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김석현,황병곤,여지환 大邱大學校 科學技術硏究所 1996 科學技術硏究 Vol.3 No.1
In thia paper , we have approached to the recognition system from assuming that two systems, time-frequency and nonlinear-dynamic pattem have different recognition range respectively. We showed that the performance of the Model connected MLP and HCNN is better than that of HMM itself. We examined HMM and HCNN under the similar conditions. The results turn out that MLP and HMM itself only show us a little change. So, we can conclude that the sysytem connected MLP and HCNN is more suit-able for speaker independent speech recognition tasks.
Pharmacophore Identification for Peroxisome Proliferator-Activated Receptor Gamma Agonists
손영식,이윤호,Chanin Park,Swan Hwang,Songmi Kim,Ayoung Baek,Minky Son,서정근,Hyong-Ha Kim,이근우 대한화학회 2011 Bulletin of the Korean Chemical Society Vol.32 No.1
Peroxisome proliferator-activated receptors (PPARs) are members of nuclear receptors and their activation induces regulation of fatty acid storage and glucose metabolism. Therefore, the PPARγ is a major target for the treatment of type 2 diabetes mellitus. In order to generate pharmacophore model, 1080 known agonists database was constructed and a training set was selected. The Hypo7, selected from 10 hypotheses, contains four features: three hydrogen-bond acceptors (HBA) and one general hydrophobic (HY). This pharmacophore model was validated by using 862 test set compounds with a correlation coefficient of 0.903 between actual and estimated activity. Secondly, CatScramble method was used to verify the model. Hence, the validated Hypo7 was utilized for searching new lead compounds over 238,819 and 54,620 chemical structures in NCI and Maybridge database, respectively. Then the leads were selected by screening based on the pharmacophore model, predictive activity, and Lipinski’s rules. Candidates were obtained and subsequently the binding affinities to PPARγ were investigated by the molecular docking simulations. Finally the best two compounds were presented and would be useful to treat type 2 diabetes.
Arooj, Mahreen,Thangapandian, Sundarapandian,John, Shalini,Hwang, Swan,Park, Jong K.,Lee, Keun W. Blackwell Publishing Ltd 2012 Chemical biology & drug design Vol.80 No.6
<P>To provide a new idea for drug design, a computational investigation is performed on chymase and its novel 1,4‐diazepane‐2,5‐diones inhibitors that explores the crucial molecular features contributing to binding specificity. Molecular docking studies of inhibitors within the active site of chymase were carried out to rationalize the inhibitory properties of these compounds and understand their inhibition mechanism. The density functional theory method was used to optimize molecular structures with the subsequent analysis of highest occupied molecular orbital, lowest unoccupied molecular orbital, and molecular electrostatic potential maps, which revealed that negative potentials near 1,4‐diazepane‐2,5‐diones ring are essential for effective binding of inhibitors at active site of enzyme. The Bayesian model with receiver operating curve statistic of 0.82 also identified arylsulfonyl and aminocarbonyl as the molecular features favoring and not favoring inhibition of chymase, respectively. Moreover, genetic function approximation was applied to construct 3D quantitative structure–activity relationships models. Two models (genetic function approximation model 1 <I>r</I><SUP>2</SUP> = 0.812 and genetic function approximation model 2 <I>r</I><SUP>2</SUP> = 0.783) performed better in terms of correlation coefficients and cross‐validation analysis. In general, this study is used as example to illustrate how combinational use of 2D/3D quantitative structure–activity relationships modeling techniques, molecular docking, frontier molecular orbital density fields (highest occupied molecular orbital and lowest unoccupied molecular orbital), and molecular electrostatic potential analysis may be useful to gain an insight into the binding mechanism between enzyme and its inhibitors.</P>
Arooj, Mahreen,Thangapandian, Sundarapandian,John, Shalini,Hwang, Swan,Park, Jong Keun,Lee, Keun Woo Molecular Diversity Preservation International (MD 2011 INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES Vol.12 No.12
<P>Human chymase is a very important target for the treatment of cardiovascular diseases. Using a series of theoretical methods like pharmacophore modeling, database screening, molecular docking and Density Functional Theory (DFT) calculations, an investigation for identification of novel chymase inhibitors, and to specify the key factors crucial for the binding and interaction between chymase and inhibitors is performed. A highly correlating (<I>r</I> = 0.942) pharmacophore model (Hypo1) with two hydrogen bond acceptors, and three hydrophobic aromatic features is generated. After successfully validating “Hypo1”, it is further applied in database screening. Hit compounds are subjected to various drug-like filtrations and molecular docking studies. Finally, three structurally diverse compounds with high <I>GOLD</I> fitness scores and interactions with key active site amino acids are identified as potent chymase hits. Moreover, DFT study is performed which confirms very clear trends between electronic properties and inhibitory activity (IC<SUB>50</SUB>) data thus successfully validating “Hypo1” by DFT method. Therefore, this research exertion can be helpful in the development of new potent hits for chymase. In addition, the combinational use of docking, orbital energies and molecular electrostatic potential analysis is also demonstrated as a good endeavor to gain an insight into the interaction between chymase and inhibitors.</P>
Ligand Based Pharmacophore Identification and Molecular Docking Studies for Grb2 Inhibitors
Arulalapperumal, Venkatesh,Sakkiah, Sugunadevi,Thangapandian, Sundarapandian,Lee, Yun-O,Meganathan, Chandrasekaran,Hwang, Swan,Lee, Keun-Woo Korean Chemical Society 2012 Bulletin of the Korean Chemical Society Vol.33 No.5
Grb2 is an adapter protein involved in the signal transduction and cell communication. The Grb2 is responsible for initiation of kinase signaling by Ras activation which leads to the modification in transcription. Ligand based pharmacophore approach was applied to built the suitable pharmacophore model for Grb2. The best pharmacophore model was selected based on the statistical values and then validated by Fischer's randomization method and test set. Hypo1 was selected as a best pharmacophore model based on its statistical values like high cost difference (182.22), lowest RMSD (1.273), and total cost (80.68). It contains four chemical features, one hydrogen bond acceptor (HBA), two hydrophobic (HY), and one ring aromatic (RA). Fischer's randomization results also shows that Hypo1 have a 95% significant level. The correlation coefficient of test set was 0.97 which was close to the training set value (0.94). Thus Hypo1 was used for virtual screening to find the potent inhibitors from various chemical databases. The screened compounds were filtered by Lipinski's rule of five, ADMET and subjected to molecular docking studies. Totally, 11 compounds were selected as a best potent leads from docking studies based on the consensus scoring function and critical interactions with the amino acids in Grb2 active site.