• Asian Pacific Journal of Cancer Prevention
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• v.15 no.5
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• pp.2345-2351
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• 2014

Lysyl oxidase-like 2 (LOXL2), a member of the lysyl oxidase (LOX) family, is a copper-dependent enzyme that catalyzes oxidative deamination of lysine residues on protein substrates. LOXL2 was found to be overexpressed in esophageal squamous cell carcinoma (ESCC) in our previous research. We later identified a LOXL2 splicing variant LOXL2-delta72 and we overexpressed LOXL2-delta72 and its wild type counterpart in ESCC cells following microarray analyses. First, the differentially expressed genes (DEGs) of LOXL2 and LOXL2-delta72 compared to empty plasmid were applied to generate protein-protein interaction (PPI) sub-networks. Comparison of these two sub-networks showed hundreds of different proteins. To reveal the potential specific roles of LOXL2- delta72 compared to its wild type, the DEGs of LOXL2-delta72 vs LOXL2 were also applied to construct a PPI sub-network which was annotated by Gene Ontology. The functional annotation map indicated the third PPI sub-network involved hundreds of GO terms, such as "cell cycle arrest", "G1/S transition of mitotic cell cycle", "interphase", "cell-matrix adhesion" and "cell-substrate adhesion", as well as significant "immunity" related terms, such as "innate immune response", "regulation of defense response" and "Toll signaling pathway". These results provide important clues for experimental identification of the specific biological roles and molecular mechanisms of LOXL2-delta72. This study also provided a work flow to test the different roles of a splicing variant with high-throughput data.

• Molecules and Cells
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• v.27 no.3
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• pp.271-277
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• 2009

Proteins interact with each other within a cell, and those interactions give rise to the biological function and dynamical behavior of cellular systems. Generally, the protein interactions are temporal, spatial, or condition dependent in a specific cell, where only a small part of interactions usually take place under certain conditions. Recently, although a large amount of protein interaction data have been collected by high-throughput technologies, the interactions are recorded or summarized under various or different conditions and therefore cannot be directly used to identify signaling pathways or active networks, which are believed to work in specific cells under specific conditions. However, protein interactions activated under specific conditions may give hints to the biological process underlying corresponding phenotypes. In particular, responsive functional modules consist of protein interactions activated under specific conditions can provide insight into the mechanism underlying biological systems, e.g. protein interaction subnetworks found for certain diseases rather than normal conditions may help to discover potential biomarkers. From computational viewpoint, identifying responsive functional modules can be formulated as an optimization problem. Therefore, efficient computational methods for extracting responsive functional modules are strongly demanded due to the NP-hard nature of such a combinatorial problem. In this review, we first report recent advances in development of computational methods for extracting responsive functional modules or active pathways from protein interaction network and microarray data. Then from computational aspect, we discuss remaining obstacles and perspectives for this attractive and challenging topic in the area of systems biology.

• Bulletin of the Korean Chemical Society
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• v.25 no.4
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• pp.539-544
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• 2004

The ability of protoberberine alkaloids, berberine and berberrubine, to act as topoisomerase II poisons is linked to the anti-cancer activity. Minor alterations in structure have a significant effect on their relative activity. Berberine, which has methoxy group at the 19-position, is significantly less potent than berberrubine. Several observations support non-specific binding to HP14 by the berberine: (i) nonspecific upfield changes in $^1H$ chemical shift for protons of the berberine; (ii) the broadening of imino protons of HP14 upon binding of the berberine; (iii) very small increases in duplex melting temperature in the presence of the berberine. Our results reveal that substitution of a hydroxyl group to a methoxy group on the 19-position, thereby converting the berberrubine to the berberine is associated with a non-specific DNA binding affinity and a reduced topoisomerase II poisoning. The presence of a bulky 19-methoxy substituent decreases intercalating properties of berberine and makes it inactive as topoisomerase II poison.

