0 software, and R version 4.1.2, respectively.

Results: Thirty-seven RCTs, with a total of 3,263 patients, involving seven oral proprietary Chinese medicines containing Chaihu, were finally included. The results of the NMA demonstrated that the top four interventions with the best efficiency were Jiawei Xiaoyao + SSRI, DZXY + SNRI, Xiaoyao pill + SSRI, and Jieyu pill + SNRI; the top four interventions reducing HAMD score were DZXY + SNRI, Jiawei Xiaoyao, Jieyu pill, and Puyu pill + SNRI; the top four interventions with the least adverse effects were Jieyu pill, Anle pill + SSRI, DZXY + SNRI, and Puyu pill + SNRI. In the aspects above, DZXY + SNRI performed better than other treatments. After network meta-analysis, we conducted a network pharmacology-based strategy on the optimal drugs, DZXY, to provide the pharmacological basis for a conclusion. A total of 147 active compounds and 248 targets in DZXY were identified, of which 175 overlapping targets related to depression. Bioinformatics analysis revealed that MAPK3, JUN, MAPK14, MYC, MAPK1, etc. could become potential therapeutic targets. The MAPK signaling pathway might play an essential role in DZXY against depression.

Conclusion: This is the very first systematic review and network meta-analysis evaluating different oral proprietary Chinese medicines containing Chaihu in depressive disorder. This study suggested that the combination of proprietary Chinese medicines containing Chaihu with antidepressants was generally better than antidepressant treatment. The incidence of adverse reactions with antidepressants alone was higher than that with proprietary Chinese medicines containing Chaihu alone or in combination with antidepressants. DZXY + SNRI showed significantly better results in efficacy, HAMD scores, and safety. The antidepressant effect of DZXY may be related to its regulation of neuroinflammation and apoptosis.

Integrated Network Pharmacology and Metabolomics Analysis to Reveal the Potential Mechanism of Siwu Paste on Aplastic Anemia Induced by Chemotherapy Drugs

Purpose

This study aimed to reveal the multicomponent synergy mechanisms of SWP based on network pharmacology and metabolomics for exploring the relationships of active ingredients, biological targets, and crucial metabolic pathways.

Materials

Network pharmacology, including TRRUST, GO, and KEGG, enrichment was used to discover the active ingredients and potential regulation mechanisms of SWP. LC-MS and multivariate data analysis method were further applied to analyze serum metabolomics profiling for discovering the potential metabolic mechanisms of SWP on AA induced by Cyclophosphamide (CTX) and 1-Acetyl-2-phenylhydrazine (APH).

Results

A total of 27 important bioactive ingredients meeting the ADME (absorption, distribution, metabolism, and excretion) screening criteria from SWP were selected. Interaction networks were constructed and validated based on the 10 associated ingredients with the relevant targets. A total of 125 biomarkers were found by Metabolomics approach, which associated with the development of AA, mainly involved in amino acid metabolism and lipid metabolism. While SWP can reverse the above 12 metabolites changed by AA. Network analysis revealed the synergistic effects of SWP through the 43 crucial pathways, including Sphingolipid signaling pathway, Sphingolipid metabolism, Arginine and proline metabolism, VEGF signaling pathway, Estrogen signaling pathway.

Conclusion

The study suggested that SWP is a useful alternative for the treatment of AA induced by CTX + APH. Its potential mechanisms are to improve hematopoietic microenvironment and promote bone marrow hematopoiesis therapies.

Elucidating the Synergistic Effect of Multiple Chinese Herbal Prescriptions in the Treatment of Post-stroke Neurological Damage

Background: Traditional Chinese medicine (TCM) has been widely used in the treatment of human diseases. However, the synergistic effects of multiple TCM prescriptions in the treatment of stroke have not been thoroughly studied.

Objective of the study: This study aimed to reveal the mechanisms underlying the synergistic effects of these TCM prescriptions in stroke treatment and identify the active compounds.

