• The Korea Journal of Herbology
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• v.38 no.6
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• pp.73-91
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• 2023

Objectives : This study used a network pharmacology approach to elucidate the efficacy and molecular mechanisms of Daehwangmokdanpitang (DHMDPT) on Psoriasis. Methods : Using OASIS databases and PubChem database, compounds of DHMDPT and their target genes were collected. The putative target genes of DHMDPT and known target genes of psoriasis were compared and found the correlation. Then, the network was constructed using Cytoscape 3.10.1. The key target genes were screened by Analyzer network and their functional enrichment analysis was conducted based on the Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathways to predict the mechanisms. Results : The result showed that total 30 compounds and 439 related genes were gathered from DHMDPT. 264 genes were interacted with psoriasis gene set, suggesting that the effects of DHMDPT are closely related to psoriasis. Based on GO enrichment analysis and KEGG pathways, 'Binding', 'Cytokine Activity', 'Receptor Ligand Activity' 'HIF-1 signaling pathway', 'IL-17 signaling pathway', 'Toll-like receptor signaling pathway', and 'TNF signaling pathway' were predicted as functional pathways of 16 key target genes of DHMDPT on psoriasis. Among the target genes, IL6, IL1B, TNF, AKT1 showed high correlation with the results of KEGG pathways. Additionally, Emodin, Acetovanillone, Gallic acid, and Ferulic acid showed a high relevance with key genes and their mechanisms. Conclusion : Through a network pharmacological method, DHMDPT was predicted to have high relevance with psoriasis. This study could be used as a basis for studying therapeutic effects of DHMDPT on psoriasis.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.22
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• pp.9791-9795
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• 2014

To study the gene expression change and possible signal pathway during androgen-dependent prostate cancer (ADPC) becoming androgen-independent prostate cancer (AIPC), an LNCaP cell model of AIPC was established using flutamide in combination with androgen-free environment inducement, and differential expression genes were screened by microarray. Then the biological process, molecular function and KEGG pathway of differential expression genes are analyzed by Molecule Annotation System (MAS). By comparison of 12,207 expression genes, 347 expression genes were acquired, of which 156 were up-ragulated and 191 down-regulated. After analyzing the biological process and molecule function of differential expression genes, these genes are found to play crucial roles in cell proliferation, differntiation, cell cycle control, protein metabolism and modification and other biological process, serve as signal molecules, enzymes, peptide hormones, cytokines, cytoskeletal proteins and adhesion molecules. The analysis of KEGG show that the relevant genes of AIPC transformation participate in glutathione metabolism, cell cycle, P53 signal pathway, cytochrome P450 metabolism, Hedgehog signal pathway, MAPK signal pathway, adipocytokines signal pathway, PPAR signal pathway, TGF-${\beta}$ signal pathway and JAK-STAT signal pathway. In conclusion, during the process of ADPC becoming AIPC, it is not only one specific gene or pathway, but multiple genes and pathways that change. The findings above lay the foundation for study of AIPC mechanism and development of AIPC targeting drugs.

• Molecular & Cellular Toxicology
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• v.4 no.4
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• pp.267-277
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• 2008

Benzene and ethylbenzene (BE), the volatile organic compounds (VOCs) are common constituents of cleaning and degreasing agents, paints, pesticides, personal care products, gasoline and solvents. VOCs are evaporated at room temperature and most of them exhibit acute and chronic toxicity to human. Chronic exposure of benzene is responsible for myeloid leukemia and also ethylbenzene is also recognized as a possible carcinogen. To evaluate the BE effect on human, whole human genome 35 K oligonucleotide microarray were screened for the identification of the differential expression profiling. We identified 280 up-regulated and 201 down-regulated genes changed by more than 1.5 fold by BE exposure. Functional analysis was carried out by using DAVID bioinformatics software. Clustering of these differentially expressed genes were associated with immune response, cytokine-cytokine receptor interaction, toll-like signaling pathway, small cell lung cancer, immune response, apoptosis, p53 signaling pathway and MAPKKK cascade possibly constituting alternative or subordinate pathways of hematotoxicity and immune toxicity. Gene ontology analysis methods including biological process, cellular components, molecular function and KEGG pathway thus provide a fundamental basis of the molecular pathways through BEs exposure in human lymphoma cells. This may provides a valuable information to do further analysis to explore the mechanism of BE induced hematotoxicity.

