• BMB Reports
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• v.50 no.2
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• pp.58-59
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• 2017

The beneficial paracrine roles of mesenchymal stem cells (MSCs) in tissue repair have potential in therapeutic strategies against various diseases. However, the key therapeutic factors secreted from MSCs and their exact molecular mechanisms of action remain unclear. In this study, the cell-free secretome of umbilical cord-derived MSCs showed significant anti-fibrotic activity in the mouse models of liver fibrosis. The involved action mechanism was the regulation of hepatic stellate cell activation by direct inhibition of the $TGF{\beta}$/Smad-signaling. Antagonizing the milk fat globule-EGF factor 8 (MFGE8) activity blocked the anti-fibrotic effects of the MSC secretome in vitro and in vivo. Moreover, MFGE8 was secreted by MSCs from the umbilical cord as well as other tissues, including teeth and bone marrow. Administration of recombinant MFGE8 protein alone had a significant anti-fibrotic effect in two different models of liver fibrosis. Additionally, MFGE8 downregulated $TGF{\beta}$ type I receptor expression by binding to ${\alpha}v{\beta}3$ integrin on HSCs. These findings revealed the potential role of MFGE8 in modulating $TGF{\beta}$-signaling. Thus, MFGE8 could serve as a novel therapeutic agent for liver fibrosis.

• The Korean Journal of Physiology and Pharmacology
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• v.13 no.6
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• pp.511-516
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• 2009

A series of substituted 2-arylnaphthyridin-4-one analogues, which were previously synthesized in our laboratory, were evaluated for their in vitro cytotoxic activity against human lung cancer A549 and human renal cancer Caki-2 cells using MTT assay. Some compounds (11, 12, and 13) showed stronger cytotoxicity than colchicine against both tumor cell lines, and compound 13 exhibited the most potent activity with $IC_{50}$ values of 2.3 and $13.4\;{\mu}M$, respectively. Three-dimensional quantitative structure activity relationship (3D-QSAR) studies of comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed. Predictive 3D-QSAR models were obtained with $q^2$ values of 0.869 and 0.872 and $r^2_{ncv}$ values of 0.983 and 0.993 for CoMFA and CoMSIA, respectively. These results demonstrate that CoMFA and CoMSIA models could be reliably used in the design of novel cytotoxic agents.

• Korean Journal of Materials Research
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• v.20 no.9
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• pp.478-482
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• 2010

A series of molecular dynamic (MD), finite element (FE) and ab initio simulations are carried out to establish suitable modeling schemes for the continuum-based analysis of aluminum matrix nanocomposites reinforced with carbon nanotubes (CNTs). From a comparison of the MD with FE models and inferences based on bond structures and electron distributions, we propose that the effective thickness of a CNT wall for its continuum representation should be related to the graphitic inter-planar spacing of 3.4${\AA}$. We also show that shell element representation of a CNT structure in the FE models properly simulated the carbon-carbon covalent bonding and long-range interactions in terms of the load-displacement behaviors. Estimation of the effective interfacial elastic properties by ab initio simulations showed that the in-plane interfacial bond strength is negligibly weaker than the normal counterpart due to the nature of the weak secondary bonding at the CNT-Al interface. Therefore, we suggest that a third-phase solid element representation of the CNT-Al interface in nanocomposites is not physically meaningful and that spring or bar element representation of the weak interfacial bonding would be more appropriate as in the cases of polymer matrix counterparts. The possibility of treating the interface as a simply contacted phase boundary is also discussed.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2004.11a
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• pp.210-218
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• 2004

