• Bulletin of the Korean Chemical Society
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• v.29 no.5
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• pp.921-927
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• 2008

Discovery of $\alpha$-glucosidase inhibitors has been actively pursued with the aim to develop therapeutics for the treatment of diabetes and the other carbohydrate mediated diseases. As a method for the discovery of new novel inhibitors of $\alpha$-glucosidase, we have addressed the performance of the computer-aided drug design protocol involving the homology modeling of $\alpha$-glucosidase and the structure-based virtual screening with the two docking tools: FlexX and the automated and improved AutoDock implementing the effects of ligand solvation in the scoring function. The homology modeling of $\alpha$-glucosidase from baker’s yeast provides a high-quality 3-D structure enabling the structure-based inhibitor design. Of the two docking programs under consideration, AutoDock is found to be more accurate than FlexX in terms of scoring putative ligands to the extent of 5-fold enhancement of hit rate in database screening when 1% of database coverage is used as a cutoff. A detailed binding mode analysis of the known inhibitors shows that they can be stabilized in the active site of $\alpha$- glucosidase through the simultaneous establishment of the multiple hydrogen bond and hydrophobic interactions. The present study demonstrates the usefulness of the automated AutoDock program with the improved scoring function as a docking tool for virtual screening of new $\alpha$-glucosidase inhibitors as well as for binding mode analysis to elucidate the activities of known inhibitors.

• Journal of KIISE:Computer Systems and Theory
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• v.35 no.6
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• pp.237-247
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• 2008

A virtual screening is the process of reducing an unmanageable number of compounds to a limited number of compounds for the target of interest by means of computational techniques such as molecular docking. And it is one of a large-scale scientific application that requires large computing power and data storage capability. Previous applications or softwares for molecular docking such as AutoDock, FlexX, Glide, DOCK, LigandFit, ViSION were developed to be run on a supercomputer, a workstation, or a cluster-computer. However the virtual screening using a supercomputer has a problem that a supercomputer is very expensive and the virtual screening using a workstation or a cluster-computer requires a long execution time. Thus we propose a service-based virtual screening system using Grid computing technology which supports a large data intensive operation. We constructed 3-dimensional chemical molecular database for virtual screening. And we designed a resource broker and a data broker for supporting efficient molecular docking service and proposed various services for virtual screening. We implemented service based virtual screening system with DOCK 5.0 and Globus 3.2 toolkit. Our system can reduce a timeline and cost of drug or new material design.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.12
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• pp.881-890
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• 2009

To solve big problem in high energy physics or bioinformatics, it needs a large number of computing resources. But it hard to be provided by one grid environment. While user can submit each job by using it's own user interface in each grid environment, it may need many cost and efforts to manage several hundred jobs conserved in each grid environment separately. In this paper, to solve this problem we develop Ganga's Gridway backend and InterGrid backend. Therefore as we provide the same grid user interface between different grid environments. We developed a Gridway backend module that provide users with access to globus-based grid resources as well. We have also developed an InterGrid backend that allows users to submit jobs that have access to both glite-based resources and globus-based resources. In order to demonstrate the practicality of the new backend plugin modules, we have integrated the AutoDock application used by WISDOM project into Ganga as a new built-in application plugin for Ganga. And we preformed interoperability experiment between PRAGMA grid based on Globus and EGEE grid based on gLite.

• International Journal of Control, Automation, and Systems
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• v.6 no.5
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• pp.731-739
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• 2008

The docking and recharging system for a mobile robot must guarantee the ability to perform its tasks continuously without human intervention. This paper proposes two docking mechanisms with localization error-compensation capability for an auto recharging system. The mechanisms use friction forces or magnetic forces between the docking parts of the robot and those of the docking station. It is a structure to improve the allowance ranges of lateral and directional docking offsets, in which the robot is able to dock into the docking station. In this paper, auto-recharging system and the features of the proposed mechanisms are verified with experimental results using simple homing method.

• Journal of Pharmacopuncture
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• v.18 no.2
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• pp.7-18
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• 2015

Objectives: Lawsone (1,4 naphthoquinone) is a non redox cycling compound that can be catalyzed by DT diaphorase (DTD) into 1,2,4-trihydroxynaphthalene (THN), which can generate reactive oxygen species by auto oxidation. The purpose of this study was to evaluate the toxicity of the phytomarker 1,4 naphthoquinone and its metabolite THN by using the molecular docking program AutoDock 4. Methods: The 3D structure of ligands such as hydrogen peroxide ($H_2O_2$), nitric oxide synthase (NOS), catalase (CAT), glutathione (GSH), glutathione reductase (GR), glucose 6-phosphate dehydrogenase (G6PDH) and nicotinamide adenine dinucleotide phosphate hydrogen (NADPH) were drawn using hyperchem drawing tools and minimizing the energy of all pdb files with the help of hyperchem by $MM^+$ followed by a semi-empirical (PM3) method. The docking process was studied with ligand molecules to identify suitable dockings at protein binding sites through annealing and genetic simulation algorithms. The program auto dock tools (ADT) was released as an extension suite to the python molecular viewer used to prepare proteins and ligands. Grids centered on active sites were obtained with spacings of $54{\times}55{\times}56$, and a grid spacing of 0.503 was calculated. Comparisons of Global and Local Search Methods in Drug Docking were adopted to determine parameters; a maximum number of 250,000 energy evaluations, a maximum number of generations of 27,000, and mutation and crossover rates of 0.02 and 0.8 were used. The number of docking runs was set to 10. Results: Lawsone and THN can be considered to efficiently bind with NOS, CAT, GSH, GR, G6PDH and NADPH, which has been confirmed through hydrogen bond affinity with the respective amino acids. Conclusion: Naphthoquinone derivatives of lawsone, which can be metabolized into THN by a catalyst DTD, were examined. Lawsone and THN were found to be identically potent molecules for their affinities for selected proteins.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.35-40
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• 2005

