• Preventive Nutrition and Food Science
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• v.17 no.3
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• pp.223-227
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• 2012

This study examined the effects of corn gluten (CG), wheat gluten (WG), and soybean protein isolate (SPI), as well as their hydrolysates, on weight reduction in rats fed a high-fat diet. Eight-month-old male Sprague-Dawley rats (n=70) were fed a high-fat diet (40% of the calories were fat) for 4 weeks. Rats were then randomly divided into seven groups and were fed isocaloric diets with different protein sources for 8 weeks. The protein sources were casein (control group), intact CG (CG group), CG hydrolysate (CGH group), intact WG (WG group), WG hydrolysate (WGH group), intact SPI (SPI group), and SPI hydrolysate (SPIH group). Body weight gain, adipose tissue weights, lipid profiles in plasma and liver; and hepatic activities of carnitine palmitoyl transferase, fatty acid synthase (FAS), malic enzyme, and glucose-6-phosphate dehydrogenase were assessed. The CGH group showed significant weight reduction compared with the other groups. Epididymal fat pad and plasma triglycerides in the CGH group were the lowest and were significantly different than those in the control group. FAS activity in the CGH group was significantly lower than that in the other groups. In conclusion, the CGH diet of these experimental animals demonstrated a weight-reducing effect by lowering the adipose tissue weight and by affecting the activities of hepatic lipogenic enzymes.

• The KIPS Transactions:PartB
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• v.13B no.3 s.106
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• pp.323-328
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• 2006

Proteins in a cell appear as spots in a two dimensional gel image which is used in protein analysis. The spots from the same protein are in near position when comparing two gel images. Finding out the different proteins between a normal tissue and a cancer one is important information in drug development. Automatic matching of gel images is difficult because they are made from biological experimental processes. This matching problem is known to be NP-hard. Neural networks are usually used to solve such NP-hard problems. Hopfield neural network is selected since it is appropriate to solve the gel matching. An energy function with location and distance parameters is defined. The two spots which make the energy function minimum are matching spots and they came from the same protein. The energy function is designed to reflect the topology of spots by examining not only the given spot but also neighborhood spots.

• BMB Reports
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• v.35 no.2
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• pp.213-219
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• 2002

Malonyl-CoA decarboxylase (E.C.4.1.1.9) catalyzes the conversion of malonyl-CoA to acetyl-CoA. Although the metabolic role of this enzyme has not been fully defined, it has been reported that its deficiency is associated with mild mental retardation, seizures, hypotonia, cadiomyopathy, developmental delay, vomiting, hypoglycemia, metabolic acidosis, and malonic aciduria. Here, we isolated a cDNA clone for malonyl CoA decarboxylase from a rat brain cDNA library, expressed it in E. coli, and characterized its biochemical properties. The full-length cDNA contained a single open-reading frame that encoded 491 amino acid residues with a calculated molecular weight of 54, 762 Da. Its deduced amino acid sequence revealed a 65.6% identity to that from the goose uropigial gland. The sequence of the first 38 amino acids represents a putative mitochondrial targeting sequence, and the last 3 amino acid sequences (SKL) represent peroxisomal targeting ones. The expression of malonyl CoA decarboxylase was observed over a wide range of tissues as a single transcript of 2.0 kb in size. The recombinant protein that was expressed in E. coli was used to characterize the biochemical properties, which showed a typical Michaelis-Menten substrate saturation pattern. The $K_m$ and $V_{max}$ were calculated to be $68\;{\mu}M$ and $42.6\;{\mu}mol/min/mg$, respectively.

• Korean Journal of Exercise Nutrition
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• v.25 no.3
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• pp.28-35
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• 2021

[Purpose] As Panax ginseng C. A. Meyer (ginseng) exhibits various physiological activities and is associated with exercise, we investigated the potential active components of ginseng and related target genes through network pharmacological analysis. Additionally, we analyzed the association between ginseng-related genes, such as the G-protein-coupled receptors (GPCRs), and improved exercise capacity. [Methods] Active compounds in ginseng and the related target genes were searched in the Traditional Chinese Medicine Database and Analysis Platform (TCMSP). Gene ontology functional analysis was performed to identify biological processes related to the collected genes, and a compound-target network was visualized using Cytoscape 3.7.2. [Results] A total of 21 ginseng active compounds were detected, and 110 targets regulated by 17 active substances were identified. We found that the active compound protein was involved in the biological process of adrenergic receptor activity in 80%, G-protein-coupled neurotransmitter in 10%, and leucocyte adhesion to arteries in 10%. Additionally, the biological response centered on adrenergic receptor activity showed a close relationship with G protein through the beta-1 adrenergic receptor gene reactivity. [Conclusion] According to bioavailability analysis, ginseng comprises 21 active compounds. Furthermore, we investigated the ginseng-stimulated gene activation using ontology analysis. GPCR, a gene upregulated by ginseng, is positively correlated to exercise. Therefore, if a study on this factor is conducted, it will provide useful basic data for improving exercise performance and health.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2003.10a
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• pp.164-169
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• 2003

In this paper, we propose the integrated Bayesian network framework to reconstruct genetic regulatory networks from genome expression data. The proposed model overcomes the dimensionality problem of multivariate analysis by building coherent sub-networks from confined gene clusters and combining these networks via intermediary points. Gene Shaving algorithm is used to cluster genes that share a common function or co-regulation. Retrieved clusters incorporate prior biological knowledge such as Gene Ontology, pathway, and protein protein interaction information for extracting other related genes. With these extended gene list, system builds genetic sub-networks using Bayesian network with MDL score and Sparse Candidate algorithm. Identifying functional modules of genes is done by not only microarray data itself but also well-proved biological knowledge. This integrated approach can improve there liability of a network in that false relations due to the lack of data can be reduced. Another advantage is the decreased computational complexity by constrained gene sets. To evaluate the proposed system, S. Cerevisiae cell cycle data [1] is applied. The result analysis presents new hypotheses about novel genetic interactions as well as typical relationships known by previous researches [2].

