scholarly journals Targeting comorbid diseases via network endopharmacology

2018 ◽  
Author(s):  
Juaquim Aguirre-Plans ◽  
Janet Piñero ◽  
Jörg Menche ◽  
Ferran Sanz ◽  
Laura I Furlong ◽  
...  
Keyword(s):  
Drug Targets ◽  
Natural Extension ◽  
Drug Repurposing ◽  
Enrichment Analysis ◽  
Biological Pathways ◽  
Pathway Enrichment Analysis ◽  
Disease Genes ◽  
Multiple Targets ◽  
Clear Cut ◽  
Traditional Drug

AbstractThe traditional drug discovery paradigm has shaped around the idea of “one target, one disease”. Recently, it has become clear that not only it is hard to achieve single target specificity but also it is often more desirable to tinker the complex cellular network by targeting multiple proteins, causing a paradigm shift towards polypharmacology (multiple targets, one disease). Given the lack of clear-cut boundaries across disease (endo)phenotypes and genetic heterogeneity across patients, a natural extension to the current polypharmacology paradigm is targeting common biological pathways involved in diseases, giving rise to “endopharmacology” (multiple targets, multiple diseases). In this study, leveraging powerful network medicine tools, we describe a recipe for first, identifying common pathways pertaining to diseases and then, prioritizing drugs that target these pathways towards endopharmacology. We present proximal pathway enrichment analysis (PxEA) that uses the topology information of the network of interactions between disease genes, pathway genes, drug targets and other proteins to rank drugs for their interactome-based proximity to pathways shared across multiple diseases, providing unprecedented drug repurposing opportunities. As a proof of principle, we focus on nine autoimmune disorders and using PxEA, we show that many drugs indicated for these conditions are not necessarily specific to the condition of interest, but rather target the common biological pathways across these diseases. Finally, we provide the high scoring drug repurposing candidates that can target common mechanisms involved in type 2 diabetes and Alzheimer’s disease, two phenotypes that have recently gained attention due to the increased comorbidity among patients.

scholarly journals Association between ALS and retroviruses: evidence from bioinformatics analysis

2019 ◽  
Vol 20 (S24) ◽  
Author(s):  
Jon P. Klein ◽  
Zhifu Sun ◽  
Nathan P. Staff
Keyword(s):  
Protein Interaction ◽  
Drug Targets ◽  
Large Scale ◽  
Bioinformatics Analysis ◽  
Enrichment Analysis ◽  
Protein Interaction Networks ◽  
Interaction Networks ◽  
Pathway Enrichment Analysis ◽  
Protein Database ◽  
Core Cluster

Abstract Background Emerging evidence suggests retroviruses play a role in the pathophysiology of amyotrophic lateral sclerosis (ALS). Specifically, activation of ancient viral genes embedded in the human genome is theorized to lead to motor neuron degeneration. We explore whether connections exist between ALS and retroviruses through protein interaction networks (PIN) and pathway analysis, and consider the potential roles in drug target discovery. Protein database and pathway/network analytical software including Ingenuity Pathway BioProfiler, STRING, and CytoScape were utilized to identify overlapping protein interaction networks and extract core cluster (s) of retroviruses and ALS. Results Topological and statistical analysis of the ALS-PIN and retrovirus-PIN identified a shared, essential protein network and a core cluster with significant connections with both networks. The identified core cluster has three interleukin molecules IL10, Il-6 and IL-1B, a central apoptosis regulator TP53, and several major transcription regulators including MAPK1, ANXA5, SQSTM1, SREBF2, and FADD. Pathway enrichment analysis showed that this core cluster is associated with the glucocorticoid receptor singling and neuroinflammation signaling pathways. For confirmation purposes, we applied the same methodology to the West Nile and Polio virus, which demonstrated trivial connectivity with ALS, supporting the unique connection between ALS and retroviruses. Conclusions Bioinformatics analysis provides evidence to support pathological links between ALS and retroviral activation. The neuroinflammation and apoptotic regulation pathways are specifically implicated. The continuation and further analysis of large scale genome studies may prove useful in exploring genes important in retroviral activation and ALS, which may help discover new drug targets.

scholarly journals Identification of a Five-Gene Prognostic Model and Its Potential Drug Repurposing in Colorectal Cancer Based on TCGA, GTEx and GEO Databases