Poly(ADP-ribose)polymerase-1 (PARP-1) is a nuclear enzyme involved in various physical functions related to genomic repair, and PARP inhibitors have therapeutic application in a variety of neurological diseases. Docking and the QSAR (quantitative structure-activity relationships) studies for 52 PARP-1 inhibitors were conducted using FlexX algorithm, comparative molecular field analysis (CoMFA), and hologram quantitative structure-activity relationship analysis (HQSAR). The resultant FlexX model showed a reasonable correlation (r$^{2}$ = 0.701) between predicted activity and observed activity. Partial least squares analysis produced statistically significant models with q$^{2}$ values of 0.795 (SDEP=0.690, r$^{2}$=0.940, s=0.367) and 0.796 (SDEP=0.678, r$^{2}$ = 0.919, s=0.427) for CoMFA and HQSAR, respectively. The models for the entire inhibitor set were validated by prediction test and scrambling in both QSAR methods. In this work, combination of docking, CoMFA with 3D descriptors and HQSAR based on molecular fragments provided an improved understanding in the interaction between the inhibitors and the PARP. This can be utilized for virtual screening to design novel PARP-1 inhibitors.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.45-48
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• 1999

Model predictive control algorithm requires a relevant model of the system to be controlled. Unfortunately, the first principle model describing a polymerization reaction system has a large number of parameters to be estimated. Thus there is a need for the identification and control of a polymerization reactor system by using available input-output data. In this work, the polynomial auto-regressive moving average (ARMA) models are employed as the input-output model and combined into the nonlinear model predictive control algorithm based on the successive linearization method. Simulations are conducted to identify the continuous styrene polymerization reactor system. The input variables are the jacket inlet temperature and the feed flow rate whereas the output variables are the monomer conversion and the weight-average molecular weight. The polynomial ARMA models obtained by the system identification are used to control the monomer conversion and the weight-average molecular weight in a continuous styrene polymerization reactor It is demonstrated that the nonlinear model predictive controller based on the polynomial ARMA model tracks the step changes in the setpoint satisfactorily. In conclusion, the polynomial ARMA model is proven effective in controlling the continuous styrene polymerization reactor.

• YAKHAK HOEJI
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• v.55 no.2
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• pp.98-105
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• 2011

To search the minimum structural requirement of tricyclic isoxazole analogues (1~30) as new class potent antidepressant, thee-dimensional quanti- tative-structure relationship (3D-QSAR) models between substituents ($R_1{\sim}R_5$) of tricyclic isoxazoles and their antidepressant activity against medetomidine-induced loss of righting were performed and discussed quantitatively using comparative molecular field analysis (CoMFA) and comparative molecular similarity indies analysis (CoMSIA) methods. The correlativity and predictability ($r^2$=0.484 and $q^2$=0.947) of CoMSIA-2 model were higher than those of the rest models. The inhibitory activity against medetomidine-induced loss of righting was dependent on electrostatic field (43.4%), hydrophobic field (35.3%), and steric field (21.2%) of tricyclic isoxazoles. From the CoMSIA-2 contour maps, it is predicted that the antidepressant activity of potent antidepressants against medetomidine-induced loss of righting will be able to increase by the substituents ($R_1{\sim}R_5$) which were in accord with CoMSIA field.

• International Journal of Control, Automation, and Systems
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• v.4 no.3
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• pp.382-393
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• 2006

Mechanical system dynamics plays an important role in the area of computational structural biology. Elastic network models (ENMs) for macromolecules (e.g., polymers, proteins, and nucleic acids such as DNA and RNA) have been developed to understand the relationship between their structure and biological function. For example. a protein, which is basically a folded polypeptide chain, can be simply modeled as a mass-spring system from the mechanical viewpoint. Since the conformational flexibility of a protein is dominantly subject to its chemical bond interactions (e.g., covalent bonds, salt bridges, and hydrogen bonds), these constraints can be modeled as linear spring connections between spatially proximal representatives in a variety of coarse-grained ENMs. Coarse-graining approaches enable one to simulate harmonic and anharmonic motions of large macromolecules in a PC, while all-atom based molecular dynamics (MD) simulation has been conventionally performed with an aid of supercomputer. A harmonic analysis of a macroscopic mechanical system, called normal mode analysis, has been adopted to analyze thermal fluctuations of a microscopic biological system around its equilibrium state. Furthermore, a structure-based system optimization, called elastic network interpolation, has been developed to predict nonlinear transition (or folding) pathways between two different functional states of a same macromolecule. The good agreement of simulation and experiment allows the employment of coarse-grained ENMs as a versatile tool for the study of macromolecular dynamics.

