• Bulletin of the Korean Chemical Society
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• 제30권11호
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• pp.2717-2722
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• 2009

The use of the classification and regression tree (CART) methodology was studied in a quantitative structure-activity relationship (QSAR) context on a data set consisting of the binding affinities of 39 imidazobenzodiazepines for the α1 benzodiazepine receptor. The 3-D structures of these compounds were optimized using HyperChem software with semiempirical AM1 optimization method. After optimization a set of 1481 zero-to three-dimentional descriptors was calculated for each molecule in the data set. The response (dependent variable) in the tree model consisted of the binding affinities of drugs. Three descriptors (two topological and one 3D-Morse descriptors) were applied in the final tree structure to describe the binding affinities. The mean relative error percent for the data set is 3.20%, compared with a previous model with mean relative error percent of 6.63%. To evaluate the predictive power of CART cross validation method was also performed.

• 한국진공학회:학술대회논문집
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• 한국진공학회 2009년도 제38회 동계학술대회 초록집
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• pp.34-34
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• 2010

Activities of various $TiO_2$ nanostructures in photocatalytic decomposition of methylene blue and toluene were determined in order to shed light on the relationship between structures and photocatalytic activity. Commercially available P-25 samples were used in the present work. In addition, $TiO_2$ nanostructures were synthesized using atomic layer deposition (ALD). We show that change in the surface structure of $TiO_2$ upon variois surface treatments results in variation in photocatalytic activity. In particular, increase in the number of OH groups on the surface leads to the enhancement in photocatalytc activity. Surface OH groups increases adsorption reactivity of organic reactants, thereby increasing activity in photocatalytic decomposition of methylene blue and toluene.

• 한국전기전자재료학회논문지
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• 제24권1호
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• pp.81-88
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• 2011

A real time monitoring system from a PC has been developed which can be accessed through transmitted data, which incorporates an established low powered transport system equipped with a single chip combined with wireless sensor network technology from a three-axis acceleration sensor. In order to distinguish between static posture and dynamic posture, the extracted parameter from the rapidly transmitted data needs differentiation of movement and activity structures and status for an accurate measurement. When results interpret a static formation, statistics referring to each respective formation, known as the K-mean algorithm is utilized to carry out a determination of detailed positioning, and when results alter towards dynamic activity, fuzzy algorithm (fuzzy categorizer), which is the relationship between speed and ISVM, is used to categorize activity levels into 4 stages. Also, the ISVM is calculated with the instrumented acceleration speed on the running machine according to various speeds and its relationship with kinetic energy goes through correlation analysis. With the evaluation of the proposed system, the accuracy level stands at 100% at a static formation and also a 96.79% accuracy with kinetic energy and we can easily determine the energy consumption through the relationship between ISVM and kinetic energy.

• 통합자연과학논문집
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• 제4권3호
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• pp.210-215
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• 2011

Holographic quantitative structure-activity relationships (HQSAR) is a useful tool to correlates structures with their biological activities. HQSAR is a two dimensional (2D) QSAR methodology, which generates QSAR equations through 2D fingerprint and correlates it with biological activity. Here, we report a 2D-QSAR model for a series of fifty-one 3,4-dihydroxychalcones derivatives utilizing HQSAR methodology. We developed HQSAR model with 6 optimum numbers of components (ONC), which resulted in cross-validated correlation coefficient ($q^2$) of 0.855 with 0.283 standard error of estimate (SEE). The non-cross-validated correlation coefficient (r2) with 0.966 indicates the model is predictive enough for analysis. Developed HQSAR model was binned in to a hologram length of 257. Atomic contribution map revealed the importance of dihydroxy substitution on phenyl ring.

• 한국생물물리학회:학술대회논문집
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• 한국생물물리학회 1999년도 학술발표회 진행표 및 논문초록
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• pp.33-33
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• 1999

Mastoparan B (MP-B), an antimicrobial cationic tetradecapeptide amide isolated from the venom of the hornet Vespa basalis, is an amphiphilic ${\alpha}$-helical peptide. In order to study the relationship between the structure and biological activity, we used the three analogues by replacing amino acids with alanine (4LysAla： 4MP-B, 12-LYsAla: 12MP-B, 9TrpAla: 9Mp-B).(omitted)

• 한국응용약물학회:학술대회논문집
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• 한국응용약물학회 1998년도 Proceedings of UNESCO-internetwork Cooperative Regional Seminar and Workshop on Bioassay Guided Isolation of Bioactive Substances from Natural Products and Microbial Products
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• pp.126-126
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• 1998

Studies on natural products are of great interest, due to the limits in development of synthesized medicine and its side effects. Deer antler is the most popular cure-all type drug among Asian folk medicines. In this study, we newly isolated the biologically active components from chloroform extract and 70% ethanol extract of deer antler, and analyzed their structures. First, the structure of monoacetyldiglyceride in deer antler was identified. To investigate the structure-activity relationship of monoacetyldiglycerides, we synthesized diverse substituted glycerides from glycerol, and confirmed their structures by spectroscopic methods. Among seven structurally-interesting compounds tested in this study, compound 1,2,3,5, and 6 showed activity toward [Ca$\^$2+/]$\_$i/ increase in fura-2 loaded rat pancreatic acinar cells. Second, 70% ethanol extract of deer antler stimulated insulin release from rat pancreatic islets. We found the most effective fraction was CN-Es-8 in 70% ethanol extract, and it increased intracellular Ca$\^$2+/ concentration in pancreatic ${\beta}$-cell.