2021 ◽  
Vol 11 ◽  
Author(s):  
Feng Yang ◽  
Shaoyi Cai ◽  
Li Ling ◽  
Haiji Zhang ◽  
Liang Tao ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Regulatory Region ◽  
Drug Repurposing ◽  
Enrichment Analysis ◽  
Tissue Expression ◽  
The Cancer Genome Atlas ◽  
Survival Prediction ◽  
Pathway Enrichment Analysis ◽  
Potential Drug ◽  
Hub Genes

Colorectal cancer (CRC) is a major cause of cancer deaths worldwide. Unfortunately, many CRC patients are still being diagnosed at an advanced stage of the cancer, and the 5-year survival rate is only ~30%. Effective prognostic markers of CRC are therefore urgently needed. To address this issue, we performed a detailed bioinformatics analysis based on the Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Gene Expression Omnibus (GEO) databases to identify prognostic biomarkers for CRC, which in turn help in exploring potential drug-repurposing. We identified five hub genes (PGM2, PODXL, RHNO1, SCD, and SEPHS1), which had good performance in survival prediction and might be involved in CRC through three key pathways (“Cell cycle,” “Purine metabolism,” and “Spliceosome” KEGG pathways) identified by a KEGG pathway enrichment analysis. What is more, we performed a co-expression analysis between five hub genes and transcription factors to explore the upstream regulatory region. Furthermore, we screened the potential drug-repurposing for the five hub genes in CRC according to the Binding DB and ZINC15 databases. Taking together, we constructed a five-gene signature to predict overall survival of CRC and found the potential drug-repurposing, which may improve the outcome of CRC in the future.

Pharmacological mechanism of Xiaoyao San in the treatment of polycystic ovary syndrome based on network pharmacology

2020 ◽  
Author(s):  
Chunyu Zhu ◽  
Yajun Hu ◽  
Wangdong Zheng ◽  
Yanyan Zhang ◽  
Yiting Li ◽  
...  
Keyword(s):  
Polycystic Ovary Syndrome ◽  
Drug Targets ◽  
Polycystic Ovary ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Active Components ◽  
Ovary Syndrome ◽  
Pharmacological Mechanism ◽  
R Project

Abstract Background : Xiaoyao San(XYS) has been widely used in the treatment of polycystic ovary syndrome(PCOS), but its mechanism is not clear. The purpose of this study is to elucidate the mechanism of XYS in the treatment of PCOS from the aspects of active components, targets and pathways. The purpose of the study is to explore the molecular mechanism of XYS in the treatment of PCOS. Methods : TCMSP database, UniProt and Perl were used to screen and collect the active components and targets of XYS. The genes related to PCOS were searched in GeneCards database. Collect the related targets of PCOS and XYS, use STRING database and Cytoscape software to process the data visually and analyze topology, and screen the key components and targets in the network. The key targets were enriched by R Project to predict the mechanism of XYS in the treatment of PCOS. Results : 68 active components and 96 drug targets in XYS were screened out. 3648 PCOS related disease targets were collected. 66 targets of XYS for PCOS treatment were obtained after analysis. 21 key targets of NCOA2, PGR, PTGS1, PPARG and AR were constructed after topology analysis. 63 biological functions and 111 biological pathways were obtained after gene ontology(GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG) Pathway enrichment analysis. Conclusions : XYS has the characteristics of multi-component, multi-target and multi-path. This study discussed the active components, targets and potential mechanism of XYS in the treatment of PCOS, which provided a new direction for further study of the mechanism of XYS in the treatment of PCOS, and provides more ideas for clinical treatment of PCOS.

scholarly journals A Network Pharmacology Technique to Investigate the Synergistic Mechanisms of Salvia miltiorrhiza and Radix puerariae in Treatment of Cardio-Cerebral Vascular Diseases

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Yang Ma ◽  
Wenjun Wang ◽  
Jiani Yang ◽  
Sha Zhang ◽  
Zhe Li ◽  
...  
Keyword(s):  
Drug Targets ◽  
Salvia Miltiorrhiza ◽  
Vascular Diseases ◽  
Enrichment Analysis ◽  
Mendelian Inheritance ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Active Ingredients ◽  
Radix Puerariae ◽  
Cerebral Vascular

