Network-based prediction of drug–target interactions using an arbitrary-order proximity embedded deep forest

Zeng, Xiangxiang; Zhu, Siyi; Hou, Yuan; Zhang, Pengyue; Li, Lang; Li, Jing; Huang, Lei; Lewis, Stephen J.; Nussinov, Ruth; Cheng, Feixiong

doi:10.1093/bioinformatics/btaa010

Cited by 122 publications

(76 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…After adding its target, an RNA helicase enzyme EIF4A 76 , silvestrol was predicted to be significantly associated with HCoVs (Z = -1.24, P = 0.041) by network proximity analysis. To increase coverage of drug-target networks, we may use computational approaches to systematically predict the drug-target interactions further 25,26 . In addition, the collected virus-host interactions are far from completeness and the quality can be influenced by multiple factors, including different experimental assays and human cell line models.…”

Section: Discussionmentioning

confidence: 99%

“…This methodology allows to identify several candidate repurposable drugs for Ebola virus 11,14 . Our work over the last decade has demonstrated how network strategies can, for example, be used to identify effective repurposable drugs 13,[22][23][24][25][26][27] and drug combinations 28 for multiple human diseases. For example, network-based drug-disease proximity sheds light on the relationship between drugs (e.g., drug targets) and disease modules (molecular determinants in disease pathobiology modules within the PPIs), and can serve as a useful tool for efficient screening of potentially new indications for approved drugs, as well as drug combinations, as demonstrated in our recent studies 13,23,27,28 .…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Network-based drug repurposing for novel coronavirus 2019-nCoV/SARS-CoV-2

et al. 2020

Self Cite

View full text Add to dashboard Cite

Human coronaviruses (HCoVs), including severe acute respiratory syndrome coronavirus (SARS-CoV) and 2019 novel coronavirus (2019-nCoV, also known as SARS-CoV-2), lead global epidemics with high morbidity and mortality. However, there are currently no effective drugs targeting 2019-nCoV/SARS-CoV-2. Drug repurposing, representing as an effective drug discovery strategy from existing drugs, could shorten the time and reduce the cost compared to de novo drug discovery. In this study, we present an integrative, antiviral drug repurposing methodology implementing a systems pharmacology-based network medicine platform, quantifying the interplay between the HCoV-host interactome and drug targets in the human protein-protein interaction network. Phylogenetic analyses of 15 HCoV whole genomes reveal that 2019-nCoV/SARS-CoV-2 shares the highest nucleotide sequence identity with SARS-CoV (79.7%). Specifically, the envelope and nucleocapsid proteins of 2019-nCoV/SARS-CoV-2 are two evolutionarily conserved regions, having the sequence identities of 96% and 89.6%, respectively, compared to SARS-CoV. Using network proximity analyses of drug targets and HCoV-host interactions in the human interactome, we prioritize 16 potential anti-HCoV repurposable drugs (e.g., melatonin, mercaptopurine, and sirolimus) that are further validated by enrichment analyses of drug-gene signatures and HCoV-induced transcriptomics data in human cell lines. We further identify three potential drug combinations (e.g., sirolimus plus dactinomycin, mercaptopurine plus melatonin, and toremifene plus emodin) captured by the "Complementary Exposure" pattern: the targets of the drugs both hit the HCoV-host subnetwork, but target separate neighborhoods in the human interactome network. In summary, this study offers powerful network-based methodologies for rapid identification of candidate repurposable drugs and potential drug combinations targeting 2019-nCoV/SARS-CoV-2.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Network-based drug repurposing for novel coronavirus 2019-nCoV/SARS-CoV-2

et al. 2020

Self Cite

View full text Add to dashboard Cite

show abstract

“…The present study aimed to use transcriptome technology to uncover the response of bovine mammary epithelial cells (BMEC) to LPS as a way to identify key candidate genes that could be target for functional verification. Along with other assays, a combined technological approach can provide precise targets for research and development of effective therapeutic drugs, ultimately achieving positive effects in terms of prevention and treatment (10).…”

