• Genomics & Informatics
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• v.11 no.4
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• pp.200-210
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• 2013

Studying biological networks, such as protein-protein interactions, is key to understanding complex biological activities. Various types of large-scale biological datasets have been collected and analyzed with high-throughput technologies, including DNA microarray, next-generation sequencing, and the two-hybrid screening system, for this purpose. In this review, we focus on network-based approaches that help in understanding biological systems and identifying biological functions. Accordingly, this paper covers two major topics in network biology: reconstruction of gene regulatory networks and network-based applications, including protein function prediction, disease gene prioritization, and network-based genome-wide association study.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2002.06a
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• pp.5-23
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• 2002

Motivation: Protein-protein interaction plays a critical role in the biological processes. The identification of interacting proteins by bioinformatical methods can provide new lead In the functional studies of uncharacterized proteins without performing extensive experiments. Results: Protein-protein interactions are predicted by a computational algorithm based on the weighted scoring system for domain interactions between interacting protein pairs. Here we propose potential interaction domain (PID) pairs can be extracted from a data set of experimentally identified interacting protein pairs. where one protein contains a domain and its interacting protein contains the other. Every combinations of PID are summarized in a matrix table termed the PID matrix, and this matrix has proposed to be used for prediction of interactions. The database of interacting proteins (DIP) has used as a source of interacting protein pairs and InterPro, an integrated database of protein families, domains and functional sites, has used for defining domains in interacting pairs. A statistical scoring system. named "PID matrix score" has designed and applied as a measure of interaction probability between domains. Cross-validation has been performed with subsets of DIP data to evaluate the prediction accuracy of PID matrix. The prediction system gives about 50% of sensitivity and 98% of specificity, Based on the PID matrix, we develop a system providing several interaction information-finding services in the Internet. The system, named PreDIN (Prediction-oriented Database of Interaction Network) provides interacting domain finding services and interacting protein finding services. It is demonstrated that mapping of the genome-wide interaction network can be achieved by using the PreDIN system. This system can be also used as a new tool for functional prediction of unknown proteins.

• Proceeding of EDISON Challenge
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• 2016.03a
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• pp.163-166
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• 2016

Hydrophobicity is the key concept to understand the water plays in protein folding, protein aggregation, and protein-protein interaction. Traditionally, the hydrophobicity of protein is defined based on the scales of the hydrophobicity of residue, assuming that the hydrophobicity of free amino acids is maintained. Here, we explore how the hydrophobicity of constituting amino acids in protein rely on the protein context, in particular, on the total charge and secondary structures of a protein. To this end, we calculate and investigate the hydration free energy of three short proteins based on the integral-equation theory of liquids. We find that the hydration free energy of charged amino acids is significantly affected by the protein total charge and exhibits contrasting behavior depending on the protein total charge being positive or negative. We also observe that amino acids in the ${\beta}-sheets$ display more enhanced the hydrophobicity than amino acids in the loop, whereas those in the ${\alpha}-helix$ do not clearly show such a tendency. And the salt-bridge forming amino acids also exhibit increase of the hydrophobicity than that with no salt bridge. Our results provide novel insights into the hydrophobicity of amino acids, and will be valuable for rationalizing and predicting the strength of water-mediated interaction involved in the biological activity of proteins.

• International Journal of Contents
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• v.9 no.4
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• pp.11-15
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• 2013

"Protein Folding Problem" is considered to be one of the "Great Challenges of Computer Science" and prediction of disordered protein is an important part of the protein folding problem. Machine learning models can predict the disordered structure of protein based on its characteristic of "learning from examples". Among many machine learning models, we investigate the possibility of multilayer perceptron (MLP) as the predictor of protein disorder. The investigation includes a single hidden layer MLP, multi hidden layer MLP and the hierarchical structure of MLP. Also, the target node cost function which deals with imbalanced data is used as training criteria of MLPs. Based on the investigation results, we insist that MLP should have deep architectures for performance improvement of protein disorder prediction.