Methods: Herbs and compounds in the Di-Tan Decoction (DTD), Xue-Fu Zhu-Yu Decoction (XFZYD), and Xiao-Xu-Ming Decoction (XXMD) were acquired from the TCMSP database. SEA, HitPick, and TargetNet web servers were used for target prediction. The compound-target (C-T) networks of three prescriptions were constructed and then filtered using the collaborative filtering algorithm. We combined KEGG enrichment analysis, molecular docking, and network analysis approaches to identify active compounds, followed by verification of these compounds with an oxygen-glucose deprivation and reoxygenation (OGD/R) model.

Results: The filtered DTD network contained 39 compounds and 534 targets, the filtered XFZYD network contained 40 compounds and 508 targets, and the filtered XXMD network contained 55 compounds and 599 targets. The filtered C-T networks retained approximately 80% of the biological functions of the original networks. Based on the enriched pathways, molecular docking, and network analysis results, we constructed a complex network containing 3 prescriptions, 14 botanical drugs, 26 compounds, 13 targets, and 5 pathways. By calculating the synergy score, we identified the top 5 candidate compounds. The experimental results showed that quercetin, baicalin, and ginsenoside Rg1 independently and synergistically increased cell viability.

Conclusion: By integrating pharmacological and chemoinformatic approaches, our study provides a new method for identifying the effective synergistic compounds of TCM prescriptions. The filtered compounds and their synergistic effects on stroke require further research.

A Comparison of Network-Based Methods for Drug Repurposing along with an Application to Human Complex Diseases

Drug repurposing strategy, proposing a therapeutic switching of already approved drugs with known medical indications to new therapeutic purposes, has been considered as an efficient approach to unveil novel drug candidates with new pharmacological activities, significantly reducing the cost and shortening the time of de novo drug discovery. Meaningful computational approaches for drug repurposing exploit the principles of the emerging field of Network Medicine, according to which human diseases can be interpreted as local perturbations of the human interactome network, where the molecular determinants of each disease (disease genes) are not randomly scattered, but co-localized in highly interconnected subnetworks (disease modules), whose perturbation is linked to the pathophenotype manifestation. By interpreting drug effects as local perturbations of the interactome, for a drug to be on-target effective against a specific disease or to cause off-target adverse effects, its targets should be in the nearby of disease-associated genes. Here, we used the network-based proximity measure to compute the distance between the drug module and the disease module in the human interactome by exploiting five different metrics (minimum, maximum, mean, median, mode), with the aim to compare different frameworks for highlighting putative repurposable drugs to treat complex human diseases, including malignant breast and prostate neoplasms, schizophrenia, and liver cirrhosis. Whilst the standard metric (that is the minimum) for the network-based proximity remained a valid tool for efficiently screening off-label drugs, we observed that the other implemented metrics specifically predicted further interesting drug candidates worthy of investigation for yielding a potentially significant clinical benefit.

Exploring Active Compounds and Mechanisms of Angong Niuhuang Wan on Ischemic Stroke Based on Network Pharmacology and Molecular Docking

Methods

The chemical ingredients of ANW were retrieved from TCMSP, TCMID, and literature. We predicted the potential targets of active ingredients by PubChem, Swiss Target Prediction, and STITCH databases. The targets related to ischemic stroke were retrieved using GeneCards, DisGeNET, DrugBank, TTD, and GEO databases. Subsequently, Venn diagrams were used to identify common targets of active ingredients and ischemic stroke. Protein-protein interaction (PPI) network was structured with STRING platform and Cytoscape 3.8.2. Gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of key targets were performed in the Metascape database. Finally, molecular docking was conducted by AutoDock Tools and PyMOL software.

Results

A total of 2391 targets were identified for 230 active ingredients of ANW, and 1386 of them overlapped with ischemic stroke targets. The key active ingredients were mainly quercetin, β-estradiol, berberine, wogonin, and β-sitosterol, and the key targets were also identified, including IL-6, AKT1, MAPK3, PIK3CA, and TNF. The biological process (BP) results indicated that ANW may have therapeutic effects through response oxidative stress, inflammatory response, cellular response to lipid, and response to nutrient levels. Furthermore, the ingredients of ANW were predicted to have therapeutic effects on ischemic stroke via the HIF-1 signaling pathway, FoxO signaling pathway, chemokine signaling pathway, fluid shear stress and atherosclerosis, and neurotrophin signaling pathway. The molecular docking results all showed that the core ingredients were strong binding activity with the core targets.