Section: Introductionmentioning

confidence: 99%

Tea Tree Oil Prevents Mastitis-Associated Inflammation in Lipopolysaccharide-Stimulated Bovine Mammary Epithelial Cells

et al. 2020

View full text Add to dashboard Cite

The main purpose of this study was to explore the effect of tea tree oil (TTO) on lipopolysaccharide (LPS)-induced mastitis model using isolated bovine mammary epithelial cells (BMEC). This mastitis model was used to determine cellular responses to TTO and LPS on cellular cytotoxicity, mRNA abundance and cytokine production. High-throughput sequencing was used to select candidate genes, followed by functional evaluation of those genes. In the first experiment, LPS at a concentration of 200 µg/mL reduced cell proliferation, induced apoptosis and upregulated protein concentrations of tumor necrosis factor-α (TNF-α), interleukin 6 (IL-6), and signal transducer and activator of transcription 1 (STAT1). Addition of TTO led to reduced cellular apoptosis along with downregulated protein concentrations of nuclear factor kappa B, mitogen-activated protein kinase 4 (MAPK4) and caspase-3. In the second experiment, BMEC challenged with LPS had a total of 1,270 differentially expressed genes of which 787 were upregulated and 483 were downregulated. Differentially expressed genes included TNF-α, IL6, STAT1, and MAPK4. Overall, results showed that TTO (at least in vitro) has a protective effect against LPS-induced mastitis. Further in vivo research should be performed to determine strategies for using TTO for prevention and treatment of mastitis and improvement of milk quality.

show abstract

“…Concurrently, this approach can provide precise targets for the research and development of related therapeutic drugs, ultimately achieving the expected combined results of prevention and treatment (15). In the omics study of mastitis, miRNA expression in bovine tissues was first confirmed in 2007 (16).…”

Section: Introductionmentioning

confidence: 99%

Tea tree oil prevents mastitis-associated inflammation in lipopolysaccharide-stimulated bovine mammary epithelial cells

Chen

Zhang

Zhou

et al. 2020

Preprint

View full text Add to dashboard Cite

Background Effective prevention and treatment of cow mastitis can provide a good guarantee for the healthy growth of cows and the qualified production of dairy products. The main purpose of this study was to explore the effect of tea tree oil on lipopolysaccharide (LPS) -induced mastitis in dairy cows, and the key gene in LPS -stimulated bovine mammary epithelial cells (BMECs) was identified. Results In this study, a model of mastitis induced by LPS was constructed, to which tea tree oil and LPS were added. The protective effects of tea tree oil on LPS-induced mastitis in BMECs were verified by the CCK-8 method, flow cytometry, real-time fluorescence quantitative detection, ELISA and other methods. The results showed that LPS at a concentration of 200 μg/ml could reduce the proliferative activity of the cells, induce a high proportion of apoptosis, and promote the expression of TNF-α, IL-6 and STAT1. Upon addition of tea tree oil, the proportion of apoptosis was reduced, and the expression of NF-κB, MAPK and caspase-3 was inhibited. Mammary epithelial cells were compared under control and LPS-treatment conditions and analyzed by second-generation sequencing. A total of 1270 mRNAs were identified as differentially expressed, of which 787 genes were upregulated and 483 were downregulated. These differentially expressed genes include TNF - α, IL6, STAT1, mapk4, etc. H&E staining and immunohistochemistry were used to verify the function of candidate genes. TNF-α and IL6 were observed to play important roles in mediating the preventive effect of tea tree oil on mastitis in LPS-stimulated bovine mammary epithelial cells. Conclusions The results showed that tea tree oil had a protective effect against LPS-induced mastitis. TNF - α and IL6 may be the marker genes of LPS-induced mastitis which provided a theoretical basis and experimental support for further research to determine new strategies for the prevention and treatment of mastitis and improvement of milk quality.

show abstract

Network-based prediction of drug–target interactions using an arbitrary-order proximity embedded deep forest

Cited by 122 publications

References 43 publications

Network-based drug repurposing for novel coronavirus 2019-nCoV/SARS-CoV-2

Network-based drug repurposing for novel coronavirus 2019-nCoV/SARS-CoV-2

Tea Tree Oil Prevents Mastitis-Associated Inflammation in Lipopolysaccharide-Stimulated Bovine Mammary Epithelial Cells

Tea tree oil prevents mastitis-associated inflammation in lipopolysaccharide-stimulated bovine mammary epithelial cells

Contact Info

Product

Resources

About