Interaction of twelve erythromycin A analogues with 50S ribosomal subunit were studied employing AutoDock 3.0.5. Results showed that all active macrolides bound at the same binding site with erythromycin A in contrast to the inactive analogues which bound at location slightly different than erythromycin A. The binding site showed consistency with the X-ray data from the perspectives of hydrogen bonding and hydrophobic interactions formed by erythromycins, roxithromycin, azithromycin, cethromycin and telithromycin with the ribosome. The inactive derivatives of erythromycin A anhydride showed higher binding free energy, while 5-desosaminyl erythronolides A and B even though having quiet similar values of binding free energy with the active analogues, docked at binding sites which are quiet different than the active analogues. These results suggest the molecular docking technique can be used in predicting the binding of erythromycin A analogues to their ribosomal target.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2004.11a
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• pp.203-209
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• 2004

Molecular docking using Lamarckian genetic algorithm of AutoDock 3.0 (AD3) was employed to understand in retrospect the selectivity of phenylaminopyrimidine (PAP) derivatives against the kinase domain c-Abl, implicated in chronic myelogenous leukemia (CML). The energetics of protein-ligand complex was scored using AD3 to identify active drug conformations while Ligplot and ligand protein contact (LPC) programs were used to probe schematic molecular recognition of the bound inhibitor to the protein. Results signify correlation between model and crystal structures of STI-571 compound or Imatinib (IM), a PAP derivative and now clinically proven for its efficacy in CML. A prospect active form Abl inhibitor scaffold from matlystatin class of compounds will be published elsewhere.

• Bulletin of the Korean Chemical Society
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• v.26 no.11
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• pp.1695-1700
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• 2005

Catechol-O-methyltransferase (COMT, EC 2.1.1.6) is an S-adenosylmethionine (SAM, AdoMet) dependent methyltransferase, and is related to the functions of the neurotransmitters in various mental processes, such as Parkinson’s disease. COMT inhibitors represent a new class of antiparkinson drugs, when they are coadministered with levodopa. Based on x-ray structure of rat COMT (rCOMT), the three dimensional structure of human COMT (hCOMT) was constructed by comparative homology modeling using MODELLER. The catalytic site of these two proteins showed subtle differences, but these differences are important to determine the characterization of COMT inhibitor. Ligand docking study is carried out for complex of hCOMT and COMT inhibitors using AutoDock. Among fifteen inhibitors chosen from world patent, nine models were energetically favorable. The average value of heavy atomic RMSD was 1.5 $\AA$. Analysis of ligand-protein binding model implies that Arg201 on hCOMT plays important roles in the interactions with COMT inhibitors. This study may give insight to develop new ways of antiparkinson drug.

• Journal of Ocean Engineering and Technology
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• v.30 no.3
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• pp.208-213
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• 2016

This paper proposes a potential field-based guidance law for docking a USV (unmanned surface vehicle). In most cases, a USV without side thrusters is an under-actuated system. Thus, there are undockable regions near docking stations where a USV cannot dock to a docking station without causing a collision or backward motion. This paper suggest a guidance law that prevents a USV from enter such a region by decreasing the lateral error to the docking station at the initial stage of the docking process. A Monte-carlo simulation was performed to validate the performance of the proposed method. The proposed method was compared to conventional guidance laws such as pure pursuit guidance and pure/lead pursuit guidance. As a result, the collision angle and lateral distance error of proposed method tended to have lower values compared to conventional methods.

• Genomics & Informatics
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• v.12 no.4
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• pp.276-282
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• 2014

The disease tuberculosis, caused by Mycobacterium tuberculosis (MTB), remains a major cause of morbidity and mortality in developing countries. The evolution of drug-resistant tuberculosis causes a foremost threat to global health. Most drug-resistant MTB clinical strains are showing resistance to isoniazid and rifampicin (RIF), the frontline anti-tuberculosis drugs. Mutation in rpoB, the beta subunit of DNA-directed RNA polymerase of MTB, is reported to be a major cause of RIF resistance. Amongst mutations in the well-defined 81-base-pair central region of the rpoB gene, mutation at codon 450 (S450L) and 445 (H445Y) is mainly associated with RIF resistance. In this study, we modeled two resistant mutants of rpoB (S450L and H445Y) using Modeller9v10 and performed a docking analysis with RIF using AutoDock4.2 and compared the docking results of these mutants with the wild-type rpoB. The docking results revealed that RIF more effectively inhibited the wild-type rpoB with low binding energy than rpoB mutants. The rpoB mutants interacted with RIF with positive binding energy, revealing the incapableness of RIF inhibition and thus showing resistance. Subsequently, this was verified by molecular dynamics simulations. This in silico evidence may help us understand RIF resistance in rpoB mutant strains.