Conclusion

In conclusion, the bioinformatics and pharmacological results reveal that counteracting oxidative stress, suppressing inflammation, inhibiting the development of AS, and even protecting neurological function are critical pathways for ANW in the treatment of ischemic stroke. These results may help to elucidate the mechanism of ANW on ischemic stroke for experimental studies and clinical applications.

In Vivo Dopamine Neuron Imaging-Based Small Molecule Screen Identifies Novel Neuroprotective Compounds and Targets

Parkinson’s disease (PD) is the second most common neurodegenerative disorder with prominent dopamine (DA) neuron degeneration. PD affects millions of people worldwide, but currently available therapies are limited to temporary relief of symptoms. As an effort to discover disease-modifying therapeutics, we have conducted a screen of 1,403 bioactive small molecule compounds using an in vivo whole organism screening assay in transgenic larval zebrafish. The transgenic model expresses the bacterial enzyme nitroreductase (NTR) driven by the tyrosine hydroxylase (th) promotor. NTR converts the commonly used antibiotic pro-drug metronidazole (MTZ) to the toxic nitroso radical form to induce DA neuronal loss. 57 compounds were identified with a brain health score (BHS) that was significantly improved compared to the MTZ treatment alone after FDR adjustment (padj<0.05). Independently, we curated the high throughput screening (HTS) data by annotating each compound with pharmaceutical classification, known mechanism of action, indication, IC50, and target. Using the Reactome database, we performed pathway analysis, which uncovered previously unknown pathways in addition to validating previously known pathways associated with PD. Non-topology-based pathway analysis of the screening data further identified apoptosis, estrogen hormone, dipeptidyl-peptidase 4, and opioid receptor Mu1 to be potentially significant pathways and targets involved in neuroprotection. A total of 12 compounds were examined with a secondary assay that imaged DA neurons before and after compound treatment. The z’-factor of this secondary assay was determined to be 0.58, suggesting it is an excellent assay for screening. Etodolac, nepafenac, aloperine, protionamide, and olmesartan showed significant neuroprotection and was also validated by blinded manual DA neuronal counting. To determine whether these compounds are broadly relevant for neuroprotection, we tested them on a conduritol-b-epoxide (CBE)-induced Gaucher disease (GD) model, in which the activity of glucocerebrosidase (GBA), a commonly known genetic risk factor for PD, was inhibited. Aloperine, olmesartan, and nepafenac showed significant protection of DA neurons in this assay. Together, this work, which combines high content whole organism in vivo imaging-based screen and bioinformatic pathway analysis of the screening dataset, delineates a previously uncharted approach for identifying hit-to-lead candidates and for implicating previously unknown pathways and targets involved in DA neuron protection.

Mechanism of Huoluo Xiaoling Dan in the Treatment of Psoriasis Based on Network Pharmacology and Molecular Docking

Objective

To explore the mechanism of the action of Huoluo Xiaoling Dan (HLXLD) in the treatment of psoriasis based on network pharmacology and molecular docking.

Methods

The main active components and targets of HLXLD were collected from CMSP, and the targets related to psoriasis were collected from GeneCards, OMIM, TTD, DisGeNET, and DrugBank. Drug disease target genes were obtained by Venny tools, drug-component-target networks were constructed and analyzed, and pathway enrichment analysis was performed. AutoDockTools is used to connect the core components and the target, and PyMOL software is used to visualize the results.

