• The Journal of the Korea Contents Association
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• v.8 no.6
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• pp.74-81
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• 2008

Protein interaction network contains a small number of highly connected protein, denoted hub and many destitutely connected proteins. Recently, several studies described that a hub protein is more likely to be essential than a non-hub protein. This phenomenon called as a centrality-lethality rule. This nile is widely credited to exhibit the importance of hub proteins in the complex network and the significance of network architecture as well. To confirm whether the rule is accurate, we Investigated all protein interaction DBs of yeast in the public sites such as Uetz, Ito, MIPS, DIP, SGB, and BioGRID. Interestingly, the protein network shows that the rule is correct in lower scale DBs (e.g., Uetz, Ito, and DIP) but is not correct in higher scale DBs (e.g., SGD and BioGRID). We are now analyzing the features of networks obtained from the SGD and BioGRD and comparing those of network from the DIP.

• Genomics & Informatics
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• v.18 no.4
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• pp.39.1-39.8
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• 2020

Alzheimer's disease (AD) is a chronic, progressive brain disorder that slowly destroys affected individuals' memory and reasoning faculties, and consequently, their ability to perform the simplest tasks. This study investigated the hub genes of AD. Proteins interact with other proteins and non-protein molecules, and these interactions play an important role in understanding protein function. Computational methods are useful for understanding biological problems, in particular, network analyses of protein-protein interactions. Through a protein network analysis, we identified the following top 10 hub genes associated with AD: PTGER3, C3AR1, NPY, ADCY2, CXCL12, CCR5, MTNR1A, CNR2, GRM2, and CXCL8. Through gene enrichment, it was identified that most gene functions could be classified as integral to the plasma membrane, G-protein coupled receptor activity, and cell communication under gene ontology, as well as involvement in signal transduction pathways. Based on the convergent functional genomics ranking, the prioritized genes were NPY, CXCL12, CCR5, and CNR2.

• Journal of the Korean Chemical Society
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• v.63 no.6
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• pp.427-434
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• 2019

The role of hydrophobic residues on protein folding reaction was studied by folding kinetics measurements in conjunction with protein engineering. The HubWA, which was derived from human ubiquitin by mutating the residues at 45 (Phe to Trp) and 26 (Val to Ala), was used as a mutational background. Fourteen hydrophobic residues were mutated to alanine. Among fourteen variants generated, only four variant proteins (V5A, I13A, V17A, and I36A) were suitable for folding study. The folding kinetics of these variants was measured by stopped-flow fluorescence spectroscopy. The folding kinetics of HubWA and V17A was observed to follow a three-state on-pathway mechanism. On the other hand, folding kinetics of V5A, I13A, and I36A was observed to follow a two-state mechanism. Based on these observations, transition of protein folding reaction from collision-diffusion mechanism to nucleation-condensation mechanism was discussed.

• Journal of the Korean Chemical Society
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• v.67 no.2
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• pp.81-88
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• 2023

The contribution of hydrophobic residues to the protein folding reaction was studied by using HubWA variant proteins with I and L to V mutation. Folding kinetics of all V variant proteins was observed to be satisfied by a three-state on-pathway mechanism, U ⇌ I ⇌ N, where U, I, and N represent unfolded, intermediate, and native state, respectively. Three-state folding reaction was quantitatively analyzed and the free energy of folding of each elementary reactions and overall folding reaction, ΔG^o_UI, ΔG^o_IN, and ΔG^o_UN, were obtained. From the ratio of free energy difference between the variant protein and HubWA, ΔΔG^o_UI/ΔΔG^o_UN (ΔΔG^o_UI = ΔG^o_UI (variant protein) - ΔG^o_UI (HubWA) and ΔΔG^o_UN = ΔG^o_UN (variant protein) - ΔG^o_UN(HubWA)), the contribution of hydrophobic residues to HubWA folding was analyzed. The residues which are located in the hydrophobic core between α-helix and β-sheet, I3, I13, L15, I30, L43, I61 and L67, showed ΔΔG^o_UI/ΔΔG^o_UN value of ~0.5 when each of these residues was mutated to V, indicating that these residues form relatively solid hydrophobic core in the intermediate state. Residues located at the end of secondary structures and loop, I23, L69 and I36 showed ΔΔG^o_UI/ΔΔG^o_UN value below 0.4 when each of these residues was mutated to V, indicating that the region containing these residues are loosely formed in the intermediate state. V17A, L50V and L56V showed fairly high ΔΔG^o_UI/ΔΔG^o_UN value of ~0.8. Since L50 and L56 are located in the region containing long loop (residue 46 to 62), it is suggested that the high ΔΔG^o_UI/ΔΔG^o_UN value of these residues prevents the formation of aggregate at the early stage of folding reaction.

