Choi J.,Bioinformatics and Molecular Design Research Center |
Ma S.L.,Yonsei University |
Kim H.-Y.,Yonsei University |
Yun J.-H.,Yonsei University |
And 4 more authors.
Bioorganic and Medicinal Chemistry | Year: 2016
The Dishevelled (Dvl) protein, which conveys signals from receptors to the downstream effectors, is a critical constituent of the Wnt/β-catenin signaling pathway. Because the PDZ domain of Dvl protein functions through associations with a wide range of protein partners, Dvl protein involved in the Wnt signaling pathway has been considered to be therapeutic targets in cancers. In this study, we performed structure-based pharmacophore model of the Dvl PDZ domain to discover novel small-molecule binders and identified eight compounds with micromolar affinity. The most potent compound identified, BMD4702, efficiently bound to the Dvl PDZ domain with 11.2. μM affinity and had a 0.186. μM KD value according to surface plasmon resonance and fluorescence spectroscopy, respectively. Combining both structural-kinetic relationship analyses and docking studies, we fourmulated that the ligand-binding site is composed of three H-bonds and three hydrophobic features. Thus, our approach led to the identification of potent binders of the Dvl PDZ domain and the findings provide novel insights into structure-based approaches to design high-affinity binders for the Dvl PDZ domain. © 2016 Elsevier Ltd.
Yim W.C.,Dongguk University |
Keum C.,Bioinformatics and Molecular Design Research Center |
Kim S.,Macrogen |
Cho Y.,Dongguk University |
And 2 more authors.
Toxicology and Environmental Health Sciences | Year: 2010
17β-estradiol (E2) is an environmental estrogen-like chemicals that is known to affect mainly reproductive functions of exposed targets. Although microarray based toxicogenomics approach allows the investigation of the potential risks of E2 in DNA level, the underling mechanisms related to their toxic effect is not fully understood. In this work, we identified genes responding toE2 by analyzing cross-experiment public gene expression datasets that studied on E2 using RankProd algorithm. We have identified 348 DEGs which play important roles in fatty acid metabolism, infection, and DNA repair. This result was also compared with conventional PubMed data mining analysis. © 2010 The Korean Society of Environmental Risk Assessment and Health Science and Springer.
Lee E.,Konkuk University |
Jeong K.-W.,Konkuk University |
Shin A.,Konkuk University |
Jin B.,Konkuk University |
And 5 more authors.
BMB Reports | Year: 2013
The anti-inflammatory activity of eriodictyol and its mode of action were investigated. Eriodictyol suppressed tumor necrosis factor (mTNF)-α, inducible nitric oxide synthase (miNOS), interleukin (mIL)-6, macrophage inflammatory protein (mMIP)-1, and mMIP-2 cytokine release in LPS-stimulated macrophages. We found that the anti-inflammatory cascade of eriodictyol is mediated through the Toll-like Receptor (TLR)4/CD14, p38 mitogen-activated protein kinases (MAPK), extracellular-signalregulated kinase (ERK), Jun-N terminal kinase (JNK), and cyclooxygenase (COX)-2 pathway. Fluorescence quenching and saturation-transfer difference (STD) NMR experiments showed that eriodictyol exhibits good binding affinity to JNK, 8.79 × 105 M-1. Based on a docking study, we propose a model of eriodictyol and JNK binding, in which eriodictyol forms 3 hydrogen bonds with the side chains of Lys55, Met111, and Asp169 in JNK, and in which the hydroxyl groups of the B ring play key roles in binding interactions with JNK. Therefore, eriodictyol may be a potent anti-inflammatory inhibitor of JNK. © 2013 by the The Korean Society for Biochemistry and Molecular Biology.
Shim H.J.,Yonsei University |
Yang H.R.,Sungkyunkwan University |
Kim H.I.,Yonsei University |
Kim H.I.,Shingyeong University |
And 5 more authors.
Bioorganic and Medicinal Chemistry Letters | Year: 2014
A lead compound 1, which inhibits the catalytic activity of PTK6, was selected from a chemical library. Derivatives of compound 1 were synthesized and analyzed for inhibitory activity against PTK6 in vitro and at the cellular level. Selected compounds were analyzed for cytotoxicity in human foreskin fibroblasts using MTT assays and for selectivity towards PTK members in HEK 293 cells. Compounds 20 (in vitro IC50= 0.12 μM) and 21 (in vitro IC50= 0.52 μM) showed little cytotoxicity, excellent inhibition of PTK6 in vitro and at the cellular level, and selectivity for PTK6. Compounds 20 and 21 inhibited phosphorylation of specific PTK6 substrates in HEK293 cells. Thus, we have identified novel PTK6 inhibitors that may be used as treatments for PTK6-positive carcinomas, including breast cancer. © 2014 Elsevier Ltd. All rights reserved.
In Y.,Bioinformatics and Molecular Design Research Center |
Lee S.K.,Hannam University |
Kim P.J.,National Institute of Environmental Research |
No K.T.,Bioinformatics and Molecular Design Research Center |
No K.T.,Yonsei University
Bulletin of the Korean Chemical Society | Year: 2012
We applied several machine learning methods for developing QSAR models for prediction of acute toxicity to fathead minnow. The multiple linear regression (MLR) and artificial neural network (ANN) method were applied to predict 96 h LC 50 (median lethal concentration) of 555 chemical compounds. Molecular descriptors based on 2D chemical structure were calculated by PreADMET program. The recursive partitioning (RP) model was used for grouping of mode of actions as reactive or narcosis, followed by MLR method of chemicals within the same mode of action. The MLR, ANN, and two RP-MLR models possessed correlation coefficients (R 2) as 0.553, 0.618, 0.632, and 0.605 on test set, respectively. The consensus model of ANN and two RP-MLR models was used as the best model on training set and showed good predictivity (R 2=0.663) on the test set.