• Bulletin of the Korean Chemical Society
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• v.27 no.5
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• pp.657-662
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• 2006

Identification of accessible sites in targeted RNAs is a major limitation to the effectiveness of antisense oligonucleotides. A class of antisense oligodeoxynucleotides, known as the “10-23” DNA enzyme or DNAzyme, which is a small catalytic DNA, has been shown to efficiently cleave target RNA at purine-pyrimidine junctions in vitro. We have designed a strategy to identify accessible cleavage sites in the target RNA, which is hepatitis C virus nonstructural gene 3 (HCV NS3) RNA that encodes viral helicase and protease, from a pool of random DNAzyme library. A pool of DNAzymes of 58 nucleotides-length that possess randomized annealing arms, catalytic core sequence, and fixed 5'/3'-end flanking sequences was designed and screened for their ability to cleave the target RNA. The screening procedure, which includes binding of DNAzyme pool to the target RNA under inactive condition, selection and amplification of active DNAzymes, incubation of the selected DNAzymes with the target RNA, and target site identification on sequencing gels, identified 16 potential cleavage sites in the target RNA. Corresponding DNAzymes were constructed for the selected target sites and were tested for RNA-cleavage in terms of kinetics and accessibility. These selected DNAzymes were effective in cleaving the target RNA in the presence of $Mg^{2+}$. This strategy can be applicable to identify accessible sites in any target RNA for antisense oligonucleotides-based gene inactivation methods.

• Journal of Microbiology and Biotechnology
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• v.13 no.3
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• pp.451-456
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• 2003

An expression vector system was developed for the secretory production of recombinant Bacillus stearothermophilus L1 lipase in Saccharomyces cerevisiae. The mature L1 lipase gene was fused to ${\alpha}-amylase$ signal sequence from Aspergillus oryzae for the effective secretion into the culture broth and the expression was controlled under GAL10 (the gene coding UDP-galactose epimerase of S. cerevisiae) promoter. S. cerevisiae harboring the resulting plasmid successfully secreted L1 lipase into the culture broth. To examine an optimum condition for L1 lipase expression in the fed-batch culture, L1 lipase expression was induced at three different growth phases (early, mid, and late-exponential growth phases). Maximum product on of L1 lipase (1,254,000 U/l, corresponding to 0.65/1) was found when the culture was induced at an early growth phase. Secreted recombinant L1 lipase was purified only through CM-Sepharose chromatography, and the purified enzyme showed 1,963 U/mg of specific activity and thermoalkalophilic properties similar to those reported for the enzyme expressed in Escherichia coli.

• Asian-Australasian Journal of Animal Sciences
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• v.25 no.6
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• pp.800-805
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• 2012

Rice straw is an important roughage resource for ruminants in many rice-producing countries. In this study, a rice brittle mutant (BM, mutation in OsCesA4, encoding cellulose synthase) and its wild type (WT) were employed to investigate the effects of a cellulose synthase gene mutation on rice straw morphological fractions, chemical composition, stem histological structure and in situ digestibility. The morphological fractions investigation showed that BM had a higher leaf sheath proportion (43.70% vs 38.21%, p<0.01) and a lower leaf blade proportion (25.21% vs 32.14%, p<0.01) than WT. Chemical composition analysis showed that BM rice straw was significantly (p<0.01) higher in CP (crude protein), hemicellulose and acid insoluble ash (AIA) contents, but lower in dry matter (DM), acid detergent fiber (ADFom) and cellulose contents when compared to WT. No significant difference (p>0.05) was detected in neutral detergent fiber (NDFom) and ADL contents for both strains. Histological structure observation indicated that BM stems had fewer sclerenchyma cells and a thinner sclerenchyma cell wall than WT. The results of in situ digestion showed that BM had higher DM, NDFom, cellulose and hemicellulose disappearance at 24 or 48 h of incubation (p<0.05). The effective digestibility of BM rice straw DM and NDFom was greater than that of WT (31.4% vs 26.7% for DM, 29.1% vs 24.3% for NDFom, p<0.05), but the rate of digestion of the slowly digested fraction of BM rice straw DM and NDF was decreased. These results indicated that the mutation in the cellulose synthase gene could improve the nutritive value of rice straw for ruminants.

