• Proceedings of the Microbiological Society of Korea Conference
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• 2008.05a
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• pp.147-149
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• 2008

• Genomics & Informatics
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• v.8 no.2
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• pp.63-69
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• 2010

Monofunctional biosynthetic peptidoglycan transglycosylase (MBPT) catalyzes the formation of the glycan chain in bacterial cell walls from peptidoglycan subunits: N-acetylglucosamine (NAG) and acetylmuramic acid (NAM). Bifunctional glycosyltransferases such as the penicillin binding protein (PBP) have peptidoglycan glycosyltransferase (PGT) on their C terminal end which links together the peptidoglycan subunits while transpeptidase (TP) on the N terminal end cross-links the peptide moieties on the NAM monosaccharide of the peptide subunits to create the bacterial cell wall. The singular function of MBPT resembles the C terminal end of PBP as it too contains and utilizes a similar PGT domain. In this article we analyzed the infectious and non infectious protein sequences of MBPT from 31 different strains of bacteria using a variety of bioinformatic tools. Motif analysis, dot-plot comparison, and phylogenetic analysis identified a number of significant differences between infectious and non-infectious protein sequences. In this paper we have made an attempt to explain, analyze and discuss these differences from an evolutionary perspective. The results of our sequence analysis may open the door for utilizing MBPT as a new target to fight a variety of infectious bacteria.

• Journal of the Korean Magnetic Resonance Society
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• v.13 no.2
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• pp.108-116
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• 2009

The HP0902, a homodimeric 22.1 kDa protein, has been suggested as a putative secretory protein from Helicobacter pylori, although the protein possesses no signal peptide for secretion. Since it may be associated with the virulence of the bacterium, NMR study has been initiated in terms of structural genomics. In our previous effort to assign the backbone NMR resonances, using 800MHz NMR machine at pH 7.8, the resonances from eight of the 99 residues could not be assined due to missing of the signals. In this work, to enhance the extent of assignments, a 900 MHz machine was employed and the sample pH was reduced down to 6.5. Finally, almost all signals, except for those from G9 and S24, could be clearly assigned. The determined secondary structure using the assined chemical shifts indicated that the HP0902 consists of 11 ${\beta}$-strands with no helices. In our database search result, HP0902 was predicted to interact with VacA (Vacuolating cytotoxin A), which is a representative virulence factor secreted from Helicobacter pylori. Thus, molecular interaction between HP0902 and VacA would be worthy of investigation, on the basis of the present results of NMR assignments.

• Korean Journal of Breeding Science
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• v.42 no.4
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• pp.397-406
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• 2010

Field screening method has been commonly used for purity test of $F_1$ hybrid seeds in melon and oriental melon. However, as this method takes a lot of time and cost, molecular marker-based purity test is necessary. To develop molecular markers for purity test, thirty pairs of SNP (single nucleotide polymorphism) primers were obtained from melon EST sequences, and 10 polymorphic markers showing HRM (high resolution melting) polymorphisms between parents of two melon cultivars and one oriental melon cultivar were selected. Blind tests were performed to validate usefulness of the selected markers for purity test. Blind test results showed that HRM genotypes were matched with the expected identity of individual sample, $F_1$ hybrid, male or female parents. Three HRM-based SNP markers were converted to CAPS markers for general use which is favor to breeders. We expect that SNP markers developed in this study will be useful for purity test of $F_1$ hybrid seeds in melon and oriental melon.

• Genomics & Informatics
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• v.6 no.1
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• pp.44-49
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• 2008

Protein kinase C (PKC) is a family of kinases involved in the transduction of cellular signals that promote lipid hydrolysis. PKC plays a pivotal role in mediating cellular responses to extracellular stimuli involved in proliferation, differentiation and apoptosis. Comparative analysis of the PKC-${\alpha},{\beta},{\varepsilon}$ isozymes of 200 recently sequenced microbial genomes was carried out using variety of bioinformatics tools. Diversity and evolution of PKC was determined by sequence alignment. The ser/thr protein kinases of Streptomyces coelicolor A3 (2), is the only bacteria to show sequence alignment score greater than 30% with all the three PKC isotypes in the sequence alignment. S.coelicolor is the subject of our interest because it is notable for the production of pharmaceutically useful compounds including anti-tumor agents, immunosupressants and over two-thirds of all natural antibiotics currently available. The comparative analysis of three human isotypes of PKC and Serine/threonine protein kinase of S.coelicolor was carried out and possible mechanism of action of PKC was derived. Our analysis indicates that Serine/ threonine protein kinase from S. coelicolor can be a good candidate for potent anti-tumor agent. The presence of three representative isotypes of the PKC super family in this organism helps us to understand the mechanism of PKC from evolutionary perspective.

• Genomics & Informatics
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• v.17 no.2
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• pp.15.1-15.7
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• 2019

Automatically detecting mentions of pharmaceutical drugs and chemical substances is key for the subsequent extraction of relations of chemicals with other biomedical entities such as genes, proteins, diseases, adverse reactions or symptoms. The identification of drug mentions is also a prior step for complex event types such as drug dosage recognition, duration of medical treatments or drug repurposing. Formally, this task is known as named entity recognition (NER), meaning automatically identifying mentions of predefined entities of interest in running text. In the domain of medical texts, for chemical entity recognition (CER), techniques based on hand-crafted rules and graph-based models can provide adequate performance. In the recent years, the field of natural language processing has mainly pivoted to deep learning and state-of-the-art results for most tasks involving natural language are usually obtained with artificial neural networks. Competitive resources for drug name recognition in English medical texts are already available and heavily used, while for other languages such as Spanish these tools, although clearly needed were missing. In this work, we adapt an existing neural NER system, NeuroNER, to the particular domain of Spanish clinical case texts, and extend the neural network to be able to take into account additional features apart from the plain text. NeuroNER can be considered a competitive baseline system for Spanish drug and CER promoted by the Spanish national plan for the advancement of language technologies (Plan TL).

