• Title/Summary/Keyword: target disease

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In silico target identification of biologically active compounds using an inverse docking simulation

  • Choi, Youngjin
    • CELLMED
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    • v.3 no.2
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    • pp.12.1-12.4
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    • 2013
  • Identification of target protein is an important procedure in the course of drug discovery. Because of complexity, action mechanisms of herbal medicine are rather obscure, unlike small-molecular drugs. Inverse docking simulation is a reverse use of molecular docking involving multiple target searches for known chemical structure. This methodology can be applied in the field of target fishing and toxicity prediction for herbal compounds as well as known drug molecules. The aim of this review is to introduce a series of in silico works for predicting potential drug targets and side-effects based on inverse docking simulations.

Identification of a Potential Anticancer Target of Danshensu by Inverse Docking

  • Chen, Shao-Jun;Ren, Ji-Long
    • Asian Pacific Journal of Cancer Prevention
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    • v.15 no.1
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    • pp.111-116
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    • 2014
  • Objective: To study potential targets of Danshensu via dual inverse docking. Method: PharmMapper and idTarget servers were used as tools, and the results were checked with the molecular docking program autodock vina in PyRx 0.8. Result: The disease-related target HRas was rated top, with a pharmacophore model matching well the molecular features of Danshensu. In addition, docking results indicated that the complex was also matched in terms of structure, H-bonds, and hydrophobicity. Conclusion: Dual inverse docking indicates that HRas may be a potential anticancer target of Danshensu. This approach can provide useful information for studying pharmacological effects of agents of interest.

A Novel Automatic Algorithm for Selecting a Target Brain using a Simple Structure Analysis in Talairach Coordinate System

  • Koo B.B.;Lee Jong-Min;Kim June Sic;Kim In Young;Kim Sun I.
    • Journal of Biomedical Engineering Research
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    • v.26 no.3
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    • pp.129-132
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    • 2005
  • It is one of the most important issues to determine a target brain image that gives a common coordinate system for a constructing population-based brain atlas. The purpose of this study is to provide a simple and reliable procedure that determines the target brain image among the group based on the inherent structural information of three-dimensional magnetic resonance (MR) images. It uses only 11 lines defined automatically as a feature vector representing structural variations based on the Talairach coordinate system. Average characteristic vector of the group and the difference vectors of each one from the average vector were obtained. Finally, the individual data that had the minimum difference vector was determined as the target. We determined the target brain image by both our algorithm and conventional visual inspection for 20 healthy young volunteers. Eighteen fiducial points were marked independently for each data to evaluate the similarity. Target brain image obtained by our algorithm showed the best result, and the visual inspection determined the second one. We concluded that our method could be used to determine an appropriate target brain image in constructing brain atlases such as disease-specific ones.

Analysis of the Active Compounds and Therapeutic Mechanisms of Yijin-tang on Meniere's Disease Using Network Pharmacology(I) (네트워크 약리학을 활용한 메니에르병에 대한 이진탕(二陳湯)의 활성 성분과 치료 기전 연구(I))

  • SunKyung Jin;Hae-Jeong Nam
    • The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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    • v.36 no.1
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    • pp.50-63
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    • 2023
  • Objectives : This study used a network pharmacology approach to explore the active compounds and therapeutic mechanisms of Yijin-tang on Meniere's disease. Methods : The active compounds of Yijin-tang were screened via the TCMSP database and their target proteins were screened via the STITCH database. The GeneCard was used to establish the Meniere's disease-related genes. The intersection targets were obtained through Venny 2.1.0. The related protein interaction network was constructed with the STRING database, and topology analysis was performed through CytoNCA. GO biological function analysis and KEGG enrichment analysis for core targets were performed through the ClueGO. Results : Network analysis identified 126 compounds in five herbal medicines of Yijin-tang. Among them, 15 compounds(naringenin, beta-sitosterol, stigmasterol, baicalein, baicalin, calycosin, dihydrocapsaicin, formononetin, glabridin, isorhamnetin, kaempferol, mairin, quercetin, sitosterol, nobiletin) were the key chemicals. The target proteins were 119, and 7 proteins(TNF, CASP9, PARP1, CCL2, CFTR, NOS2, NOS1) were linked to Meniere's disease-related genes. Core genes in this network were TNF, CASP9, and NOS2. GO/KEGG pathway analysis results indicate that these targets are primarily involved in regulating biological processes, such as excitotoxicity, oxidative stress, and apoptosis. Conclusion : Pharmacological network analysis can help to explain the applicability of Yijin-tang on Meniere's disease.

EVALUATION OF DIAGNOSTIC TESTS WITH MULTIPLE DIAGNOSTIC CATEGORIES

  • Birkett N.J.
    • 대한예방의학회:학술대회논문집
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    • 1994.02b
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    • pp.154-157
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    • 1994
  • The evaluation of diagnostic tests attempts to obtain one or more statistical parameters which can indicate the intrinsic diagnostic utility of a test. Sensitivity. specificity and predictive value are not appropriate for this use. The likelihood ratio has been proposed as a useful measure when using a test to diagnose one of two disease states (e.g. disease present or absent). In this paper, we generalize the likelihood ratio concept to a situation in which the goal is to diagnose one of several non-overlapping disease states. A formula is derived to determine the post-test probability of a specific disease state. The post-test odds are shown to be related to the pre-test odds of a disease and to the usual likelihood ratios derived from considering the diagnosis between the target diagnosis and each alternate in turn. Hence, likelihood ratios derived from comparing pairs of diseases can be used to determine test utility in a multiple disease diagnostic situation.