• Korean Journal of Veterinary Service
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• v.42 no.2
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• pp.73-83
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• 2019

Foot-and-Mouth Disease (FMD) is a highly contagious trans-boundary viral disease caused by FMD virus, which causes huge economic losses. FMDV infects cloven hoofed (two-toed) mammals such as cattle, sheep, goats, pigs and various wildlife species. To control the FMDV, it is necessary to understand the life cycle and the pathogenesis of FMDV in host. Especially, the protein-protein interaction between FMDV and host will help to understand the survival cycle of viruses in host cell and establish new therapeutic strategies. However, the computational approach for protein-protein interaction between FMDV and pig hosts have not been applied to studies of the onset mechanism of FMDV. In the present work, we have performed the prediction of the pig's proteins which interact with FMDV based on RNA-Seq data, protein sequence, and structure information. After identifying the virus-host interaction, we looked for meaningful pathways and anticipated changes in the host caused by infection with FMDV. A total of 78 proteins of pig were predicted as interacting with FMDV. The 156 interactions include 94 interactions predicted by sequence-based method and the 62 interactions predicted by structure-based method using domain information. The protein interaction network contained integrin as well as STYK1, VTCN1, IDO1, CDH3, SLA-DQB1, FER, and FGFR2 which were related to the up-regulation of inflammation and the down-regulation of cell adhesion and host defense systems such as macrophage and leukocytes. These results provide clues to the knowledge and mechanism of how FMDV affects the host cell.

• Asian-Australasian Journal of Animal Sciences
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• v.5 no.1
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• pp.107-112
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• 1992

Feeding of bypass protein to lactating animals have been suggested by many research scientists as a way to increase the nutrient supply at the intestinal level thereby enhance animal production in ruminant animals. A feeding trial with a formulated bypass protein feed on straw based ration was carried out by using lactating cross bred cows at the stage of 4th month of their lactation. Bypass protein feed was fed at 5 different levels. Urea Molasses Block was used as a nitrogen source to the rumen microflora. In order to reduce the heat increment straw intake was restricted to all the animals. Urea Molasses Block intake was noticed varying in proportion with the bypass protein feed intake. Milk production was observed increasing in accordance with the level of bypass protein feed intake. However, the maximum response was noticed in cows that were fed 3 kg bypass protein feed. The nutrient availability at this stage was below the NRC (1988) requirements. Other remarkable finding was that the cows maintained the persistency of milk production even after 3rd month of lactation when the ambient temperature was $40^{\circ}C$.

• Proceeding of EDISON Challenge
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• 2014.03a
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• pp.103-113
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• 2014

Hydrophobicity is the key concept to understand the role of water in protein folding, protein self-assembly, and protein-ligand interaction. Conventionally, hydrophobicity of amino acids in a protein has been argued based on hydrophobicity scales determined for individual free amino acids, assuming that those scales are unaltered when amino acids are embedded in a protein. Here, we investigate how the hydrophobicity of constituent amino acids depends on the protein context, in particular, on the total charge and secondary structures of a protein. To this end, we compute and analyze the hydration free energy - free energy change upon hydration quantifying the hydrophobicity - of three short proteins based on the integral-equation theory of liquids. We find that the hydration free energy of charged amino acids is significantly affected by the protein total charge and exhibits contrasting behavior depending on the protein net charge being positive or negative. We also observe that amino acids in the central ${\beta}$-strand sandwiched by ${\beta}$-sheets display more enhanced hydrophobicity than free amino acids, whereas those in the ${\alpha}$-helix do not clearly show such a tendency. Our results provide novel insights into the hydrophobicity of amino acids, and will be valuable for rationalizing and predicting the strength of water-mediated interaction involved in the biological activity of proteins.