• Proceedings of the Korea Contents Association Conference
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• 2016.05a
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• pp.191-192
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• 2016

DNA 염기서열 자체에는 변화가 없으나 크로마틴의 변형을 통하여 유전자의 발현 양상이 변하는 현상을 후성유전이라 한다. 최근에 이런 후성유전학적 변이가 암 발생과 밀접한 연관이 있는 것으로 알려졌다. 본 연구에서는 암 관련 단백질과 암 관련 후성유전 단백질 상호작용 네트워크를 통하여 암과 후성 유전적 관계를 분석하고자 하였다. 먼저 상호작용 네트워크를 기반으로 허브에 해당하는 히스톤 변형 단백질 20개를 추출하였다. 추출한 20개 단백질을 KEGG pathway에 적용하여 암 관련 단백질과의 상관관계를 분석하였다. 암 관련 단백질 발현양상을 확인할 수 있는 Expression Atlas로부터 발현이 증가하거나 감소하는 단백질을 분류하고, 발현 정보를 KEGG pathway 위에 있는 단백질에 적용함으로써 후성유전학적 암 발생 기전을 도출하였다.

• The Journal of Korean Medicine
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• v.31 no.4
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• pp.79-100
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• 2010

Objective: Production of ROS from glucose toxicity results in injury of pancreatic $\beta$-cells in diabetes models. This study was undertaken to examine the influence of Lespedeza Cuneata extract (LCE) on cytoprotective effects on glucose toxicity, insulin secretion and gene expression in RIN-m5F cells. Methods: First, we measured LCE's antioxidant activity by DPPH free radical-scavenging activity and SOD activity. After the various concentrations of LCE were added to the RIN-m5F cells, we measured cell viability with glucose stimulation by MTT assay and glucose-stimulated insulin secretion. We analyzed gene expression with Agilent whole mouse genome 44K oligo DNA microarray and searched for related pathways in KEGG (Kyoto Encyclopedia of Genes and Genomes). Lastly we measured INS-1, INS-2, INS-R, IRS-1, IRS-2, IRS-3, GLP-1R, and GLP-2R mRNA expression by real time RT-PCR. Results: Free radical-scavenging activity, SOD activity and insulin secretion increased dependent on LCE concentration, but LCE did not show considerable cytoprotective effect on RIN-m5F cells. More than twice expressed gene was 6362 in Oligo DNA chip. In KEGG, the most related pathway was the metabolic pathway. In the insulin signaling pathway, up expressed genes were Irs1, Mapk8, Akt1, and Lipe and down expressed genes were Rhoq, Fbp2, Prkar2b, Gck, and Prkag1. In real time RT-PCR, IRS-2, and IRS-3 expression increased significantly compared to the control group on LCE $12{\mu}g/m{\ell}$ concentration and GCK expression decreased significantly compared to the control group. Conclusions: These results show that LCE encourages insulin secretion and insulin metabolism by complicated gene mechanisms. Further mechanism study and clinical study seem to be necessary about Lespedeza Cuneata.

• Genomics & Informatics
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• v.20 no.2
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• pp.20.1-20.13
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• 2022

Recent studies have focused on the early detection of ovarian cancer (OC) using tumor materials by liquid biopsy. The mechanisms of microRNAs (miRNAs) to impact OC and signaling pathways are still unknown. This study aims to reliably perform functional analysis of previously validated circulating miRNAs' target genes by using pathfindR. Also, overall survival and pathological stage analyses were evaluated with miRNAs' target genes which are common in the The Cancer Genome Atlas and GTEx datasets. Our previous studies have validated three downregulated miRNAs (hsa-miR-885-5p, hsa-miR-1909-5p, and hsa-let7d-3p) having a diagnostic value in OC patients' sera, with high-throughput techniques. The predicted target genes of these miRNAs were retrieved from the miRDB database (v6.0). Active-subnetwork-oriented Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was conducted by pathfindR using the target genes. Enrichment of KEGG pathways assessed by the analysis of pathfindR indicated that 24 pathways were related to the target genes. Ubiquitin-mediated proteolysis, spliceosome and Notch signaling pathway were the top three pathways with the lowest p-values (p < 0.001). Ninety-three common genes were found to be differentially expressed (p < 0.05) in the datasets. No significant genes were found to be significant in the analysis of overall survival analyses, but 24 genes were found to be significant with pathological stages analysis (p < 0.05). The findings of our study provide in-silico evidence that validated circulating miRNAs' target genes and enriched pathways are related to OC and have potential roles in theranostics applications. Further experimental investigations are required to validate our results which will ultimately provide a new perspective for translational applications in OC management.