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Brain Hypoxia Imaging (뇌 저산소증 영상)

  • Song, Ho-Chun
    • Nuclear Medicine and Molecular Imaging
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    • v.41 no.2
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    • pp.91-96
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    • 2007
  • The measurement of pathologically low levels of tissue $pO_2$ is an important diagnostic goal for determining the prognosis of many clinically important diseases including cardiovascular insufficiency, stroke and cancer. The target tissues nowaday have mostly been tumors or the myocardium, with less attention centered on the brain. Radiolabelled nitroimidazole or derivatives may be useful in identifying the hypoxic cells in cerebrovascular disease or traumatic brain injury, and hypoxic-ischemic encephalopathy. In acute stroke, the target of therapy is the severely hypoxic but salvageable tissue. $^{18}F-MISO$ PET and $^{99}mTc-EC-metronidazole$ SPECT in patients with acute ischemic stroke identified hypoxic tissues and ischemic penumbra, and predicted its outcome. A study using $^{123}I-IAZA$ in patient with closed head injury detected the hypoxic tissues after head injury. Up till now these radiopharmaceuticals have drawbacks due to its relatively low concentration with hypoxic tissues associated with/without low blood-brain barrier permeability and the necessity to wait a long time to achieve acceptable target to background ratios for imaging in acute ischemic stroke. It is needed to develop new hypoxic marker exhibiting more rapid localization in the hypoxic region in the brain. And then, the hypoxic brain imaging with imidazoles or non-imidazoles may be very useful in detecting the hypoxic tissues, determining therapeutic strategies and developing therapeutic drugs in several neurological disease, especially, in acute ischemic stroke.

Systems pharmacology approaches in herbal medicine research: a brief review

  • Lee, Myunggyo;Shin, Hyejin;Park, Musun;Kim, Aeyung;Cha, Seongwon;Lee, Haeseung
    • BMB Reports
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    • v.55 no.9
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    • pp.417-428
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    • 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.

AMP-activated protein kinase: An emerging target for ginseng

  • Jeong, Kyong Ju;Kim, Go Woon;Chung, Sung Hyun
    • Journal of Ginseng Research
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    • v.38 no.2
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    • pp.83-88
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    • 2014
  • The adenosine monophosphate (AMP)-activated protein kinase (AMPK) is a key sensor of cellular energy. Once activated, it switches on catabolic pathways generating adenosine triphosphate (ATP), while switching off biosynthetic pathways consuming ATP. Pharmacological activation of AMPK by metformin holds a therapeutic potential to reverse metabolic abnormalities such as type 2 diabetes and nonalcoholic fatty liver disease. In addition, altered metabolism of tumor cells is widely recognized and AMPK is a potential target for cancer prevention and/or treatment. Panax ginseng is known to be useful for treatment and/or prevention of cancer and metabolic diseases including diabetes, hyperlipidemia, and obesity. In this review, we discuss the ginseng extracts and ginsenosides that activate AMPK, we clarify the various mechanisms by which they achieve this, and we discuss the evidence that shows that ginseng or ginsenosides might be useful in the treatment and/or prevention of metabolic diseases and cancer.

Isolation of 6,6'-Bieckol from Grateloupia elliptica and its Antioxidative and Anti-Cholinesterase Activity

  • Lee, Bong Ho;Choi, Byoung Wook;Lee, Soo Young
    • Ocean and Polar Research
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    • v.39 no.1
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    • pp.45-49
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    • 2017
  • During the search for anticholinesterase compounds from marine organisms, we were able to isolate 6,6'-bieckol from a red alga, Grateloupia elliptica. This compound showed moderate acetylcholinesterase (AChE) inhibitory activity in a micromole range ($IC_{50}$ $44.5{\mu}M$). However, for butyrylcholinesterase (BuChE), a new target for the treatment of Alzheimer's disease (AD), it showed particularly potent inhibitory activity ($IC_{50}$ $27.4{\mu}M$), which is more potent compared to AChE. It also inhibits BACE-1, a new target for reducing the generation of ${\beta}-amyloid$.

Applications of NMR spectroscopy based metabolomics: a review

  • Yoon, Dahye;Lee, Minji;Kim, Siwon;Kim, Suhkmann
    • Journal of the Korean Magnetic Resonance Society
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    • v.17 no.1
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    • pp.1-10
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    • 2013
  • Metabolomics is the study which detects the changes of metabolites level. Metabolomics is a terminal view of the biological system. The end products of the metabolism, metabolites, reflect the responses to external environment. Therefore metabolomics gives the additional information about understanding the metabolic pathways. These metabolites can be used as biomarkers that indicate the disease or external stresses such as exposure to toxicant. Many kinds of biological samples are used in metabolomics, for example, cell, tissue, and bio fluids. NMR spectroscopy is one of the tools of metabolomics. NMR data are analyzed by multivariate statistical analysis and target profiling technique. Recently, NMR-based metabolomics is a growing field in various studies such as disease diagnosis, forensic science, and toxicity assessment.