Results

126 active components (such as quercetin, luteolin, tanshinone IIA, dihydrotanshinlactone, and beta-sitosterol) and 238 targets of HLXLD were screened out. 1,293 targets of psoriasis were obtained, and 123 drug-disease targets were identified. Key targets included AKT1, TNF, IL6, TP53, VEGFA, JUN, CASP3, IL1B, STAT3, PTGS2, HIF1A, EGF, MYC, EGFR, MMP9, and PPARG. Enrichment analysis showed that 735 GO analysis and 85 KEGG pathways were mainly involved in biological processes such as response to the drug, inflammatory response, gene expression, and cell proliferation and apoptosis, as well as signal pathways such as cancer, TNF, HIF-1, and T cell receptor. Molecular docking showed that there was strong binding activity between the active ingredient and the target protein.

Conclusions

HLXLD could treat psoriasis through multicomponents, multitargets, and multipathways, which provides a new theoretical basis for further basic research and clinical application.

Network pharmacology analysis reveals neuroprotection of Gynostemma pentaphyllum (Thunb.) Makino in Alzheimer' disease

Background

Alzheimer’s disease (AD) is one of the most common neurodegenerative disorders in the world, but still lack of effective drug treatment. Gynostemma Pentaphyllum (Thunb.) Makino (GpM), a Chinese medicinal herb, plays important roles in anti-inflammation, anti-oxidative stress and anti-tumor, which has been reported to ameliorate cognitive impairment of AD. However, the neuroprotective mechanism of GpM remains unclear. This study aims to investigate the targets and possible signaling pathways of GpM in the treatment of AD.

Methods

Active compounds of GpM and their putative target proteins were selected from Traditional Chinese Medicine Systems Pharmacology (TCMSP) Database and Analysis Platform. AD-associated targets were identified from GeneCards, the Online Mendelian Inheritance in Man (OMIM) database and the Therapeutic Target Database (TTD). The intersecting targets of GpM and AD were identified and Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were carried out to analyze the mechanism of them. Compound-target-pathway (CTP) network and protein–protein interaction (PPI) network were constructed and analyzed to elucidate the correlation between compounds, proteins and pathways. Molecular docking was performed to further demonstrate the possibility of GpM for AD.

Results

A total of 13 active compounds of GpM, 168 putative target proteins of compounds and 722 AD-associated targets were identified. Eighteen intersecting targets of GpM and AD were found and the epidermal growth factor receptor (EGFR), interleukin-1 beta (IL-1β), interleukin-6 (IL-6), nitric oxide synthase in endothelial (NOS3) and serum paraoxonase/arylesterase 1 (PON1) were selected as the primary targets of GpM in the treatment of AD. The neuroprotective effect of GPM was related to a variety of pathways, including amoebiasis, HIF-1 signaling pathway, cytokine-cytokine receptor interaction and so on.

Conclusions

Our findings elucidate the active compounds, targets and pathways of GpM involved in effects of anti-AD. The novel mechanism of GpM against AD provides more treatment options for AD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12906-022-03534-z.

Network pharmacology-based predictions of active components and pharmacological mechanisms of Artemisia annua L. for the treatment of the novel Corona virus disease 2019 (COVID-19)

BACKGROUND

Novel Corona Virus Disease 2019 (COVID-19) is closely associated with cytokines storms. The Chinese medicinal herb Artemisia annua L. (A. annua) has been traditionally used to control many inflammatory diseases, such as malaria and rheumatoid arthritis. We performed network analysis and employed molecular docking and network analysis to elucidate active components or targets and the underlying mechanisms of A. annua for the treatment of COVID-19.

METHODS

Active components of A. annua were identified through the TCMSP database according to their oral bioavailability (OB) and drug-likeness (DL). Moreover, target genes associated with COVID-19 were mined from GeneCards, OMIM, and TTD. A compound-target (C-T) network was constructed to predict the relationship of active components with the targets. A Compound-disease-target (C-D-T) network has been built to reveal the direct therapeutic target for COVID-19. Molecular docking, molecular dynamics simulation studies (MD), and MM-GBSA binding free energy calculations were used to the closest molecules and targets between A. annua and COVID-19.

