• 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.

• Herbal Formula Science
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• v.18 no.2
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• pp.227-239
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• 2010

Objective : The purpose of this study was to develop the simulator which can analyze the anti-inflammatory effects of herbs based on e-cell, or the virtual cell. Method : We have ensured the medical herbs and its active compounds by investigating the oriental medicine records and NBCI(Biomedicine database). Also we have developed the web-based search system for confirming database related to anti-inflammation. We have researched the cell signal pathway related with inflammatory response control and established the mathematical model of herb interaction on selected signal pathway in e-cell. Finally we have developed the prototype which can confirm the result of this model visibly. Results : We constructed the database of 62 cases of anti-inflammatory active compounds in 61 cases of medical herbs which have been known anti-inflammation effects in the paper, 16 cases of inflammatory factors, 10 cases of signal pathways related with inflammatory response and 6,834 cases of URL(Uniform Resource Locator) of referenced papers. And we embodied the web-based research system, which can research this database. User can search basic and detailed information of medical plants related with anti-inflammatory by using information system. And user can acquire information on an active compounds, a signal pathway and a link URL of related paper. Among investigated ten pathways, we selected NF-${\kappa}B$, which plays important role in activation of immune system, and we searched the mechanisms of actions of proteins which could be components of this pathway. We reduced total network into IKK-$I{\kappa}B$ - NF-${\kappa}B$, and completed mathematic modeling by using ordinary differential equations and response variables of $I{\kappa}B-NF-{\kappa}B$ signaling model network which is suggested by Baltimore Group. We designed OED(Ordinary Differential Equation) for response of IKK, $I{\kappa}B$, $NF-{\kappa}B$ in e-cell's cytoplasm and nucleus, and measured whether an active compound of medicinal plants which is inputted by an user would have a anti-inflammation effects in obedience to change in concentration over time. The proposed model was verified by using experimental results of the papers which are listed on NCBI.

• Genomics & Informatics
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• v.7 no.3
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• pp.175-177
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• 2009

We have developed WinBioDBs with Windows interfaces, which include importing modules and searching interfaces for 10 major public databases such as GenBank, PIR, SwissProt, Pathway, EPD, ENZYME, REBASE, Prosite, Blocks, and Pfam. User databases can be constructed with searching results of queries and their entries can be edited. The program is a stand-alone database searching program on Windows PC. Database update features are supported by importing raw database files and indexing after downloading them. Users can adjust their own searching environments and report format and construct their own projects consisting of a combination of a local databases. WinBioDBs are implemented with VC++ and its database is based on MySQL.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.7
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• pp.3313-3317
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• 2012

Prostate cancer is a highly prevalent disease in older men of the western world. MicroRNAs (miRNAs) are small RNA molecules that regulate gene expression via posttranscriptional inhibition of protein synthesis. To identify the diagnostic potential of miRNAs in prostate cancer, we downloaded the miRNA expression profile of prostate cancer from the GEO database and analysed the differentially expressed miRNAs (DE-miRNAs) in prostate cancerous tissue compared to non-cancerous tissue. Then, the targets of these DE-miRNAs were extracted from the database and mapped to the STRING and KEGG databases for network construction and pathway enrichment analysis. We identified a total of 16 miRNAs that showed a significant differential expression in cancer samples. A total of 9 target genes corresponding to 3 DE-miRNAs were obtained. After network and pathway enrichment analysis, we finally demonstrated that miR-20 appears to play an important role in the regulation of prostate cancer onset. MiR-20 as single biomarker or in combination could be useful in the diagnosis of prostate cancer. We anticipate our study could provide the groundwork for further experiments.

• Herbal Formula Science
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• v.28 no.3
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• pp.243-254
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• 2020

Objectives : Network pharmacology analysis is commonly used to investigate the synergies and potential mechanisms of multiple compounds by analyzing complex, multi-layered networks. We used TCMSP and BATMAN-TCM databases to compare results of network pharmacological analysis between White Ginseng(WG) and Red Ginseng(RG). Methods : WG and RG were compared with components and their target molecules using TCMSP database, and compound-target-pathway/disease networks were compared using BATMAN-TCM database. Results : Through TCMSP, 104 kinds of target molecules were derived from WG and 38 kinds were derived from RG. Using the BATMAN-TCM database, target pathways and diseases were screened, and more target pathways and diseases were screened compared to RG due to the high composition of WG ingredients. Analysis of component-target-pathway/disease network using network analysis tools provided by BATMAN-TCM showed that WG formed more networks than RG. Conclusions : Network pharmacology analysis can be effectively performed using various databases used in system biology research, and although the materials that have been reported in the past can be used efficiently for research on diseases related to targets, the results are unreliable if prior studies are focused on limited or narrow research areas.