• Molecules and Cells
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• v.27 no.1
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• pp.67-74
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• 2009

Autophagy degrades toxic materials and old organelles, and recycles nutrients in eukaryotic cells. Whereas the studies on autophagy have been reported in other eukaryotic cells, its functioning in plants has not been well elucidated. We analyzed the roles of OsATG10 genes, which are autophagy-related. Two rice ATG10 genes - OsATG10a and OsATG10b - share significant sequence homology (about 75%), and were ubiquitously expressed in all organs examined here. GUS assay indicated that OsATG10b was highly expressed in the mesophyll cells and vascular tissue of younger leaves, but its level of expression decreased in older leaves. We identified T-DNA insertional mutants in that gene. Those osatg10b mutants were sensitive to treatments with high salt and methyl viologen (MV). Monodansylcadaverine-staining experiments showed that the number of autophagosomes was significantly decreased in the mutants compared with the WT. Furthermore, the amount of oxidized proteins increased in MV-treated mutant seedlings. These results demonstrate that OsATG10b plays an important role in the survival of rice cells against oxidative stresses.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2000.11a
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• pp.56-58
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• 2000

Post-genomics may be defined in different ways depending on how one views the challenges after the genome. A popular view is to follow the concept of the central dogma in molecular biology, namely from genome to transcriptome to proteome. Projects are going on to analyze gene expression profiles both at the mRNA and protein levels and to catalog protein 3D structure families, which will no doubt help the understanding of information in the genome. However complete, such catalogs of genes, RNAs, and proteins only tell us about the building blocks of life. They do not tell us much about the wiring (interaction) of building blocks, which is essential for uncovering systemic functional behaviors of the cell or the organism. Thus, an alternative view of post-genomics is to go up from the molecular level to the cellular level, and to understand, what I call, the "interactome"or a complete picture of molecular interactions in the cell. KEGG (http://www.genome.ad.jp/kegg/) is our attempt to computerize current knowledge on various cellular processes as a collection of "generalized"protein-protein interaction networks, to develop new graph-based algorithms for predicting such networks from the genome information, and to actually reconstruct the interactomes for all the completely sequenced genomes and some partial genomes. During the reconstruction process, it becomes readily apparent that certain pathways and molecular complexes are present or absent in each organism, indicating modular structures of the interactome. In addition, the reconstruction uncovers missing components in an otherwise complete pathway or complex, which may result from misannotation of the genome or misrepresentation of the KEGG pathway. When combined with additional experimental data on protein-protein interactions, such as by yeast two-hybrid systems, the reconstruction possibly uncovers unknown partners for a particular pathway or complex. Thus, the reconstruction is tightly coupled with the annotation of individual genes, which is maintained in the GENES database in KEGG. We are also trying to expand our literature surrey to include in the GENES database most up-to-date information about gene functions.

• Proceedings of the Korean Society for Applied Microbiology Conference
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• 2001.06a
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• pp.15-19
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• 2001

Creating an artificial strain with a minimal gene set for a specific purpose is every biologist's dream. With the complete genome sequencing of more than 50 microorganisms and extensive functional analyses of their genes, it is possible to design a genetic blueprint for a simple custom-designed microbe with the minimal gene set. Two different approaches are being considered. The first 'top-down' approach is trimming the genome to a minimal gene set by selectively removing genes of an organism thought to be unnecessary based on microbial genomics. The second 'bottom-up' approach is to synthesize the proposed minimal genome from basic chemical building blocks. The 'top-down' approach starting with the genome of a well known microorganism is more technically feasible, whereas the bottom-up approach may not be attainable in the nearest future because of the lack of the complete functional analysis of the genes needed for a life. Here in this study, we used the top-down approach to minimize the E. coli genome to create an artificial organism with 'core' elements for self-sustaining and self-replicating cells by eliminating unnecessary genes. Using several different kinds of sophisticated deletion techniques combined with a p:1age and transposons, we deleted about 19％ of the E. coli genome without causing any damages to cellular growth. This smaller E. coli genome will be further reduced to a genome with a minimal gene l;et essential for cell life. This minimized E. coli genome can lead to the construction of many custom-designed strains with myriad practical and commercial applications.

• Journal of Digital Contents Society
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• v.11 no.1
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• pp.99-104
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• 2010

Numerous bio-digital contents have been produced by new technology using biochip and others for analyzing early chemical-induced genes. These contents have little meaning by themselves, and so they should be modified and extracted after consideration of biological meaning. These include genomics, transcriptomics, protenomics, metabolomics, which combined into omics. Omics tools could be applied into toxicology, forming a new field of toxicogenomics. It is possible that approach of toxicogenomics can estimate toxicity more quickly and accurately by analyzing gene/protein/metabolite profiles. These approaches should help not only to discover highly sensitive and predictive biomarkers but also to understand molecular mechanism(s) of toxicity, based on the development of analysing technology. Furthermore, it is important that bio-digital contents should be obtained from specific cells having biological events more than from whole cells. Taken together, many bio-digital contents should be analyzed by careful calculating algorism under well-designed experimental protocols, network analysis using computational algorism and related profound databases.