• 한국지식정보기술학회논문지
• /
• 제13권5호
• /
• pp.607-614
• /
• 2018

오령산은 몸 속의 수분을 순환시키고 소변으로 배출이 잘 되게 하는 효능이 있어 수분이 정체되어 나타나는 질환에 많이 쓰이는 처방이다. 본 연구에서는 시스템 약리학 접근 방법을 이용해서 오령산의 작용 기전을 탐색하기 위해서 오령산의 구성약재의 성분-타겟 네트워크를 구축하고 분석하였다. 우선, 오령산의 475개 성분에 대해서 STITCH 데이터베이스에서 연관된 타겟을 검색하였으며, 성분과 타겟의 상호작용에 대한 검색 결과는 XML 파일로 다운로드하였다. 본 연구에서 성분-타겟 네트워크는 Gephi를 이용해서 시각화하고 탐색하였다. 노드는 성분과 타겟이 되고, 링크는 성분과 타겟들간에 상호작용이 존재하면 연결되며, 상호작용의 신뢰도에 따라 링크에 가중치를 부여하였다. MCL 알고리즘을 이용해서 네트워크를 클러스터링 하였으며, 총 130개의 클러스터가 생성되었다. 가장 많은 노드를 가지는 클러스터에서 노드의 개수는 32개였다. 성분-타겟 네트워크에서 약재의 유효 성분들이 신장의 혈압 조절 기능과 관련된 타겟들과 연결되어 있는 것을 발견할 수 있었다. 향후에는 질병 데이터베이스와 연계해서 보다 명확한 오령산의 작용 기전을 밝힐 수 있도록 할 계획이다.

• 로봇학회논문지
• /
• 제13권4호
• /
• pp.213-219
• /
• 2018

In this paper, we introduce a target position reasoning system based on Bayesian network that selects destinations of robots on a map to explore compound disaster environments. Compound disaster accidents have hazardous conditions because of a low visibility and a high temperature. Before firefighters enter the environment, the robots notify information in advance, such as victim's positions, number of victims, and status of debris of building. The problem of the previous system is that the system requires a target position to operate the robots and the firefighter need to learn how to use the robot. However, selecting the target position is not easy because of the information gap between eyewitness accounts and map coordinates. In addition, learning the technique how to use the robots needs a lot of time and money. The proposed system infers the target area using Bayesian network and selects proper x, y coordinates on the map based on image processing methods of the map. To verify the proposed system, we designed three example scenarios based on eyewetinees testimonies and compared time consumption between human and the system. In addition, we evaluate the system usability by 40 subjects.

• BMB Reports
• /
• 제55권9호
• /
• pp.417-428
• /
• 2022

Herbal medicine, a multi-component treatment, has been extensively practiced for treating various symptoms and diseases. However, its molecular mechanism of action on the human body is unknown, which impedes the development and application of herbal medicine. To address this, recent studies are increasingly adopting systems pharmacology, which interprets pharmacological effects of drugs from consequences of the interaction networks that drugs might have. Most conventional network-based approaches collect associations of herb-compound, compound-target, and target-disease from individual databases, respectively, and construct an integrated network of herb-compound-target-disease to study the complex mechanisms underlying herbal treatment. More recently, rapid advances in high-throughput omics technology have led numerous studies to exploring gene expression profiles induced by herbal treatments to elicit information on direct associations between herbs and genes at the genome-wide scale. In this review, we summarize key databases and computational methods utilized in systems pharmacology for studying herbal medicine. We also highlight recent studies that identify modes of action or novel indications of herbal medicine by harnessing drug-induced transcriptome data.

• 대한한의학회지
• /
• 제45권1호
• /
• pp.114-125
• /
• 2024

Objectives: Network pharmacology is an analysis method that explores drug-centered efficacy and mechanism by constructing a compound-target-disease network based on system biology, and is attracting attention as a methodology for studying herbal medicine that has the characteristics for multi-compound therapeutics. Thus, we investigated the potential functions and pathways of Myrrha on Allergic Rhinitis (AR) via network pharmacology analysis and molecular docking. Methods: Using public databases and PubChem database, compounds of Myrrha and their target genes were collected. The putative target genes of Myrrha and known target genes of AR were compared and found the correlation. Then, the network was constructed using STRING database, and functional enrichment analysis was conducted based on the Gene Ontology (GO) Biological process and Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathways. Binding-Docking stimulation was performed using CB-Dock. Results: The result showed that total 3 compounds and 55 related genes were gathered from Myrrha. 33 genes were interacted with AR gene set, suggesting that the effects of Myrrha are closely related to AR. Target genes of Myrrha are considerably associated with various pathways including 'Fc epsilon RI signaling pathway' and 'JAK-STAT signaling pathway'. As a result of blinding docking, AKT1, which is involved in both mechanisms, had high binding energies for abietic acid and dehydroabietic acid, which are components of Myrrha. Conclusion: Through a network pharmacological method, Myrrha was predicted to have high relevance with AR by regulating AKT1. This study could be used as a basis for studying therapeutic effects of Myrrha on AR.

• 대한한의학방제학회지
• /
• 제28권3호
• /
• pp.243-254
• /
• 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.

• Genomics & Informatics
• /
• 제9권4호
• /
• pp.173-180
• /
• 2011

Recent trends in generating multiple, large-scale datasets provide new challenges to manipulating the relationship of different types of components, such as gene expression and drug response data. Integrative analysis of compound response and gene expression datasets generates an opportunity to capture the possible mechanism of compounds by using signature genes on diverse types of cancer cell lines. Here, we integrated datasets of compound response and gene expression profiles on NCI60 cell lines and constructed a network, revealing the relationship for 801 compounds and 341 gene probes. As examples, obtusol, which shows an exclusive sensitivity on a small number of colon cell lines, is related to a set of gene probes that have unique overexpression in colon cell lines. We also found that the SLC7A11 gene, a direct target of miR-26b, might be a key element in understanding the action of many diverse classes of anticancer compounds. We demonstrated that this network might be useful for studying the mechanisms of varied compound response on diverse cancer cell lines.