RESULTS

In our network, GO, and KEGG analysis indicated that A. annua acted in response to COVID-19 by regulating inflammatory response, proliferation, differentiation, and apoptosis. The molecular docking results manifested excellent results to verify the binding capacity between the hub components and hub targets in COVID-19. MD and MM-GBSA data showed quercetin to be the more effective candidate against the virus by target MAPK1, and kaempferol to be the other more effective candidate against the virus by target TP53. We identified A. annua's potentially active compounds and targets associated with them that act against COVID-19.

CONCLUSIONS

These findings suggest that A. annua may prevent and inhibit the inflammatory processes related to COVID-19.

Nucleic Acid-Based COVID-19 Therapy Targeting Cytokine Storms: Strategies to Quell the Storm

Coronavirus disease 2019 (COVID-19) has shaken the world and triggered drastic changes in our lifestyle to control it. Despite the non-typical efforts, COVID-19 still thrives and plagues humanity worldwide. The unparalleled degree of infection has been met with an exceptional degree of research to counteract it. Many drugs and therapeutic technologies have been repurposed and discovered, but no groundbreaking antiviral agent has been introduced yet to eradicate COVID-19 and restore normalcy. As lethality is directly correlated with the severity of disease, hospitalized severe cases are of the greatest importance to reduce, especially the cytokine storm phenomenon. This severe inflammatory phenomenon characterized by elevated levels of inflammatory mediators can be targeted to relieve symptoms and save the infected patients. One of the promising therapeutic strategies to combat COVID-19 is nucleic acid-based therapeutic approaches, including microRNAs (miRNAs). This work is an up-to-date review aimed to comprehensively discuss the current nucleic acid-based therapeutics against COVID-19 and their mechanisms of action, taking into consideration the emerging SARS-CoV-2 variants of concern, as well as providing potential future directions. miRNAs can be used to run interference with the expression of viral proteins, while endogenous miRNAs can be targeted as well, offering a versatile platform to control SARS-CoV-2 infection. By targeting these miRNAs, the COVID-19-induced cytokine storm can be suppressed. Therefore, nucleic acid-based therapeutics (miRNAs included) have a latent ability to break the COVID-19 infection in general and quell the cytokine storm in particular.

Solasonine Induces Apoptosis and Inhibits Proliferation of Bladder Cancer Cells by Suppressing NRP1 Expression

Solasonine, a steroidal alkaloid extracted from Solanum nigrum L., has been found to exert inhibitory effect on cancers. However, the underlying anticancer mechanisms of solasonine, particularly in urinary bladder cancer (BC), remain unclear. In this study, we identified the potential targets and biological functions associated with solasonine activity using a bioinformatics approach. Ingenuity pathway analysis revealed that neuropilin-1 (NRP1) and other signaling pathways, such as PI3K/AKT and ERK/MAPK pathways, were potentially involved in the therapeutic effects of solasonine. The ability of solasonine in inducing apoptosis and inhibiting proliferation in BC cells was confirmed experimentally, and the inhibition of ERK/MAPK, P38/MAPK, and PI3K/AKT pathways was validated by Western blot. Mechanistically, solasonine suppressed the expression of NRP1 protein, but not that of mRNA. Further results of molecular docking and molecular dynamics simulation analysis indicated that solasonine could directly bind to the b1 domain of NRP1 protein with a reasonable and stable docking conformation. We previously found that targeting NRP1 is a potential antitumor strategy. Combined with these findings, it can be speculated that the binding of solasonine with NRP1 on the cell membrane could prevent the formation of NRP1/VEGFA/VEGFR2 and NRP1/EGFR complexes, resulting in the inhibition of downstream signaling, including ERK/MAPK, P38/MAPK, and PI3K/AKT pathways. Additionally, intracellular solasonine could inhibit the membrane localization of NRP1 and provoke its cytoplasmic retention, facilitating the degradation of NRP1 protein in the cytoplasm. The dual effects induced by the binding of solasonine to NRP1 extracellularly and intracellularly could account for the antiproliferative and proapoptotic effects of solasonine on BC.