• Bulletin of the Korean Chemical Society
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• v.33 no.1
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• pp.177-182
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• 2012

A new composition of standardized Scutellariae Radix extract (HPO12) was developed for treatment of Alzheimer's disease. For the preclinical pharmacokinetic study of HPO12, a rapid, sensitive, and selective LCMS/MS method was developed and validated for the simultaneous determination of 4 bioactive compounds, baicalein, baicalin, wogonin, and wogonoside. After extraction with ethylacetate, chromatographic analysis was performed on a Thermo $C_{18}$ column ($150mm{\times}2.1mm$, $3{\mu}m$) with a mobile phase consisting of 0.1% formic acid (A) and 0.1% formic acid in 95% acetonitrile (B) by using gradient elution at a flow rate of $250{\mu}L/min$. Analytes introduced to a mass spectrometer were monitored by multiple reaction monitoring (MRM) in positive ion mode. Using $25{\mu}L$ of plasma sample, the method was validated over the following concentration ranges: 25-5000 ng/mL for baicalein, 20-40000 ng/mL for baicalin, 1-1000 ng/mL for wogonin, and 5-10000 ng/mL for wogonoside. The intra- and inter-day precision and accuracy of the quality control samples at the 4 concentrations showed $\leq$ 13.7% relative standard deviation (RSD) and 86.6-105.5% accuracy. The method was successfully applied to determine the concentrations of baicalein, baicalin, wogonin, and wogonoside in rat plasma after intraperitoneal and oral administrations of HPO12.

• Genomics & Informatics
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• v.6 no.3
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• pp.142-146
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• 2008

In order to understand the protein functions that are related to disease, it is important to detect the correlation between amino acid mutations and disease. Many mutation studies about disease-related proteins have been carried out through molecular biology techniques, such as vector design, protein engineering, and protein crystallization. However, experimental protein mutation studies are time-consuming, be it in vivo or in vitro. We therefore performed a bioinformatic analysis of known disease-related mutations and their protein structure changes in order to analyze the correlation between mutation and disease. For this study, we selected 111 diseases that were related to 175 proteins from the PDB database and 710 mutations that were found in the protein structures. The mutations were acquired from the Human Gene Mutation Database (HGMD). We selected point mutations, excluding only insertions or deletions, for detecting structural changes. To detect a structural change by mutation, we analyzed not only the structural properties (distance of pocket and mutation, pocket size, surface size, and stability), but also the physico-chemical properties (weight, instability, isoelectric point (IEP), and GRAVY score) for the 710 mutations. We detected that the distance between the pocket and disease-related mutation lay within $20\;{\AA}$ (98.5%, 700 proteins). We found that there was no significant correlation between structural stability and disease-causing mutations or between hydrophobicity changes and critical mutations. For large-scale mutational analysis of disease-causing mutations, our bioinformatics approach, using 710 structural mutations, called "Structural Mutatomics," can help researchers to detect disease-specific mutations and to understand the biological functions of disease-related proteins.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.35 no.6
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• pp.556-561
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• 2022

Computational material science as an application of Density Functional Theory (DFT) to the discipline of material science has emerged and applied to the research and development of energy materials and electronic materials such as semiconductor. However, there are a few difficulties, such as generating input files for various types of materials in both the same calculating condition and appropriate parameters, which is essential in comparing results of DFT calculation in the right way. In this tutorial status report, we will introduce how to create crystal structures and to prepare input files automatically for the Vienna Ab initio Simulation Package (VASP) and Gaussian, the most popular DFT calculation programs. We anticipate this tutorial makes DFT calculation easier for the ones who are not experts on DFT programs.

• Journal of KIISE:Databases
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• v.30 no.6
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• pp.573-584
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• 2003

Recent massive data generation by genomics and proteomics requires bioinformatic tools to extract the biological meaning from the massive results. Here we introduce ROSPath, a database system to deal with information on reactive oxygen species (ROS)-mediated cell signaling pathways. It provides a structured repository for handling pathway related data and tools for querying, displaying, and analyzing pathways. ROSPath data model provides the extensibility for representing incomplete knowledge and the accessibility for linking the existing biochemical databases via the Internet. For flexibility and efficient retrieval, hierarchically structured data model is defined by using the object-oriented model. There are two major data types in ROSPath data model: ‘bio entity’ and ‘interaction’. Bio entity represents a single biochemical entity: a protein or protein state involved in ROS cell-signaling pathways. Interaction, characterized by a list of inputs and outputs, describes various types of relationship among bio entities. Typical interactions are protein state transitions, chemical reactions, and protein-protein interactions. A complex network can be constructed from ROSPath data model and thus provides a foundation for describing and analyzing various biochemical processes.