• Bulletin of the Korean Chemical Society
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• v.31 no.10
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• pp.2877-2883
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• 2010

The folding kinetics of $WT^*$ ubiquitin variant with valine to alanine mutation at sequence position 26 (HubWA) was studied by stopped-flow fluorescence spectroscopy. While unfolding kinetics showed a single exponential phase, refolding reaction showed three exponential phases. The semi-logarithmic plot of urea concentration vs. rate constant for the first phase showed v-shape pattern while the second phase showed v-shape with roll-over effect at low urea concentration. The rate constant and the amplitude of the third phase were constant throughout the urea concentrations, suggesting that this phase represents parallel process due to the configurational isomerization. Interestingly, the first and second phases appeared to be coupled since the amplitude of the second phase increased at the expense of the amplitude of the first phase in increasing urea concentrations. This observation together with the roll-over effect in the second folding phase indicates the presence of intermediate state during the folding reaction of HubWA. Quantitative analysis of Hub-WA folding kinetics indicated that this intermediate state is on the folding pathway. Folding kinetics measurement of a mutant HubWA with hydrophobic core residue mutation, Val to Ala at residue position 17, suggested that the intermediate state has significant amount of native interactions, supporting the interpretation that the intermediate is on the folding pathway. It is considered that HubWA is a useful model protein to study the contribution of residues to protein folding process using folding kinetics measurements in conjunction with protein engineering.

• Bulletin of the Korean Chemical Society
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• v.27 no.9
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• pp.1285-1286
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• 2006

• Proceedings of the Korea Contents Association Conference
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• 2008.05a
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• pp.842-845
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• 2008

The protein interaction network contains a small number of highly connected protein, denoted hub and many destitutely connected proteins. Recently, several studies described that a hub protein is more likely to be essential than a non-hub protein. This phenomenon called as the centrality-lethality rule. This rule is widely credited to exhibit the importance of hub proteins in the complex network and the significance of network architecture as well. To confirm whether the rule is accurate, we investigated all protein interaction DBs of yeast in the public sites such as Uetz, Ito, MIPS, DIP, SGD, and BioGRID. Interestingly, the protein network shows that the rule is correct in lower scale DBs (e.g., Uetz, Ito, and DIP) but is not correct in higher scale DBs (e.g., SGD and BioGRID). We are now analyzing the features of networks obtained from the SGD and BioGRD and comparing those of network from the DIP.

• Genomics & Informatics
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• v.19 no.2
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• pp.16.1-16.14
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• 2021

Even in the current age of advanced medicine, the prognosis of malignant peritoneal mesothelioma (MPM) remains abysmal. Molecular mechanisms responsible for the initiation and progression of MPM are still largely not understood. Adopting an integrated bioinformatics approach, this study aims to identify the key genes and pathways responsible for MPM. Genes that are differentially expressed in MPM in comparison with the peritoneum of healthy controls have been identified by analyzing a microarray gene expression dataset. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses of these differentially expressed genes (DEG) were conducted to gain a better insight. A protein-protein interaction (PPI) network of the proteins encoded by the DEGs was constructed using STRING and hub genes were detected analyzing this network. Next, the transcription factors and miRNAs that have possible regulatory roles on the hub genes were detected. Finally, survival analyses based on the hub genes were conducted using the GEPIA2 web server. Six hundred six genes were found to be differentially expressed in MPM; 133 are upregulated and 473 are downregulated. Analyzing the STRING generated PPI network, six dense modules and 12 hub genes were identified. Fifteen transcription factors and 10 miRNAs were identified to have the most extensive regulatory functions on the DEGs. Through bioinformatics analyses, this work provides an insight into the potential genes and pathways involved in MPM.

