• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.11a
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• pp.668-669
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• 2008

In this paper, we introduce various coarse-grained elastic network modeling (ENM) techniques as a novel computational method for simulating atomic scale dynamics in macromolecules including DNA, RNA, protein, and polymer. In ENM, a system is modeled as a spring network among representative atoms in which each linear elastic spring is well designed to replace both bonded and nonbonded interactions among atoms in the sense of quantum mechanics. Based on this simplified system, a harmonic Hookean potential is defined and used for not only calculating intrinsic vibration modes of a given system, but also predicting its anharmonic conformational change, both of which are strongly related with its functional features. Various nano and bio applications of ENM such as fracture mechanics of nanocomposite and protein dynamics show that ENM is one of promising tools for simulating atomic scale dynamics in a more effective and efficient way comparing to the traditional molecular dynamics simulation.

• BMB Reports
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• v.45 no.4
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• pp.213-220
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• 2012

Viruses have evolved to manipulate the host cell machinery for virus propagation, in part by interfering with the host cellular signaling network. Molecular studies of individual pathways have uncovered many viral host-protein targets; however, it is difficult to predict how viral perturbations will affect the signaling network as a whole. Systems biology approaches rely on multivariate, context-dependent measurements and computational analysis to elucidate how viral infection alters host cell signaling at a network level. Here we describe recent advances in systems analyses of signaling networks in both viral and non-viral biological contexts. These approaches have the potential to uncover virus- mediated changes to host signaling networks, suggest new therapeutic strategies, and assess how cell-to-cell variability affects host responses to infection. We argue that systems approaches will both improve understanding of how individual virus-host protein interactions fit into the progression of viral pathogenesis and help to identify novel therapeutic targets.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.4
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• pp.508-518
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• 2019

Objective: This research aimed to determine biological pathways and protein-protein interaction (PPI) networks for 305-d milk yield (MY), 305-d fat yield (FY), and age at first calving (AFC) in the Thai multibreed dairy population. Methods: Genotypic information contained 75,776 imputed and actual single nucleotide polymorphisms (SNP) from 2,661 animals. Single-step genomic best linear unbiased predictions were utilized to estimate SNP genetic variances for MY, FY, and AFC. Fixed effects included herd-year-season, breed regression and heterosis regression effects. Random effects were animal additive genetic and residual. Individual SNP explaining at least 0.001% of the genetic variance for each trait were used to identify nearby genes in the National Center for Biotechnology Information database. Pathway enrichment analysis was performed. The PPI of genes were identified and visualized of the PPI network. Results: Identified genes were involved in 16 enriched pathways related to MY, FY, and AFC. Most genes had two or more connections with other genes in the PPI network. Genes associated with MY, FY, and AFC based on the biological pathways and PPI were primarily involved in cellular processes. The percent of the genetic variance explained by genes in enriched pathways (303) was 2.63% for MY, 2.59% for FY, and 2.49% for AFC. Genes in the PPI network (265) explained 2.28% of the genetic variance for MY, 2.26% for FY, and 2.12% for AFC. Conclusion: These sets of SNP associated with genes in the set enriched pathways and the PPI network could be used as genomic selection targets in the Thai multibreed dairy population. This study should be continued both in this and other populations subject to a variety of environmental conditions because predicted SNP values will likely differ across populations subject to different environmental conditions and changes over time.

• BMB Reports
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• v.34 no.1
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• pp.33-38
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• 2001

The human PTK6 (also known as Brk) polypeptide, which is deduced from its full-length cDNA, represents a non-receptor protein tyrosine kinase (PTK). It contains SH3, SH2, and tyrosine kinase catalytic domains that are closely related to Src family members. We generated an antihuman PTK6 antibody by immunizing rabbits with a PTK6-specific oligopeptide conjugated to BSA, which corresponds to 11 amino acid residues near the C-terminus. An immunoblot analysis with the antibody detected an expected 52-kDa band in various mammalian transformed cell lines. Immunoprecipitation and immunoblot analyses demonstrated that PTK6 is phosphorylated on the tyrosine residues) and interacts with approximately a 23-kDa tyrosine-phosphorylated polypeptide (most likely a substrate of PTK6) in breast carcinoma T-47D cells. An immunofluorescence analysis demonstrated that PTK6 is localized throughout the cytoplasm of T-47D cells. These results support a possible role for PTK6 in the intracellular signal transduction through tyrosine phosphorylation.

• Journal of Microbiology and Biotechnology
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• v.16 no.6
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• pp.911-920
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• 2006

[ $CD8^+$ ] T Iymphocytes with the cytotoxic activity and capability to release various cytokines are the major players in immune responses against viral infection and cancer. To identify the proteins specific to resting or activated human CD8$^+$ T cells, human CD8$^+$ T cells were activated with anti-CD3+anti-CD28 mAb in the presence of IL-2. The solubilized proteins from resting and activated human CD8$^+$ T cells were separated by high-resolution two-dimensional polyacrylamide gel electrophoresis, and their proteomes were analyzed. Proteomic analysis of resting and activated T cells resulted in identification of 35 proteins with the altered expression. Mass spectrometry coupled with Profound and SWISS-PROT database analysis revealed that these identified proteins are to be functionally associated with cell proliferation, metabolic pathways, antigen presentation, and intracellular signal transduction pathways. We also identified six unknown proteins predicted from genomic DNA sequences specific to resting or activated CD8$^+$ T cells. Protein network studies and functional characterization of these novel proteins may provide new insight into the signaling transduction pathway of CD8$^+$ T cell activation.

