• Genomics & Informatics
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• v.7 no.2
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• pp.65-84
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• 2009

Sequences from the clones of full-length enriched cDNA libraries serve as valuable resources for functional genomics related studies, genome annotation and SNP discovery. We analyzed 7,392 high-quality chromatograms (Phred value ${\geq}$30) obtained from sequencing the 5' ends of clones derived from full-length enriched cDNA libraries of Korean native pigs including brainstem, liver, cerebellum, neocortex and spleen libraries. In addition, 50,000 EST sequence trace files obtained from GenBank were combined with our sequences to identify cSNPs in silico. The process generated 11,324 contigs, of which 2,895 contigs contained at least one SNP and among them 610 contigs had a minimum of one sequence from Korean native pigs. Of 610 contigs, we randomly selected 262 contigs and performed in silico analysis for the identification of cSNPs. From the results, we identified 1,531 putative coding single nucleotide polymorphisms (cSNPs) and the SNP detection frequency was one SNP per 465 bp. A large-scale sequencing result of clones from full-length enriched cDNA libraries and identified cSNPs will serve as a useful resource to functional genomics related projects such as a pig HapMap project in the near future.

• 한국생물공학회:학술대회논문집
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• 2003.10a
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• pp.783-784
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• 2003

• 한국생물공학회:학술대회논문집
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• 2005.10a
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• pp.793-794
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• 2005

• 한국생물공학회:학술대회논문집
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• 2005.10a
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• pp.595-595
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• 2005

• Molecular & Cellular Toxicology
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• v.3 no.sup4
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• pp.37.4-37.4
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• 2007

• Journal of Life Science
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• v.12 no.5
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• pp.610-621
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• 2002

Conserved genes are importantly used to understand the major function in survival and replication of living organism. This study was focused on identification of conserved genes in microbial species and measuring the degree of conservation. For this purpose, in silico analysis was performed to search conserved genes based on the conservation level within microbial species. The ortholog list of COGs (Clusters of Orthologous Groups of proteins) in NCBI was used and whole genomes of 43 microbial species were included in that list. The distance value, derived from CLUSTALW multiple alignment program, was used as a descriptor of the conservation level of orthologs. It was revealed that 43 microbial genomes hold 72 conserved orthologs in common. The majority(72.2%) of the conserved genes was related to "translation, ribosomal structure and biogenesis" functional category. A GTPase-translation elogation factor(COG0050) was the best conserved gene from the distance value analysis. The 72 conserved genes, found in this research, would be useful not only to study minimal function genes but also new drug target among pathogens and to make a model of the virtual cell.tual cell.

• Biotechnology and Bioprocess Engineering:BBE
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• v.10 no.5
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• pp.425-431
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• 2005

The systems-level analysis of microbes with myriad of heterologous data generated by omics technologies has been applied to improve our understanding of cellular function and physiology and consequently to enhance production of various bioproducts. At the heart of this revolution resides in silico genome-scale metabolic model, In order to fully exploit the power of genome-scale model, a systematic approach employing user-friendly software is required. Metabolic flux analysis of genome-scale metabolic network is becoming widely employed to quantify the flux distribution and validate model-driven hypotheses. Here we describe the development of an upgraded MetaFluxNet which allows (1) construction of metabolic models connected to metabolic databases, (2) calculation of fluxes by metabolic flux analysis, (3) comparative flux analysis with flux-profile visualization, (4) the use of metabolic flux analysis markup language to enable models to be exchanged efficiently, and (5) the exporting of data from constraints-based flux analysis into various formats. MetaFluxNet also allows cellular physiology to be predicted and strategies for strain improvement to be developed from genome-based information on flux distributions. This integrated software environment promises to enhance our understanding on metabolic network at a whole organism level and to establish novel strategies for improving the properties of organisms for various biotechnological applications.