• Journal of Microbiology and Biotechnology
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• 제28권8호
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• pp.1299-1309
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• 2018

We previously reported on lactophoricin (LPcin), a cationic ${\alpha}-helical$ antimicrobial peptide derived from bovine milk, which has antimicrobial effects on Candida albicans as well as Gram-positive and Gram-negative bacteria. In this study, we designed the LPcin-YK3 peptide, a shorter analog of LPcin, and investigated its antimicrobial activity. This peptide, consisting of 15 amino acids with + 3 net charges, was an effective antimicrobial agent against the on the Gram-positive strain, Staphylococcus aureus (MIC: $0.62{\mu}g/ml$). In addition, the hemolytic activity assay revealed that the peptide was not toxic to mouse and human erythrocytes up to $40{\mu}g/ml$. We also used circular dichroism spectroscopy to confirm that peptide in the presence of lipid has ${\alpha}-helical$ structures and later provide an overview of the relationship between each structure and antimicrobial activity. This peptide is a member of a new class of antimicrobial agents that could potentially overcome the problem of bacterial resistance caused by overuse of conventional antibiotics. Therefore, it could be used as a therapeutic or natural additive, particularly in the cosmetics industry.

• Journal of Microbiology and Biotechnology
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• 제9권4호
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• pp.414-421
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• 1999

Helicobacter pylori were found to be resistant to azide but sensitive to vanadate, suggesting that defect in the P-type ATPase activity rather than F-type ATPase would be lethal to cell survival or growth. To elucidate the relationship between this enzyme inhibition and H. pylori death, we determined the effect of omeprazole (OMP) plus vanadate on enzyme activity and cell growth. The minimum inhibitory concentration (MIC; ca. 0.8$\mu$mol/disk) of vanadate for H. pylori growth was lowered over l0-fold with the aid of OMP, whereby its inhibitory potential toward the P-type ATPase activity was diametrically increased. Alternatively, we found that this enzyme activity was essential for active transport in H. pylori. From these observations, we strongly suggest that the immediate cause of the growth inhibition of H. pylori cells with OMP and/or vanadate might be defective in the cell's active transport due to the lack of P-type ATPase activity. From the spectral data with circular dichroism (CD) spectroscopy, we found that activated OMP (OAS) at concentration below MIC did not disrupt helical structures of membrane proteins. Separately, we determined the cytopathic effect of OAS by SDS-PAGE, indicating the change in the production of cytoplasmic protein but not cell membrane.

• ALGAE
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• 제38권4호
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• pp.217-240
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• 2023

Sulfated polysaccharides (SPs) isolated from seaweed have emerged as remarkable bioactive compounds with a wide spectrum of biological activities and have substantial value in the scientific and industrial domains. The current study explores the diverse biological activities of SPs and their relationship with their structures. This aids in an in-depth examination of the multifaceted biological activities of SPs, including anticoagulant, anti-inflammatory, antiviral, antioxidant, and immunomodulatory properties, which underpin their potential health benefits. Furthermore, the current study explores the complicated properties of SPs, with their extraction methodologies and techniques for precise characterization. Elucidation of the commercial significance of SPs derived from brown, red, and green seaweed by highlighting their potential applications has emphasized their importance in human well-being. Further, this review emphasizes the challenges needed to overcome research and industrial innovations for SPs. Collaboration among researchers, industry stakeholders, and regulatory authorities can overcome these challenges and elevate the potential of SPs to revolutionize industries such as pharmaceuticals, cosmeceuticals, food, and biotechnology.

• Bulletin of the Korean Chemical Society
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• 제26권1호
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• pp.139-145
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• 2005

Artificial neural networks (ANNs), for a first time, were successfully developed for the modeling and prediction of solvent effects on rate constant of [2+2] cycloaddition reaction of diethyl azodicarboxylate with ethyl vinyl ether in various solvents with diverse chemical structures using quantitative structure-activity relationship. The most positive charge of hydrogen atom (q$^+$), dipole moment ($\mu$), the Hildebrand solubility parameter (${\delta}_H^2$) and total charges in molecule (q$_t$) are inputs and output of ANN is log k$_2$ . For evaluation of the predictive power of the generated ANN, the optimized network with 68 various solvents as training set was used to predict log k$_2$ of the reaction in 16 solvents in the prediction set. The results obtained using ANN was compared with the experimental values as well as with those obtained using multi-parameter linear regression (MLR) model and showed superiority of the ANN model over the regression model. Mean square error (MSE) of 0.0806 for the prediction set by MLR model should be compared with the value of 0.0275 for ANN model. These improvements are due to the fact that the reaction rate constant shows non-linear correlations with the descriptors.