• Herbal Formula Science
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• v.30 no.3
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• pp.175-182
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• 2022

Objective : This study aims to investigate the active ingredients and potential mechanisms of the beneficial herb on human cancers such as the liver by employing network pharmacology. Methods : Ingredients and their target information was obtained from various databases such as TM-MC, TTD, and Drugbank. Related protein for liver cancer was retrieved from the Comparative Toxicogenomics Database and literature. A hypergeometric test and gene set enrichment analysis were conducted to evaluate associations between protein targets of red ginseng (Panax ginseng C. A. Meyer) and liver cancer-related proteins and identify related signaling pathways, respectively. Network proximity was employed to identify active ingredients of red ginseng on liver cancer. Results : A compound-target network of red ginseng was constructed, which consisted of 363 edges between 53 ingredients and 121 protein targets. MAPK signaling pathway, PI3K-Akt signaling pathway, p53 signaling pathway, TGF-beta signaling pathway, and cell cycle pathway was significantly associated with protein targets of red ginseng. Network proximity results indicated that Ginsenoside Rg1, Acetic Acid, Ginsenoside Rh2, 20(R)-Ginsenoside Rg3, Notoginsenoside R1, Ginsenoside Rk1, 2-Methylfuran, Hexanal, Ginsenoside Rd, Ginsenoside Rh1 could be active ingredients of red ginseng against liver cancer. Conclusion : This study suggests that network-based approaches could be useful to explore potential mechanisms and active ingredients of red ginseng for liver cancer.

• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.22 no.3
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• pp.47-62
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• 2009

Glenditsia spina (GS) can resolve carbuncle, relive swelling, dispel wind and destroy parasites. For these reasons, GS has been widely used as dermatologic agent clinically. In this study, the specific pathways of anti-proliferative effect of GS on human derived melanoma cells were identified. The molecular profile was measured using microarray technique to identify up- or down-regulated genes in SK-MEL-2 cell line. Pathway analysis was done by listing percentage of pathway involvement, and the represented pathways were obtained from KEGG. The transcription factor binding sequences were obtained by Transfac database. By the promoter analysis, up-regulated genes by GS were mainly associated with MAPK, Regulation of actin cytoskeleton, Wnt, Focal adhesion and Long term potentiation pathway. Down-regulated genes by GS were mainly associated with MAPK and Antigen processing and presentation pathway. And some of the transcription factors like Sp1 and NF-Y in up-regulated genes and Oct-1 in down-regulated genes by GS also identified.

• The Korea Journal of Herbology
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• v.38 no.1
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• pp.45-53
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• 2023

Objectives : Network pharmacology-based research is one of useful tool to predict the possible efficacy and molecular mechanisms of natural materials with multi compounds-multi targeting effects. In this study, we investigated the functional underlying mechanisms of Astragalus membranaceus Bunge (AM) on its anti-obesity effects using a network pharmacology analysis. Methods : The constituents of AM were collected from public databases and its target genes were gathered from PubChem database. The target genes of AM were compared with the gene set of obesity to find the correlation. Then, the network was constructed by Cytoscape 3.9.1. and functional enrichment analysis was conducted to predict the most relevant pathway of AM. Results : The result showed that AM network contained the 707 nodes and 6867 edges, and 525 intersecting genes were exhibited between AM and obesity gene set, indicating that high correlation with the effects of AM on obesity. Based on GO biological process and KEGG Pathway, 'Response to lipid', 'Cellular response to lipid', 'Lipid metabolic process', 'Regulation of chemokine production', 'Regulation of lipase activity', 'Chemokine signaling pathway', 'Regulation of lipolysis in adipocytes' and 'PPAR signaling pathway' were predicted as functional pathways of AM on obesity. Conclusions : AM showed high relevance with the lipid metabolism related with the chemokine production and lipolysis pathways. This study could be a basis that AM has promising effects on obesity via network pharmacology analysis.

• 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.

• Genomics & Informatics
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• v.16 no.4
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• pp.28.1-28.6
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• 2018

Due to the increasing interest in synonymous codons, several codon bias-related terms were introduced. As one measure of them, the tRNA adaptation index (tAI) was invented about a decade ago. The tAI is a measure of translational efficiency for a gene and is calculated based on the abundance of intracellular tRNA and the binding strength between a codon and a tRNA. The index has been widely used in various fields of molecular evolution, genetics, and pharmacology. Afterwards, an improved version of the index, named specific tRNA adaptation index (stAI), was developed by adapting tRNA copy numbers in species. Although a subsequently developed webserver (stAIcalc) provided tools that calculated stAI values, it was not available to access pre-calculated values. In addition to about 100 species in stAIcalc, we calculated stAI values for whole coding sequences in 148 species. To enable easy access to this index, we constructed a novel web database, named STADIUM (Species-specific tRNA adaptive index compendium). STADIUM provides not only the stAI value of each gene but also statistics based on pathway-based classification. The database is expected to help researchers who have interests in codon optimality and the role of synonymous codons. STADIUM is freely available at http://stadium.pmrc.re.kr.