• Journal of the Korean Chemical Society
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• v.68 no.3
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• pp.151-159
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• 2024

Indian spices are well known for their numerous health benefits, flavour, taste, and colour. Recent Advancements in chemical technology have led to better extraction and identification of bioactive molecules (phytochemicals) from spices. The therapeutic effects of spices against diabetes, cardiac problems, and various cancers has been well established. The present in silico study aims to investigate the binding affinity of 29 phytochemicals from 11 Indian spices with two prominent proteins, BCL3 and CXCL10 involved in invasiveness and bone metastasis of breast cancer. The three-dimensional structures of 29 phytochemicals were extracted from PubChem database. Protein Data Bank was used to retrieve the 3D structures of BCL3 and CXCL10 proteins. The drug-likeness and other properties of compounds were analysed by ADME and Lipinski rule of five (RO5). All computational simulations were carried out using Autodock 4.0 on Windows platform. The proteins were set to be rigid and compounds were kept free to rotate. In-silico study demonstrated a strong complex formation (positive binding constants and negative binding energy ΔG) between all phytochemicals and target proteins. However, piperine and sesamolin demonstrated high binding constants with BCL3 (50.681 × 10³ mol^-1, 137.76 × 10³ mol^-1) and CXCL10 (98.71 × 10³ mol^-1, 861.7 × 10³ mol^-1), respectively. The potential of these two phytochemicals as a drug candidate was highlighted by their binding energy of -6.5 kcal mol^-1, -7.1 kcal mol^-1 with BCL3 and -6.9 kcal mol^-1, -8.2 kcal mol^-1 with CXCL10, respectively coupled with their favourable drug likeliness and pharmacokinetics properties. These findings underscore the potential of piperine and sesamolin as drug candidates for inhibiting invasiveness and regulating breast cancer metastasis. However, further validation through in vitro and in vivo studies is necessary to confirm the in silico results and evaluate their clinical potential.

• Journal of Life Science
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• v.28 no.3
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• pp.307-313
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• 2018

Alopecia cause psychological stress due to their effect on appearance. Thus, the global market size of the alopecia treatment products are growing quickly. Timosaponin A III is the well known active ingredient of Anemarrhenae Rhizoma. In this study, we investigated and compared the binding affinity of timosaponin A III with finasteride (5-beta reductase antagonist) and minoxidil (androgen receptor antagonist) on the target protein active site by in silico computational docking studies. The three dimensional crystallographic structure of 5-beta reductase (PDB ID : 3G1R) and androgen receptor (PDB ID: 4K7A) was obtained from PDB database. In silico computational autodocking analysis was performed using PyRx, Autodock Vina, Discovery Studio Version 4.5, and NX-QuickPharm option based on scoring functions. The timosaponin A III showed optimum binding affinity (docking energy) with 5-beta reductase as -12.20 kcal/mol as compared to the finasteride (-11.70 kcal/mol) and with androgen receptor as -9.00 kcal/mol as compared to the minoxidil (-7.40 kcal/mol). The centroid X, Y, Z grid position of the timosaponin A III on the 5-beta reductase was similar (overlap) to the finasteride, but the X, Y, Z centroid grid of the timosaponin A III on the androgen receptor was significantly far from the minoxidil centroid position. These results significantly indicated that timosaponin A III could be more potent antagonist to the 5-beta reductase and androgen receptor. Therefore, the extract of Anemarrhenae Rhizoma or timosaponin A III containing biomaterials can substitute the finasteride and minoxidil and can be applied to the alopecia protecting product and related industrial fields.

• Toxicological Research
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• v.32 no.1
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• pp.15-20
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• 2016

Physiologically based pharmacokinetic (PBPK) modeling can provide an effective way to utilize in vitro and in silico based information in modern risk assessment for children and other potentially sensitive populations. In this review, we describe the process of in vitro to in vivo extrapolation (IVIVE) to develop PBPK models for a chemical in different ages in order to predict the target tissue exposure at the age of concern in humans. We present our on-going studies on pyrethroids as a proof of concept to guide the readers through the IVIVE steps using the metabolism data collected either from age-specific liver donors or expressed enzymes in conjunction with enzyme ontogeny information to provide age-appropriate metabolism parameters in the PBPK model in the rat and human, respectively. The approach we present here is readily applicable to not just to other pyrethroids, but also to other environmental chemicals and drugs. Establishment of an in vitro and in silico-based evaluation strategy in conjunction with relevant exposure information in humans is of great importance in risk assessment for potentially vulnerable populations like early ages where the necessary information for decision making is limited.