• Genomics & Informatics
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• v.13 no.1
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• pp.15-24
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• 2015

Fatty acid synthase (FASN, EC 2.3.1.85), is a multi-enzyme dimer complex that plays a critical role in lipogenesis. This lipogenic enzyme has gained importance beyond its physiological role due to its implications in several clinical conditions-cancers, obesity, and diabetes. This has made FASN an attractive pharmacological target. Here, we have attempted to predict the theoretical models for the human enoyl reductase (ER) and ${\beta}$-ketoacyl reductase (KR) domains based on the porcine FASN crystal structure, which was the structurally closest template available at the time of this study. Comparative modeling methods were used for studying the structure-function relationships. Different validation studies revealed the predicted structures to be highly plausible. The respective substrates of ER and KR domains-namely, trans-butenoyl and ${\beta}$-ketobutyryl-were computationally docked into active sites using Glide in order to understand the probable binding mode. The molecular dynamics simulations of the apo and holo states of ER and KR showed stable backbone root mean square deviation trajectories with minimal deviation. Ramachandran plot analysis showed 96.0% of residues in the most favorable region for ER and 90.3% for the KR domain, respectively. Thus, the predicted models yielded significant insights into the substrate binding modes of the ER and KR catalytic domains and will aid in identifying novel chemical inhibitors of human FASN that target these domains.

• Genomics & Informatics
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• v.10 no.2
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• pp.123-127
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• 2012

Gene set analysis (GSA) is useful in interpreting a genome-wide association study (GWAS) result in terms of biological mechanism. We compared the performance of two different GSA implementations that accept GWAS p-values of single nucleotide polymorphisms (SNPs) or gene-by-gene summaries thereof, GSA-SNP and i-GSEA4GWAS, under the same settings of inputs and parameters. GSA runs were made with two sets of p-values from a Korean type 2 diabetes mellitus GWAS study: 259,188 and 1,152,947 SNPs of the original and imputed genotype datasets, respectively. When Gene Ontology terms were used as gene sets, i-GSEA4GWAS produced 283 and 1,070 hits for the unimputed and imputed datasets, respectively. On the other hand, GSA-SNP reported 94 and 38 hits, respectively, for both datasets. Similar, but to a lesser degree, trends were observed with Kyoto Encyclopedia of Genes and Genomes (KEGG) gene sets as well. The huge number of hits by i-GSEA4GWAS for the imputed dataset was probably an artifact due to the scaling step in the algorithm. The decrease in hits by GSA-SNP for the imputed dataset may be due to the fact that it relies on Z-statistics, which is sensitive to variations in the background level of associations. Judicious evaluation of the GSA outcomes, perhaps based on multiple programs, is recommended.

• Molecular & Cellular Toxicology
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• v.4 no.3
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• pp.260-266
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• 2008

Recently, there has been scientific discussion on the utility of -omics techniques such as genomics, proteomics, and metabolomics within toxicological research and mechanism-based risk assessment. Toxicogenomics is a novel approach integrating the expression analysis of genes (genomic) or proteins (proteomic) with traditional toxicological methods. Since 1999, the toxicogenomic approach has been extensively applied for regulatory purposes in order to understand the potential toxic mechanisms that result from chemical compound exposures. Therefore, this article's purpose was to consider the utility of toxicogenomic profiles for improved risk assessment, explore the current limitations in applying toxicogenomics to regulation, and finally, to rationalize possible avenues to resolve some of the major challenges. Based on many recent works, the significant impact toxicogenomic techniques would have on human health risk assessment is better identification of toxicity pathways or mode-of-actions (MOAs). In addition, the application of toxicogenomics in risk assessment and regulation has proven to be cost effective in terms of screening unknown toxicants prior to more extensive and costly experimental evaluation. However, to maximize the utility of these techniques in regulation, researchers and regulators must resolve many parallel challenges with regard to data collection, integration, and interpretation. Furthermore, standard guidance has to be prepared for researchers and assessors on the scientifically appropriate use of toxicogenomic profiles in risk assessment. The National Institute of Toxicological Research (NITR) looks forward to an ongoing role as leader in addressing the challenges associated with the scientifically sound use of toxicogenomics data in risk assessment.