• Food Science of Animal Resources
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• v.41 no.5
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• pp.855-868
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• 2021

The present study was designed to investigate the effects of protein formula with different casein (C) to whey protein (W) ratios on dispersion stability, protein quality and body composition in rats. Modification of the casein to whey protein (CW) ratio affected the extent of protein aggregation, and heated CW-2:8 showed a significantly increased larger particle (>100 ㎛) size distribution. The largest protein aggregates were formed by whey protein self-aggregation. There were no significant differences in protein aggregation when the CW ratios changed from 10:0 to 5:5. Based on the protein quality assessment (CW-10:0, CW-8:2, CW-5:5, and CW-2:8) for four weeks, CW-10:0 showed a significantly higher feed intake (p<0.05), but the high proportion of whey protein in the diet (CW-5:5 and CW-2:8) increased the feed efficiency ratio, protein efficiency ratio, and net protein ratio compared to other groups. Similarly, CW-2:8 showed greater true digestibility compared to other groups. No significant differences in fat mass and lean mass analyzed by dual-energy x-ray absorptiometry were observed. A significant difference was found in the bone mineral density between the CW-10:0 and CW-2:8 groups (p<0.05), but no difference was observed among the other groups. Based on the results, CW-5:5 improved protein quality without causing protein instability problems in the dispersion.

• Nutrition Research and Practice
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• v.17 no.5
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• pp.1028-1041
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• 2023

BACKGROUND/OBJECTIVES: This study aimed to analyze the potential of school meals in South Korea as a sustainable tool to reduce carbon emissions by focusing on animal- vs. plant-based protein foods. MATERIALS/METHODS: By using a stratified proportional allocation method, 536 out of the 11,082 schools nationwide were selected including 21 kindergartens, 287 elementary-, 120 middle- and 108 high schools. A total of 2,680 meals served for 5 consecutive days (June 21-25, 2021) were collected. We analyzed the average serving amounts of protein foods (animal- vs. plant-based) per meal and then, calculated the estimated average amounts of carbon emission equivalents per meal by applying the conversion coefficients. The t-test and analysis of variance were used for statistical analyses (α = 0.05). RESULTS: The average serving amount of animal-based protein foods per meal was 12.5 g, which was approximately 3 times higher than that of plant-based ones (3.8 g) (P < 0.001); the Meat-group had the highest average amount of 17.0 g, followed by Egg-group (9.6 g), Fish-group (7.6 g), and Beans-and-Nuts-group (3.8 g) (P < 0.05). Specifically, pork (25.1 g) was ranked first, followed by poultry (19.6 g), processed meat products (18.0 g). The estimated average amount of carbon emission equivalents of animal-based protein foods per meal was 80.1 g CO₂e, which was approximately 31 times higher than that of plant-based ones (2.6 g CO₂e) (P < 0.001); the Meat-group had the highest average amount of 120.3 g CO₂e, followed by Fish-group (44.5 g CO₂e), Egg-group (25.9 g CO₂e), and Beans-and-Nuts-group (2.6 g CO₂e) (P < 0.05). Specifically, processed meat products (270.8 g CO₂e) were ranked first, followed by pork (91.7 g CO₂e), and processed fish products (86.6 g CO₂e). CONCLUSIONS: The results implied that school meals with plant-based alternatives could be a sustainable tool to improve carbon footprint.

• Genomics & Informatics
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• v.16 no.4
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• pp.23.1-23.5
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• 2018

Virus taxonomy was initially determined by clinical experiments based on phenotype. However, with the development of sequence analysis methods, genotype-based classification was also applied. With the development of genome sequence analysis technology, there is an increasing demand for virus taxonomy to be extended from in vivo and in vitro to in silico. In this study, we verified the consistency of the current International Committee on Taxonomy of Viruses taxonomy using an in silico approach, aiming to identify the specific sequence for each virus. We applied this approach to norovirus in Caliciviridae, which causes 90% of gastroenteritis cases worldwide. First, based on the dogma "protein structure determines its function," we hypothesized that the specific sequence can be identified by the specific structure. Firstly, we extracted the coding region (CDS). Secondly, the CDS protein sequences of each genus were annotated by the conserved domain database (CDD) search. Finally, the conserved domains of each genus in Caliciviridae are classified by RPS-BLAST with CDD. The analysis result is that Caliciviridae has sequences including RNA helicase in common. In case of Norovirus, Calicivirus coat protein C terminal and viral polyprotein N-terminal appears as a specific domain in Caliciviridae. It does not include in the other genera in Caliciviridae. If this method is utilized to detect specific conserved domains, it can be used as classification keywords based on protein functional structure. After determining the specific protein domains, the specific protein domain sequences would be converted to gene sequences. This sequences would be re-used one of viral bio-marks.