• Bulletin of the Korean Chemical Society
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• v.23 no.1
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• pp.9-10
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• 2002

• The Plant Pathology Journal
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• v.33 no.6
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• pp.529-542
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• 2017

Control of plant diseases is largely dependent on use of agrochemicals. However, there are widening gaps between our knowledge on plant diseases gained from genetic/mechanistic studies and rapid translation of the knowledge into target-oriented development of effective agrochemicals. Here we propose that the time is ripe for computer-aided drug discovery/design (CADD) in molecular plant pathology. CADD has played a pivotal role in development of medically important molecules over the last three decades. Now, explosive increase in information on genome sequences and three dimensional structures of biological molecules, in combination with advances in computational and informational technologies, opens up exciting possibilities for application of CADD in discovery and development of agrochemicals. In this review, we outline two categories of the drug discovery strategies: structure- and ligand-based CADD, and relevant computational approaches that are being employed in modern drug discovery. In order to help readers to dive into CADD, we explain concepts of homology modelling, molecular docking, virtual screening, and de novo ligand design in structure-based CADD, and pharmacophore modelling, ligand-based virtual screening, quantitative structure activity relationship modelling and de novo ligand design for ligand-based CADD. We also provide the important resources available to carry out CADD. Finally, we present a case study showing how CADD approach can be implemented in reality for identification of potent chemical compounds against the important plant pathogens, Pseudomonas syringae and Colletotrichum gloeosporioides.

• Journal of Integrative Natural Science
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• v.11 no.2
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• pp.121-129
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• 2018

CXCR6 is a major target in drug design as it is a determinant receptor in many diseases like AIDS, Type I Diabetes, some cancer types, atherosclerosis, tumor formation, liver disease and steatohepatitis. In this study, we propose the active site residues of CXCR6 molecule. We employed homology modelling and molecular docking approach to generate the 3D structure for CXCR6 and to explore its interaction between the antagonists and agonists. 3D models were generated using 14 different templates having high sequence identity with CXCR6. Surflex docking studies using pyridine and pyrimidine derivatives enabled the analysis of the binding site and finding of the important residues involved in binding. 3D structure of CXCL16, a natural ligand for CXCR6, was modelled using PHYRE and protein - protein docking was performed using ClusPro. The residues which were found to be crucial in interaction with the ligand are THR110, PHE113, TYR114, GLN160, GLN195, CYS251 and SER255. This study can be used as a guide for therapeutic studies of human CXCR6.

• Biotechnology and Bioprocess Engineering:BBE
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• v.11 no.3
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• pp.223-229
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• 2006

In this study, we have conducted kinetics and modelling studies of Centella asiatica cell growth and substrate uptake, in an attempt to evaluate cell growth for a better understanding and control of the process. In our bioreactor cultivation experiment, we observed a growth rate of 0.18/day, a value only 20% higher than was seen in the shake flask cultivation trial. However, the observed maximum cell dry weight in the shake flask, 10.5g/L, was 14% higher than was achieved in the bioreactor. Ninety seven percentage confidence was achieved via the fitting of three unstructured growth models; the Monod, Logistic, and Gompertz equations, to the cell growth data. The Monod equation adequately described cell growth in both cultures. The specific growth rate, however, was not effectively predicted with the Logistic and Gompertz equations, which resulted in deviations of up to 73 and 393%, respectively. These deviations in the Logistic and Gompertz models may be attributable to the fact that these models were developed for substrate-independent growth and fungi growth, respectively.

• Proceeding of EDISON Challenge
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• 2017.03a
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• pp.16-26
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• 2017

Auxin response factor (ARF) and Aux/IAA transcriptional repressor family proteins play a major role in auxin's signalling process. Using the GALAXY protein modelling programs, monomer, dimer and oligomer structures of Aux/IAA17 and ARF5 protein were predicted based on the known experimental structures. By analysing the proposed complex structures, key interacting residues on binding site could be determined, and further suggestions for experimental studies were made.

• Journal of Animal Science and Technology
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• v.57 no.12
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• pp.44.1-44.9
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• 2015

Background: Heat shock proteins play an important role in protection from stress stimuli and metabolic insults in almost all organisms. Methods: In this study, computational tools were used to deeply analyse the physicochemical characteristics and, using homology modelling, reliably predict the tertiary structure of the blunt snout bream (Ma-) Hsp70 and Hsc70 proteins. Derived three-dimensional models were then used to predict the function of the proteins. Results: Previously published predictions regarding the protein length, molecular weight, theoretical isoelectric point and total number of positive and negative residues were corroborated. Among the new findings are: the extinction coefficient (33725/33350 and 35090/34840 - Ma-Hsp70/ Ma-Hsc70, respectively), instability index (33.68/35.56 - both stable), aliphatic index (83.44/80.23 - both very stable), half-life estimates (both relatively stable), grand average of hydropathicity (-0.431/-0.473 - both hydrophilic) and amino acid composition (alanine-lysine-glycine/glycine-lysine-aspartic acid were the most abundant, no disulphide bonds, the N-terminal of both proteins was methionine). Homology modelling was performed by SWISS-MODEL program and the proposed model was evaluated as highly reliable based on PROCHECK's Ramachandran plot, ERRAT, PROVE, Verify 3D, ProQ and ProSA analyses. Conclusions: The research revealed a high structural similarity to Hsp70 and Hsc70 proteins from several taxonomically distant animal species, corroborating a remarkably high level of evolutionary conservation among the members of this protein family. Functional annotation based on structural similarity provides a reliable additional indirect evidence for a high level of functional conservation of these two genes/proteins in blunt snout bream, but it is not sensitive enough to functionally distinguish the two isoforms.