• Journal of Preventive Medicine and Public Health
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• v.42 no.6
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• pp.371-376
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• 2009

In this article, we reviewed the literature on risk assessment (RA) models with and without molecular genomic markers and the current utility of the markers in the pharmacogenetic field. Epidemiological risk assessment is applied using statistical models and equations established from current scientific knowledge of risk and disease. Several papers have reported that traditional RA tools have significant limitations in decision-making in management strategies for individuals as predictions of diseases and disease progression are inaccurate. Recently, the model added information on the genetic susceptibility factors that are expected to be most responsible for differences in individual risk. On the continuum of health care, from diagnosis to treatment, pharmacogenetics has been developed based on the accumulated knowledge of human genomic variation involving drug distribution and metabolism and the target of action, which has the potential to facilitate personalized medicine that can avoid therapeutic failure and serious side effects. There are many challenges for the applicability of genomic information in a clinical setting. Current uses of genetic markers for managing drug therapy and issues in the development of a valid biomarker in pharmacogenetics are discussed.

• The Korean Journal of Physiology and Pharmacology
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• v.23 no.1
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• pp.1-20
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• 2019

Neuropathic pain is a complex chronic pain state caused by the dysfunction of somatosensory nervous system, and it affects the millions of people worldwide. At present, there are very few medical treatments available for neuropathic pain management and the intolerable side effects of medications may further worsen the symptoms. Despite the presence of profound knowledge that delineates the pathophysiology and mechanisms leading to neuropathic pain, the unmet clinical needs demand more research in this field that would ultimately assist to ameliorate the pain conditions. Efforts are being made globally to explore and understand the basic molecular mechanisms responsible for somatosensory dysfunction in preclinical pain models. The present review highlights some of the novel molecular targets like D-amino acid oxidase, endoplasmic reticulum stress receptors, sigma receptors, hyperpolarization-activated cyclic nucleotide-gated cation channels, histone deacetylase, $Wnt/{\beta}-catenin$ and Wnt/Ryk, ephrins and Eph receptor tyrosine kinase, Cdh-1 and mitochondrial ATPase that are implicated in the induction of neuropathic pain. Studies conducted on the different animal models and observed results have been summarized with an aim to facilitate the efforts made in the drug discovery. The diligent analysis and exploitation of these targets may help in the identification of some promising therapies that can better manage neuropathic pain and improve the health of patients.

• Molecules and Cells
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• v.44 no.12
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• pp.861-878
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• 2021

The human genome contains many retroviral elements called human endogenous retroviruses (HERVs), resulting from the integration of retroviruses throughout evolution. HERVs once were considered inactive junk because they are not replication-competent, primarily localized in the heterochromatin, and silenced by methylation. But HERVs are now clearly shown to actively regulate gene expression in various physiological and pathological conditions such as developmental processes, immune regulation, cancers, autoimmune diseases, and neurological disorders. Recent studies report that HERVs are activated in patients suffering from coronavirus disease 2019 (COVID-19), the current pandemic caused by SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) infection. In this review, we describe internal and external factors that influence HERV activities. We also present evidence showing the gene regulatory activity of HERV LTRs (long terminal repeats) in model organisms such as mice, rats, zebrafish, and invertebrate models of worms and flies. Finally, we discuss several molecular and cellular pathways involving various transcription factors and receptors, through which HERVs affect downstream cellular and physiological events such as epigenetic modifications, calcium influx, protein phosphorylation, and cytokine release. Understanding how HERVs participate in various physiological and pathological processes will help develop a strategy to generate effective therapeutic approaches targeting HERVs.