• BMB Reports
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• v.36 no.6
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• pp.552-557
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• 2003

Oligomers with $\alpha$-aminooxy acids are reported to form very stable turn and helix structures, and they are supposed to be useful peptidomimetics for drug design. A recent report suggested that homochiral oxa-peptides form a strong eight-member-ring structure by a hydrogen bond between adjacent aminooxy-acid residues in a $CDCl_3$ solution. In order to design an $\alpha$-MSH analog with a stable turn conformation, we synthesized four tetramers and one pentamer, based on $\alpha$-MSH sequence, and determined the solution structures of the molecules by two-dimensional NMR spectroscopy and simulated annealing calculations. The solution conformations of the three peptidomimetic molecules (TLV, TDV, and TLL) in DMSO-$d_6$ contain a stable 7-membered-ring structure that is similar to a $\gamma$-turn in normal peptides. Newly-designed tetramer TDF and pentamer PDF have a ball-type rigid structure that is induced by strong hydrogen bonds between adjacent amide protons and carbonyl oxygens. In conclusion, the aminooxy acids, easily prepared from natural or unnatural amino acids, can be employed to prepare peptidomimetic analogues with well-defined turn structures for pharmaceutical interest.

• Genomics & Informatics
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• v.21 no.2
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• pp.23.1-23.9
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• 2023

The mammalian sirtuin family, consisting of SIRT1-SIRT7, plays a vital role in various biological processes, including cancer, diabetes, neurodegeneration, cardiovascular disease, cellular metabolism, and cellular homeostasis maintenance. Due to their involvement in these biological processes, modulating sirtuin activity seems promising to impact immuneand aging-related diseases, as well as cancer pathways. However, more understanding is required regarding the safety and efficacy of sirtuin-targeted therapies due to the complex regulatory mechanisms that govern their activity, particularly in the context of multiple targets. In this study, the interaction landscape of the sirtuin family was analyzed using a systems biology approach. A sirtuin protein-protein interaction network was built using the Cytoscape platform and analyzed using the NetworkAnalyzer and stringApp plugins. The result revealed the sirtuin family's association with numerous proteins that play diverse roles, suggesting a complex interplay between sirtuins and other proteins. Based on network topological and functional analysis, SIRT1 was identified as the most prominent among sirtuin family members, demonstrating that 25 of its protein partners are involved in cancer, 22 in innate immune response, and 29 in aging, with some being linked to a combination of two or more pathways. This study lays the foundation for the development of novel therapies that can target sirtuins with precision and efficacy. By illustrating the various interactions among the proteins in the sirtuin family, we have revealed the multifaceted roles of SIRT1 and provided a framework for their possible roles to be precisely understood, manipulated, and translated into therapeutics in the future.

• Journal of KIISE:Computer Systems and Theory
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• v.36 no.2
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• pp.60-67
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• 2009

Analyzing protein-protein interactions(PPI) is an important task in bioinformatics as it can help in new drugs' discovery process. However, due to vast amount of PPI data and their complexity, efficient visualization of the data is still remained as a challenging problem. We have developed efficient and effective visualization system that integrates Gene Ontology(GO) and PPI network to provide better insights to scientists. To provide efficient data visualization, we have employed dynamic interactive graph drawing methods and context-based browsing strategy. In addition, quick and flexible cross-reference system between GO and PPI; LCA(Least Common Ancestor) finding for GO; and etc are supported as special features. In terms of interface, our visualization system provides two separate graphical windows side-by-side for GO graphs and PPI network, and also provides cross-reference functions between them.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.13
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• pp.5445-5451
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• 2015

Fascin-1 (FSCN1) is an actin-bundling protein that induces cell membrane protrusions, increases cell motility, and is overexpressed in various human epithelial cancers, including esophageal squamous cell carcinoma (ESCC). We analyzed various protein-protein interactions (PPI) of differentially-expressed genes (DEGs), in fascin knockdown ESCC cells, to explore the role of fascin overexpression. The node-degree distributions indicated these PPI sub-networks to be characterized as scale-free. Subcellular localization analysis revealed DEGs to interact with other proteins directly or indirectly, distributed in multiple layers of extracellular membrane-cytoskeleton/ cytoplasm-nucleus. The functional annotation map revealed hundreds of significant gene ontology (GO) terms, especially those associated with cytoskeleton organization of FSCN1. The Random Walk with Restart algorithm was applied to identify the prioritizations of these DEGs when considering their relationship with FSCN1. These analyses based on PPI network have greatly expanded our comprehension of the mRNA expression profile following fascin knockdown to future examine the roles and mechanisms of fascin action.

• Journal of Life Science
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• v.26 no.8
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• pp.904-910
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• 2016

Complex traits are determined by the combined effects of many loci and are affected by gene networks or biological pathways. Systems biology approaches have an important role in the identification of candidate genes related to complex diseases or traits at the system level. The gene network analysis has been performed by diverse types of methods such as gene co-expression, gene regulatory relationships, protein-protein interaction (PPI) and genetic networks. Moreover, the network-based methods were described for predicting gene functions such as graph theoretic method, neighborhood counting based methods and weighted function. However, there are a limited number of researches in livestock. The present study systemically analyzed genes associated with 102 types of economic traits based on the Animal Trait Ontology (ATO) and identified their relationships based on the gene co-expression network and PPI network in cattle. Then, we constructed the two types of gene network databases and network visualization system (http://www.nabc.go.kr/cg). We used a gene co-expression network analysis from the bovine expression value of bovine genes to generate gene co-expression network. PPI network was constructed from Human protein reference database based on the orthologous relationship between human and cattle. Finally, candidate genes and their network relationships were identified in each trait. They were typologically centered with large degree and betweenness centrality (BC) value in the gene network. The ontle program was applied to generate the database and to visualize the gene network results. This information would serve as valuable resources for exploiting genomic functions that influence economically and agriculturally important traits in cattle.