Objective. This study is aimed to analyze the active ingredients, drug targets, and related pathways in the combination of Salvia miltiorrhiza (SM) and Radix puerariae (RP) in the treatment of cardio-cerebral vascular diseases (CCVDs). Method. The ingredients and targets of SM and RP were obtained from Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), and the disease targets were obtained from Therapeutic Target Database (TTD), National Center for Biotechnology Information (NCBI), and Online Mendelian Inheritance in Man (OMIM) Database. The synergistic mechanisms of the SM and RP were evaluated by gene ontology (GO) enrichment analyses and Kyoto encyclopedia of genes and genomes (KEGG) path enrichment analyses. Result. A total of 61 active ingredients and 58 common targets were identified in this study. KEGG pathway enrichment analysis results showed that SM- and RP-regulated pathways were mainly inflammatory processes, immunosuppression, and cardiovascular systems. The component-target-pathway network indicated that SM and RP exert a synergistic mechanism for CCVDs through PTGS2 target in PI3k-Akt, TNF, and Jak-STAT signaling pathways. Conclusion. In summary, this study clarified the synergistic mechanisms of SM and RP, which can provide a better understanding of effect in the treatment of CCVDs.

scholarly journals Construction of a TF–miRNA–gene feed-forward loop network predicts biomarkers and potential drugs for myasthenia gravis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Chunrui Bo ◽  
Huixue Zhang ◽  
Yuze Cao ◽  
Xiaoyu Lu ◽  
Cong Zhang ◽  
...  
Keyword(s):  
Myasthenia Gravis ◽  
Molecular Mechanisms ◽  
Critical Role ◽  
Mirna Gene ◽  
Experimental Studies ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Disease Genes ◽  
Feed Forward ◽  
Tf Gene

AbstractMyasthenia gravis (MG) is an autoimmune disease and the most common type of neuromuscular disease. Genes and miRNAs associated with MG have been widely studied; however, the molecular mechanisms of transcription factors (TFs) and the relationship among them remain unclear. A TF–miRNA–gene network (TMGN) of MG was constructed by extracting six regulatory pairs (TF–miRNA, miRNA–gene, TF–gene, miRNA–TF, gene–gene and miRNA–miRNA). Then, 3/4/5-node regulatory motifs were detected in the TMGN. Then, the motifs with the highest Z-score, occurring as 3/4/5-node composite feed-forward loops (FFLs), were selected as statistically significant motifs. By merging these motifs together, we constructed a 3/4/5-node composite FFL motif-specific subnetwork (CFMSN). Then, pathway and GO enrichment analyses were performed to further elucidate the mechanism of MG. In addition, the genes, TFs and miRNAs in the CFMSN were also utilized to identify potential drugs. Five related genes, 3 TFs and 13 miRNAs, were extracted from the CFMSN. As the most important TF in the CFMSN, MYC was inferred to play a critical role in MG. Pathway enrichment analysis showed that the genes and miRNAs in the CFMSN were mainly enriched in pathways related to cancer and infections. Furthermore, 21 drugs were identified through the CFMSN, of which estradiol, estramustine, raloxifene and tamoxifen have the potential to be novel drugs to treat MG. The present study provides MG-related TFs by constructing the CFMSN for further experimental studies and provides a novel perspective for new biomarkers and potential drugs for MG.

scholarly journals Identification of potential therapeutic targets and mechanisms of COVID-19 through network analysis and screening of chemicals and herbal ingredients

2021 ◽  
Author(s):  
Hong Wang ◽  
Jingqing Zhang ◽  
Zhigang Lu ◽  
Weina Dai ◽  
Chuanjiang Ma ◽  
...  
Keyword(s):  
Drug Targets ◽  
Drug Repurposing ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Therapeutic Effects ◽  
Protein Protein Interaction ◽  
Disease Module ◽  
Approved Drugs ◽  
Data Driven Modeling ◽  
The Relationship

Abstract After experiencing the COVID-19 pandemic, it is widely acknowledged that a rapid drug repurposing method is highly needed. A series of useful drug repurposing tools have been developed based on data-driven modeling and network pharmacology. Based on the disease module, we identified several hub proteins that play important roles in the onset and development of the COVID-19, which are potential targets for repositioning approved drugs. Moreover, different network distance metrics were applied to quantify the relationship between drug targets and COVID-19 disease targets in the protein–protein-interaction (PPI) network and predict COVID-19 therapeutic effects of bioactive herbal ingredients and chemicals. Furthermore, the tentative mechanisms of candidates were illustrated through molecular docking and gene enrichment analysis. We obtained 15 chemical and 15 herbal ingredient candidates and found that different drugs may play different roles in the process of virus invasion and the onset and development of the COVID-19 disease. Given pandemic outbreaks, our method has an undeniable immense advantage in the feasibility analysis of drug repurposing or drug screening, especially in the analysis of herbal ingredients.

scholarly journals Construction and comprehensive analysis of a ceRNA network to reveal potential prognostic biomarkers for lung adenocarcinoma