• 한국컴퓨터정보학회논문지
• /
• 제28권10호
• /
• pp.113-121
• /
• 2023

한의학 및 중의학 분야에서 네트워크 약리학은 계산학적인 방법을 통해 한약의 분자생물학적인 기전을 연구하기 위해 널리 활용된다. 개별 연구를 위해 사용되는 데이터베이스, 분석기법, 분석기준 등은 다양하나, 대부분의 한의학 네트워크 약리학 연구들은 약재-성분 네트워크 구축, 성분-표적 네트워크 구축, 표적의 해석이라는 유사한 단계로 수행된다. 효율적이고 일관성있는 한의학 네트워크 약리학 분석을 위해서, 우리는 일반적으로 적용할 수 있는 한의학 네트워크 분석 파이프라인 시스템을 설계하고 구현하였다. 우리는 이 시스템의 신뢰성을 약재의 네트워크 약리학 분석을 위해 널리 사용되는 데이터베이스를 활용해서 확인하였다. 제안된 시스템은 다양한 한약에 대한 네트워크 약리학적 분석을 용이하게 하고, 일관성 있는 분석을 도울 것이다.

• 대한한의학방제학회지
• /
• 제27권3호
• /
• pp.189-197
• /
• 2019

Objectives : The purpose of this study was to confirm whether Codonopsis Radix(CR) could be used in the same way for expected indications or diseases of adaptation instead of Ginseng Radix(GR), which acts as a principal herb in Sagunja-tang. Methods : The Traditional Chinese Medicine Systems pharmacology(TCMSP), a database for the study of systems biology related to Chinese medicine, screened potential active compounds in each quartet. By searching for all the proteins that each compound provides, the target of Sagunja-tang with GR(GRST) and the target of Sagunja-tang with CR(CRST) were compared using the network analysis method, and the top ranked target of each serving was selected. Results : Through TCMSP, a Chinese medicine database, the potential effective ingredients of GRST or CRST screened, and the target proteins related to these substances were found to be the most affected by Glycyrrhizae Radix et Rhizome, an herbal medicine mixed in Sagunja-tang, and the target diseases were the same. And the same were found for the target protein, gene and target diseases of GRST and CRST. Conclusions : The prescription with similar composition is likely to have similar network pharmacology analysis results, and the analysis result may be controlled by the herbal medicines which are assumed to be the main function. Therefore, rich and reproducible basic studies is more important because network pharmacological studies can be dominated by data that has been done a lot of previous studies.

• 대한한의학방제학회지
• /
• 제31권4호
• /
• pp.245-252
• /
• 2023

Objectives : The purpose of this study was to explore the compounds, targets and related diseases of garlic by the approaches of network pharmacology and bioinformatics in traditional chinese medicine. Methods : We investigated components and their target molecules of garlic using SymMap and TCMSP and they were compared with analysis platform. Results : 56 potential compounds were identified in garlic, 26 of which contained target information, and it was found that these 26 compounds and 154 targets interact with each other through a combination of 243 compounds. In addition, Apigenin was linked to the most targeted gene (78) in 26 compounds, followed by Kaempferol (61 genes), Nicotic Acid (14 genes), Geraniol (11 genes), Eee (10 genes), and Sobrol A (9 genes). Among 56 potential compounds, three compounds (Kaempferol, Dipterocarpol, and N-Methyl cytisine) corresponded to the active compound by screening criterion Absorption, Distribution, Metabolism, Excretion (ADME). In addition, 12 compounds in 56 potential compounds were associated with gastrointestinal (GI) motility disorder. Among them, Kaempferol was a compound that met the ADME parameters and the rest were potential compounds that did not meet. Also, Kaempferol was closely related to GI motility disorder, indicating that this Kaempferol could be a candidate for potential medical efficacy. Conclusions : It shows the relationship between the compound of garlic, an herbal supplement, and the biological process associated with GI motility disorder. These results are thought to help develop strategies for treating GI motility disorders.

• 인지과학
• /
• 제28권4호
• /
• pp.299-314
• /
• 2017

In-silico 기반의 약물-표적 단백질 연관관계 예측은 신약 탐색 단계에서 매우 중요하다. 그러나 기존의 예측모델은 입력 값이 고정적이며 표적 단백질의 특질 값이 가공된 데이터로 한정됨으로써 예측 모델의 확장성과 유연성이 부족하다. 본 논문에서는 약물-표적 단백질 연관관계를 예측하는 확장 가능한 형태의 머신러닝 모델을 소개한다. 확장 가능한 머신러닝 모델의 핵심 아이디어는 쌍기반의 뉴럴 네트워크로써, 약물과 단백질의 미가공 데이터를 사용하여 특질을 추출하고 특질 값을 각각의 뉴럴 네트워크 레이어에 입력한다. 이 방법은 추가적인 지식없이 자동적으로 약물과 단백질의 특질을 추출한다. 또한 쌍기반 레이어는 특질 값을 풍부한 저차원의 벡터로 향상 시킴으로써 입력 값의 차이로 인한 편향 학습을 방지한다. PubChem BioAssay(PCBA) 데이터 셋에 기반한 5-폴드 교차 검증법을 통하여 제안한 모델의 성능을 평가했으며, 이전의 모델보다 우월한 성능을 보였다.