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.4
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• pp.138-147
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• 2007

Metabolic pathway is a series of chemical reactions occuning within a cell and can be used for drug development and understanding of life phenomenon. Many biologists are trying to extract metabolic pathway information from huge literatures for their metabolic-circuit regulation study. We propose a text-mining technique based on the keyword and pattern. Proposed technique utilizes a web robot to collect huge papers and stores them into a local database. We use gene ontology to increase compound recognition rate and NCBI Tokenizer library to recognize useful information without compound destruction. Furthermore, we obtain useful sentence patterns representing metabolic pathway from papers and KEGG database. We have extracted 66 patterns in 20,000 documents for Glycosphingolipid species from KEGG, a representative metabolic database. We verify our system for nineteen compounds in Glycosphingolipid species. The result shows that the recall is 95.1%, the precision 96.3%, and the processing time 15 seconds. Proposed text mining system is expected to be used for metabolic pathway reconstruction.

• Journal of Microbiology and Biotechnology
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• v.31 no.4
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• pp.621-629
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• 2021

Shigella flexneri is a facultative intracellular pathogen that causes bacillary dysentery in humans. Infection with S. flexneri can result in more than a million deaths yearly and most of the victims are children in developing countries. Therefore, identifying novel and unique drug targets against this pathogen is instrumental to overcome the problem of drug resistance to the antibiotics given to patients as the current therapy. In this study, a comparative analysis of the metabolic pathways of the host and pathogen was performed to identify this pathogen's essential enzymes for the survival and propose potential drug targets. First, we extracted the metabolic pathways of the host, Homo sapiens, and pathogen, S. flexneri, from the KEGG database. Next, we manually compared the pathways to categorize those that were exclusive to the pathogen. Further, all enzymes for the 26 unique pathways were extracted and submitted to the Geptop tool to identify essential enzymes for further screening in determining the feasibility of the therapeutic targets that were predicted and analyzed using PPI network analysis, subcellular localization, druggability testing, gene ontology and epitope mapping. Using these various criteria, we narrowed it down to prioritize 5 novel drug targets against S. flexneri and one vaccine drug targets against all strains of Shigella. Hence, we suggest the identified enzymes as the best putative drug targets for the effective treatment of S. flexneri.

• Proceedings of the Korea Contents Association Conference
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• 2015.05a
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• pp.231-232
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• 2015

최근 유전체학, NGS(Next Generation Sequencing) 기술, IT/NT 장비의 발전 등에 따라 방대한 양의 바이오-메디컬 데이터가 생산되고, 이에 따라 빅데이터를 활용한 헬스케어 산업이 급속히 발달하고 있으며, 이와 관련된 빅데이터 기술은 국민의 건강 증대와 건강한 고령 삶을 제공하는 핵심 기술로 급부상하고 있다. 패스웨이는 단백질, 유전자, 세포 등의 생체적 요소 간의 역학관계 혹은 상호작용 등을 네트워크 형식으로 표현한 생물학적 심층지식으로, 바이오-메디컬 빅데이터 분석에 있어서 널리 활용되고 있다. 하지만 패스웨이는 매우 다양한 형태를 갖고 용량이 매우 큰 빅데이터로 이를 분석하는데 많은 시간이 소요된다. 그래서 본 논문에서는 세계적으로 가장 우수하고 방대한 양의 패스웨이를 제공하는 KEGG 패스웨이 데이터베이스로부터 사용자가 관심 갖는 패스웨이만을 자동 수집하고 패스웨이 간 계층구조를 기반으로 네트워크를 구성 후, 해당 패스웨이 네트워크에 대한 클러스터링과 핵심 패스웨이 선정을 통해 패스웨이 간의 역학관계 또는 상호작용을 직관적으로 분석할 수 시스템을 제안했다.

• Journal of Plant Biotechnology
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• v.43 no.2
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• pp.189-203
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• 2016

Brassica oleraceae var capitata is a member of the Brassicaceae family and is widely used as an horticultural crop. In the present study, transcriptome analysis of B. oleraceae L. var capitata was done for the first time using eight-week old seedlings treated with $50{\mu}m$ MeJA, versus mock-treated samples. The complete transcripts for both samples were obtained using the GS-FLX sequencer. Overall, we obtained 275,570 and 266,457 reads from seedlings treated with or without $50{\mu}m$ MeJA, respectively. All the obtained reads were annotated using biological databases and functionally classified using gene ontology (GO), the Kyoto Encyclopedia of Genes and Genomics (KEGG). By using GO analyses, putative transcripts were examined in terms of biotic and abiotic stresses, cellular component organization, biogenesis, and secondary metabolic processes. The KEGG pathways for most of the transcripts were involved in carbohydrate metabolism, energy metabolism, and secondary metabolite synthesis. In order to double the sequenced data, we randomly chose two putative genes involved in terpene biosynthetic pathways and studied their transcript patterns under MeJA treatment. This study will provide us a platform to further characterize the genes in B. oleracea var capitata.