2021 ◽  
Author(s):  
Lei Gao ◽  
Ling Zhang
Keyword(s):  
Lung Adenocarcinoma ◽  
Drug Targets ◽  
Enrichment Analysis ◽  
Circular Rnas ◽  
Pathway Enrichment Analysis ◽  
Functional Roles ◽  
Cerna Network ◽  
Kaplan Meier ◽  
Underlying Mechanisms ◽  
Patient Prognosis

Abstract Background More and more studies have proven that circular RNAs (circRNAs) play vital roles in cancer development via sponging miRNAs. However, the expression pattern of competing endogenous RNA (ceRNA) in lung adenocarcinoma (LUAD) remains largely unclear. The current study explored functional roles and the regulatory mechanisms of circRNA as ceRNAs in LUAD and their potential impact on LUAD patient prognosis. Methods In this study, we systematically screened differential expression circRNAs (DEcircRNAs), miRNAs (DEmiRNAs) and mRNAs (DEGs) associated with LUAD. Then, DEcircRNAs, DEmiRNAs and DEGs were selected to construct a circRNA–miRNA–mRNA prognosis-related regulatory network based on interaction information from the ENCORI database. Subsequently, the gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed on the genes in the network to predict the potential underlying mechanisms and functions of circRNAs in LUAD. In addition, Kaplan–Meier survival analysis was performed to evaluate clinical outcomes of LUAD patients, and drug sensitivity analysis was used to screen potential biomarkers for drug treatment of patients with LUAD. Results As a result, ten circRNAs were aberrantly expressed in LUAD tissues. The ceRNA network was built, which included 3 DEcircRNAs, 6 DEmiRNAs and 157 DEGs. The DEGs in the ceRNA network of hsa_circ_0049271 enriched in biological processes of cell proliferation and the Jak-STAT signaling pathway. We also detected 7 mRNAs in the ceRNA network of hsa_circ_0049271 that were significantly associated with the overall survival of LUAD patients (P < 0.05). Importantly, four genes (PDGFB, CCND2, CTF1, IL7R) identified were strongly associated with STAT3 activation and drugs sensitivity in GDSC. Conclusions In summary, a ceRNA network was successfully constructed, which including one circRNA, two miRNAs, and seven mRNAs. Seven mRNAs (PDGFB, TNFRSF19, CCND2, CTF1, IL11RA, IL7R and MAOA) were remarkably associated with the prognosis of LUAD patients. Among seven mRNA species, four genes (PDGFB, CCND2, CTF1, and IL7R) could be considered as drug targets in LUAD. Our research will provide new insights into the prognosis-related ceRNA network in LUAD.

scholarly journals Mapping the SARS-CoV-2–Host Protein–Protein Interactome by Affinity Purification Mass Spectrometry and Proximity-Dependent Biotin Labeling: A Rational and Straightforward Route to Discover Host-Directed Anti-SARS-CoV-2 Therapeutics

2021 ◽  
Vol 22 (2) ◽  
pp. 532
Author(s):  
Rosa Terracciano ◽  
Mariaimmacolata Preianò ◽  
Annalisa Fregola ◽  
Corrado Pelaia ◽  
Tiziana Montalcini ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Drug Discovery ◽  
Protein Interactions ◽  
Drug Targets ◽  
Affinity Purification ◽  
Drug Repurposing ◽  
Host Protein ◽  
Host Cells ◽  
Traditional Drug ◽  
Approved Drugs

Protein–protein interactions (PPIs) are the vital engine of cellular machinery. After virus entry in host cells the global organization of the viral life cycle is strongly regulated by the formation of virus-host protein interactions. With the advent of high-throughput -omics platforms, the mirage to obtain a “high resolution” view of virus–host interactions has come true. In fact, the rapidly expanding approaches of mass spectrometry (MS)-based proteomics in the study of PPIs provide efficient tools to identify a significant number of potential drug targets. Generation of PPIs maps by affinity purification-MS and by the more recent proximity labeling-MS may help to uncover cellular processes hijacked and/or altered by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), providing promising therapeutic targets. The possibility to further validate putative key targets from high-confidence interactions between viral bait and host protein through follow-up MS-based multi-omics experiments offers an unprecedented opportunity in the drug discovery pipeline. In particular, drug repurposing, making use of already existing approved drugs directly targeting these identified and validated host interactors, might shorten the time and reduce the costs in comparison to the traditional drug discovery process. This route might be promising for finding effective antiviral therapeutic options providing a turning point in the fight against the coronavirus disease-2019 (COVID-19) outbreak.

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