• Journal of Korean Neurosurgical Society
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• v.65 no.5
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• pp.697-709
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• 2022

Objective : The present study aimed to identify the function of ischemic stroke (IS) patients' peripheral blood and its role in IS, explore the pathogenesis, and provide direction for clinical research progress by comprehensive bioinformatics analysis. Methods : Two datasets, including GSE58294 and GSE22255, were downloaded from Gene Expression Omnibus database. GEO2R was utilized to obtain differentially expressed genes (DEGs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs were performed using the database annotation, visualization and integrated discovery database. The protein-protein interaction (PPI) network of DEGs was constructed by search tool of searching interactive gene and visualized by Cytoscape software, and then the Hub gene was identified by degree analysis. The microRNA (miRNA) and miRNA target genes closely related to the onset of stroke were obtained through the miRNA gene regulatory network. Results : In total, 36 DEGs, containing 27 up-regulated and nine down-regulated DEGs, were identified. GO functional analysis showed that these DEGs were involved in regulation of apoptotic process, cytoplasm, protein binding and other biological processes. KEGG enrichment analysis showed that these DEGs mediated signaling pathways, including human T-cell lymphotropic virus (HTLV)-I infection and microRNAs in cancer. The results of PPI network and cytohubba showed that there was a relationship between DEGs, and five hub genes related to stroke were obtained : SOCS3, KRAS, PTGS2, EGR1, and DUSP1. Combined with the visualization of DEG-miRNAs, hsa-mir-16-5p, hsa-mir-181a-5p and hsa-mir-124-3p were predicted to be the key miRNAs in stroke, and three miRNAs were related to hub gene. Conclusion : Thirty-six DEGs, five Hub genes, and three miRNA were obtained from bioinformatics analysis of IS microarray data, which might provide potential targets for diagnosis and treatment of IS.

• Genomics & Informatics
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• v.19 no.4
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• pp.42.1-42.17
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• 2021

Salivary gland carcinoma (SGC) is rare cancer, constituting 6% of neoplasms in the head and neck area. The most responsible genes and pathways involved in the pathology of this disorder have not been fully understood. We aimed to identify differentially expressed genes (DEGs), the most critical hub genes, transcription factors, signaling pathways, and biological processes (BPs) associated with the pathogenesis of primary SGC. The mRNA dataset GSE153283 in the Gene Expression Omnibus database was re-analyzed for determining DEGs in cancer tissue of patients with primary SGC compared to the adjacent normal tissue (adjusted p-value < 0.001; |Log2 fold change| > 1). A protein interaction map (PIM) was built, and the main modules within the network were identified and focused on the different pathways and BP analyses. The hub genes of PIM were discovered, and their associated gene regulatory network was built to determine the master regulators involved in the pathogenesis of primary SGC. A total of 137 genes were found to be differentially expressed in primary SGC. The most significant pathways and BPs that were deregulated in the primary disease condition were associated with the cell cycle and fibroblast proliferation procedures. TP53, EGF, FN1, NOTCH1, EZH2, COL1A1, SPP1, CDKN2A, WNT5A, PDGFRB, CCNB1, and H2AFX were demonstrated to be the most critical genes linked with the primary SGC. SPIB, FOXM1, and POLR2A significantly regulate all the hub genes. This study illustrated several hub genes and their master regulators that might be appropriate targets for the therapeutic aims of primary SGC.