• Membrane Journal
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• v.30 no.4
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• pp.242-251
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• 2020

Computer simulation tools mainly used for polymer materials and polymeric membranes are divided into various fields depending on the size of the object to be simulated and the time to be simulated. The computer simulations introduced in this review are classified into three categories: Quantum mechanics (QM), molecular dynamics (MD), and mesoscale modeling, which are mainly used in computational material chemistry. The computer simulation used in polymer research has different research target for each kind of computational simulation. Quantum mechanics deals with microscopic phenomena such as molecules, atoms, and electrons to study small-sized phenomena, molecular dynamics calculates the movement of atoms and molecules calculated by Newton's equation of motion when a potential or force of is given, and mesoscale simulation is a study to determine macroscopically by reducing the computation time with large molecules by forming beads by grouping atoms together. In this review, various computer simulation programs mainly used for polymers and polymeric membranes divided into the three types classified above will be introduced according to each feature and field of use.

• Journal of the Korean Applied Science and Technology
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• v.16 no.4
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• pp.329-335
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• 1999

The influences of fluorophor, scatterer, and absorber in turbid material by light scattering were interpreted for the scattered fluorescence intensity and wavelength. The molecular properties have been studied by laser induced fluorescence spectroscopy in phantom. It has been found that the effects of optical properties in scattering media could be investigated by the optical parameters(${\mu}_a$, ${\mu}_a$, ${\mu}_t$). Experimental and Monte Carlo Simulation method for modelling light transport in tissue was applied. The experimental results using a phantom were discussed and compared with those obtained through Monte Carlo Simulation. It may also aid in designing the best model for oil chemistry, medicine and application of medical engineering.

• Advances in nano research
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• v.12 no.3
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• pp.253-261
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• 2022

Numerical modelling of an integrated Carbon NanoTube (CNT) membrane is only achievable if probable deformations and realistic alterations from a perfect CNT membrane are taken into account. Considering the possible forms of CNTs, bending is one of the most probable deformations in these high aspect ratio nanostructures. Hence, investigation of effect associated with bent CNTs are of great interest. In the present study, molecular dynamics simulation is utilized to investigate fluid flow dynamics in deformed CNT membranes, specifically when the tube cross section is not affected. Bending in armchair (5,5) CNT was simulated using Tersoff potential, prior to flow rate investigation. Also, to study effect of inclined entry of the CNT to the membrane wall, argon flow through generated inclined CNT membranes is examined. The results show significant variation in both cases, which can be interpreted as counter-intuitive, since the cross section of the CNT was not deformed in either case. The distribution of fluid-fluid and fluid-wall interaction potential is investigated to explain the anomalous behavior of the flow rate versus bending angle.

• Smart Structures and Systems
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• v.22 no.5
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• pp.561-574
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• 2018

In this paper, for efficiently reducing the computational cost of the model updating during the optimization process of damage detection, the structural response is evaluated using properly trained surrogate model. Furthermore, in practice uncertainties in the FE model parameters and modelling errors are inevitable. Hence, an efficient approach based on Monte Carlo simulation is proposed to take into account the effect of uncertainties in developing a surrogate model. The probability of damage existence (PDE) is calculated based on the probability density function of the existence of undamaged and damaged states. The current work builds a framework for Probability Based Damage Detection (PBDD) of structures based on the best combination of metaheuristic optimization algorithm and surrogate models. To reach this goal, three popular metamodeling techniques including Cascade Feed Forward Neural Network (CFNN), Least Square Support Vector Machines (LS-SVMs) and Kriging are constructed, trained and tested in order to inspect features and faults of each algorithm. Furthermore, three wellknown optimization algorithms including Ideal Gas Molecular Movement (IGMM), Particle Swarm Optimization (PSO) and Bat Algorithm (BA) are utilized and the comparative results are presented accordingly. Furthermore, efficient schemes are implemented on these algorithms to improve their performance in handling problems with a large number of variables. By considering various indices for measuring the accuracy and computational time of PBDD process, the results indicate that combination of LS-SVM surrogate model by IGMM optimization algorithm have better performance in predicting the of damage compared with other methods.