• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.518-518
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• 2000

We have researched quantitative structure activity relationships between molecular structure of medicines and physiological activity. Since they are non-linear, neural networks are useful tool to research them. There are many ranks for the non-linearity; therefore, the neuron function must be selected carefully. As the results of some trial calculations, Ire find the sigmoid-linear functions pair. We call the neural network constructed of the pair as ANN. The inter- or extrapolation abilities of the ANN are excellent; therefere, ANN is a superior predictor for the relationships. We evaluated the anticarcinogenic medicines, Carboquinone derivatives, by the developed ANN and leave-one-out method.

• Food Science and Biotechnology
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• 제17권3호
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• pp.501-507
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• 2008

The quantitative structure-activity relationships (QSAR) study of antioxidative anthocyanidins and their glycosides were evaluated using 4 different assays of Trolox equivalent antioxidant capacity (TEAC), superoxide radical ($O_2^{{\cdot}-}$), hydrogen peroxide ($H_2O_2$), and peroxynitrite radical ($ONOO^-$) scavenging with TSAR software. Four models were developed with significant predictive values ($r^2$ and p value), which indicated that the antioxidant activities were mainly governed by the 3-dimensional structural energy (torsional energy), constitutional properties (the number of hydroxyl and methyl groups), and electrostatic properties (heat of formation, and dipole, quadrupole, and octupole components). This QSAR approach could contribute to a better understanding of structural properties of anthocyanidins and their glycosides that are responsible for their antioxidant activities. It might also be useful in predicting the antioxidant activities of other anthocyanins.

• 농약과학회지
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• 제6권3호
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• pp.166-174
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• 2002

정량적인 분자 구조와 물리-화학적인 성질 사이의 상관관계(QSAR)식을 이용하여 약효성을 예측하고 새로운 농약을 탐색하거나 개발하는데 있어서 효율적인 수단으로 활용되는 QSAR 기법의 발전 과정과 자유 에너지 직선관계(LFER)에 관한 기본 개념을 위시한 QSAR 기법의 목적과 유용성 그리고 장단점과 활용 상 제한점 등에 관한 일반적인 내용에 대하여 간략하게 논의하였다.

• 대한약학회:학술대회논문집
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• 대한약학회 2002년도 Proceedings of the Convention of the Pharmaceutical Society of Korea Vol.2
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• pp.348.2-348.2
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• 2002

The significant antitumor activities of 3-arylisoquinolines promoted us to explore the structure-activity relationship of these compounds. A series of 3-Arylisoquinoline derivatives, which related to Benzo［c］ phenanthridine alkaloids. were evaluated for antitumor cytotoxicity against human lung tumor cell (A 549). We tried to study structure-activity relationship (SAR) of 3-Arylisoquinolines using the comparative molecular field analysis (CoMFA) method. (omitted)

• Molecular & Cellular Toxicology
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• 제4권2호
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• pp.170-176
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• 2008

The quantitative structure-activity relationship (QSAR) of a set of 35 flavonoid compounds presenting antioxidant activity was established by means of Genetic Algorithm-Multiple Linear Regression (GA-MLR) technique. Four-parametric models for two sets of data, the 1,1-diphenyl-2-picryl hydrazyl (DPPH) radical scavenging activity $(R^2=0.788,\;Q^2_{cv}=0.699\;and\;Q^2_{ext}=0.577)$ and scavenging activity of reactive oxgen species (ROS) induced by $H_2O_2 (R^=0.829,\;Q^2_{cv}=0.754\;and\;Q^2_{ext}=0.573)$ were obtained with low external predictive ability on a mass basis, respectively. Each model gave some different mechanistic aspects of the flavonoid compounds tested in terms of the radical scavenging activity. Topological charge, H-bonding complex and deprotonation processes were likely to be involved in the radical scavenging activity.

• Bulletin of the Korean Chemical Society
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• 제27권2호
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• pp.266-272
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• 2006

Three-dimensional quantitative structure-activity relationship (3D-QSAR) models were developed for 67 molecules of 2-amino-benzothiazole-6-anilide derivatives against lymphocyte-specific protein tyrosine kinase (P56 LCK). The molecular field analysis (MFA) and receptor surface analysis (RSA) were employed for QSAR studies and the predictive ability of the model was validated by 15 test set molecules. Structure-based investigations using molecular docking simulation were performed with the crystal structure of P56 LCK. Good correlation between predicted fitness scores versus observed activities was demonstrated. The results suggested that the nature of substitutions at the 2-amino and 6-anilide positions were crucial in enhancing the activity, thereby providing new guidelines for the design of novel P56 LCK inhibitors.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.89.5-89
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• 2002

The technology to predict new chemical compounds by using properties of already known compounds is a kind of data mining and an important technology in chemical industrial fields. Many knowledge have been accumulated in the fields, and especially nowadays in the field of medicine development industry, the technology is connected with the post genome technology, and generates a new conception, physiome. The word is defined as followings. It is the quantitative and integrated description of the functional behavior of the physiological state of an individual or species. The physiome describes the physiological of the normal intact organism and is built on information and structure, that is geno...

• 통합자연과학논문집
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• 제10권3호
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• pp.141-147
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• 2017

Vascular endothelial growth factor (VEGF) is an important signaling protein involved in angiogenesis, which is the formation of new blood vessels from pre-existing vessels. Consequently, blocking of the vascular endothelial growth factor receptor (VEGFR-2) by small molecule inhibitors leads to the inhibition of cancer induced angiogenesis. In this study, we performed a two dimensional quantitative structure activity relationship (2D-QSAR) study of 38 N-Phenyl-N'-{4-(4-quinolyloxy) phenyl} urea derivatives as VEGFR-2 inhibitors based on hologram quantitative structure-activity (HQSAR). The model developed showed reasonable $q^2=0.521$ and $r^2=0.932$ values indicating good predictive ability and reliability. The atomic contribution map analysis of most active compound (compound 7) indicates that hydrogen and oxygen atoms in the side chain of ring A and oxygen atom in side chain of ring C contributes positively to the activity of the compounds. The HQSAR model developed and the atomic contribution map can serve as a guideline in designing new compounds for VEGFR-2 inhibition.

• 대한화장품학회:학술대회논문집
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• 대한화장품학회 2003년도 IFSCC Conference Proceeding Book I
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• pp.225-231
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• 2003

To search and development a new material with superior melanogenesis inhibitory activity, the bioactivities (obs. pl$_{50}$) of alkyl-3,4-dihydroxybenzoyl esters and N-alkyl-3,4-dihydroxybenz-oyl amides as substrate molecules were measured in mouse melanoma cells. And also, we have studied that 3-D QSARs (3 dimensional Quantitative Structure-Activity Relationships) between molecular interaction field of substrates and the bioactivities were analyzed using CoMFA (Comparative Molecular Field Analyses) method. When cross-validation value (q$^2$) is 0.68 at 3 components, the Pearson correlation coefficient ($r^2$) is 0.900. From the basis on the findings, the model was appeared by the contour map such as steric field and electrostatic field relationships between quantitative structure and the bioactivity of the various substrate derivatives. Measured bioactivities (obs. pl$_{50}$) of unknown compounds are very similar to predicted activity (pred. pl$_{50}$) according to the CoMFA model. As the results of prediction, we could conclude that the bioactivities were increased by creation of R$_1$ substitution of 5,5-dime-thylhexoxy, 6,6-dimethylheptyl, 1-amino-6,6-dimethylheptyl group etc and R$_2$ substitution of hydroxy, methyl, methoxy group etc.p etc.

• 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.