• Review of Korea Contents Association
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• v.7 no.4
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• pp.12-18
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• 2009

• The Korea Genome Conference
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• 2004.07a
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• pp.35.2-35.2
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• 2004

• BMB Reports
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• v.33 no.5
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• pp.370-378
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• 2000

Incubation of purified laminin1-nidogen1 complexes with $[{\gamma}-^{32}P]-ATP$ in the presence of the catalytic subunit of the protein kinase A (cAMP-dependent protein kinase) resulted in the phosphorylation of the alpha chain of laminin-1 and of the nidogen-1 molecule. Aminoacid electrophoresis indicated that phosphate was incorporated on serine residues. The phosphorylation effect of laminin-1 on the process of self assembly was studied by turbidometry. In these experiments, the phosphorylated laminin-1 showed a reduced maximal aggregation capacity in comparison to the non-phosphorylated molecule. Examination of the laminin-1 network under the electron microscope showed that the phosphorylated sample formed mainly linear extended oligomers, in contrast to controls that formed large and dense multimeric aggregates. Heparin binding on phosphorylated laminin-1 in comparison to controls was also tested using solid-phase binding assays. The results indicated an enhanced heparin binding to the phosphorylated protein. The results of this study indicate that laminin1-nidogen1 is a substrate for protein kinase A in vitro. This phosphorylation had an obvious influence on the lamininl-nidogen1 network formation and the heparin binding capacity of this molecule. However, further studies are needed to investigate whether or not this phenomenon could play a role in the formation of the structure of basement membranes in vivo.

• Molecules and Cells
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• v.39 no.9
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• pp.692-698
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• 2016

Advances in next generation sequencing (NGS) technologies have enabled population-level studies for many animals to unravel the relationships between genotypic differences and traits of specific populations. The objective of this study was to perform evolutionary analysis of single nucleotide polymorphisms (SNP) in genes of Korean native cattle Hanwoo in comparison to SNP data from four other cattle breeds (Jersey, Simmental, Angus, and Holstein) and four related species (pig, horse, human, and mouse) obtained from public databases through NGS-based resequencing. We analyzed population structures and differentiation levels for the five cattle breeds and estimated species-specific SNPs with their origins and phylogenetic relationships among species. In addition, we identified Hanwoo-specific genes and proteins, and determined distinct changes in protein-protein interactions among five species (cattle, pig, horse, human, mouse) in the STRING network database by additionally considering indirect protein interactions. We found that the Hanwoo population was clearly different from the other four cattle populations. There were Hanwoo-specific genes related to its meat trait. Protein interaction rewiring analysis also confirmed that there were Hanwoo-specific protein-protein interactions that might have contributed to its unique meat quality.

• BMB Reports
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• v.54 no.9
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• pp.464-469
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• 2021

Cardiomyocyte differentiation occurs through complex and finely regulated processes including cardiac lineage commitment and maturation from pluripotent stem cells (PSCs). To gain some insight into the genome-wide characteristics of cardiac lineage commitment, we performed transcriptome analysis on both mouse embryonic stem cells (mESCs) and human induced PSCs (hiPSCs) at specific stages of cardiomyocyte differentiation. Specifically, the gene expression profiles and the protein-protein interaction networks of the mESC-derived platelet-derived growth factor receptor-alpha (PDGFRα)⁺ cardiac lineage-committed cells (CLCs) and hiPSC-derived kinase insert domain receptor (KDR)⁺ and PDGFRα⁺ cardiac progenitor cells (CPCs) at cardiac lineage commitment were compared with those of mesodermal cells and differentiated cardiomyocytes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses revealed that the genes significantly upregulated at cardiac lineage commitment were associated with responses to organic substances and external stimuli, extracellular and myocardial contractile components, receptor binding, gated channel activity, PI3K-AKT signaling, and cardiac hypertrophy and dilation pathways. Protein-protein interaction network analysis revealed that the expression levels of genes that regulate cardiac maturation, heart contraction, and calcium handling showed a consistent increase during cardiac differentiation; however, the expression levels of genes that regulate cell differentiation and multicellular organism development decreased at the cardiac maturation stage following lineage commitment. Additionally, we identified for the first time the protein-protein interaction network connecting cardiac development, the immune system, and metabolism during cardiac lineage commitment in both mESC-derived PDGFRα⁺ CLCs and hiPSC-derived KDR⁺PDGFRα⁺ CPCs. These findings shed light on the regulation of cardiac lineage commitment and the pathogenesis of cardiometabolic diseases.