• BMB Reports
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• v.35 no.5
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• pp.498-507
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• 2002

A gene that encodes a thermostable protease, coined thermicin, has been isolated from Thermoanaerobacter yonseiensis that is expressed and characterized in E. coli.. In order to elucidate the molecular characteristics on thermostability of the enzyme, molecular modeling and mutagenesis technology were applied. In the modeling structure, the structural core, including the active site, was well conserved; whereas, the two loop regions were unique when compared to thermitase. The mutant enzyme with the small loop deleted (D190-I196), based on modeling structural information, showed identical enzyme activity. However, when the large loop was deleted (P233-P244), a little lower $K_m$ and even a lower kcat was found. This indicates that the large loop could influence catalytic activity. However, the unfolding temperature ($T_m$), which was determined by a differential-scanning calorimetry for the mutant enzyme deleted the small loop, was $96^{\circ}C$. This is $14^{\circ}C$ lower than that for the parent thermicin. These results suggest that the small loop may play a role in maintaining the proper folding of the enzyme at high temperatures, whereas the large loop might be related to catalysis.

• Proceedings of the Korean Magnetic Resonance Society Conference
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• 2002.08a
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• pp.90-90
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• 2002

Syndecans, transmembrane heparan sulfate proteoglycans, are coreceptors with integrin in cell adhesion process. It forms a ternary signaling complex with protein kinase C and phosphatidylinositol 4,5 bisphosphate (PIP2) for integrin signaling. NMR data indicates that cytoplasmic domain of syndecan-4 (4L) undergoes a conformational transition in the presence of PIP2, forming oligomeric conformation. The structure based on NMR data demonstrated that syndecan-4L itself forms a compact intertwined symmetric dimer with an unusual clamp shape for residues Leu$^{186}$ -Ala$^{195}$ . The molecular surface of the syndecan-4L dimer is highly positively charged. In addition, no inter-subunit NOEs in membrane proximal amino acid resides (Cl region) has been observed, demonstrating that the Cl region is mostly unstructured in syndecan-4L dimmer. However, the complex structure in the presence of PIP2 induced a high order multimeric conformation in solution. In addition, phosphorylation of cytoplasmic domain induces conformational change of syndecan-4, resulting inhibition of PKC signaling. The NMR structural data strongly suggest that PIP2 promotes oligomerization of syndecan-4 cytoplasmic domain for PKC activation and further induces structural reorganization of syndecan for mediating signaling network in cell adhesion procedure.

• 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.

• Journal of the Korea Society of Computer and Information
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• v.20 no.2
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• pp.137-147
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• 2015

This study proposes an algorithm for predicting breast cancer prognosis based on genetic network. We identify prognosis-specific network using gene expression data and PPI(protein-protein interaction) data. To acquire the network, we calculate Pearson's correlation coefficient(PCC) between genes in all PPI pairs using gene expression data. We develop a prediction model for breast cancer patients with estrogen-receptor-negative using the network as a classifier. We compare classification performance of our algorithm with existing algorithms on independent data and shows our algorithm is improved. In addition, we make an functionality analysis on the genes in the prognosis-specific network using GO(Gene Ontology) enrichment validation.

• Proceedings of the Korea Contents Association Conference
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• 2004.11a
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• pp.511-515
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• 2004

In the post-genomic era, researches on proteins as well as genes have been increasingly required. Particularly, work on protein-protein interaction and protein network construction have been recently establishing. Most biologists publish their research results through papers or other media. However, biologists do not use the information effectively, since the published research results are very large. As the growth of internet, it becomes easy to access very large research results. It is significantly important to extract information with a biological meaning from varisous media. Therefore, in this research, we efficiently extract protein-protein interaction information from many open papers or other media and construct the database of the extracted information. We build a protein network from the established database and then design and implement various pathway analysis algorithms which find biological meaning from the protein network.

• Bulletin of the Korean Chemical Society
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• v.29 no.2
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• pp.347-351
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• 2008

Acetyl-CoA carboxylase (ACC) is an excellent candidate for antibiotics drug target, which mediates malonyl-CoA synthesis from acetyl-CoA through acetylation process. It is also involved in the committed step of fatty acid synthesis which is essential for living organisms. We have determined the three dimensional structure of C terminal domain of HP0371, biotin-carboxyl carrier protein of H. pyroli, in solution state using heteronuclear multi-dimensional NMR spectroscopy. The structure of HP0371 shows a flatten b-sheet fold which is similar with that of E. coli. However, the sequence and structure of protruding thumb are different with that of E. coli and the thumb shows different basis of structural rigidity based on backbone dynamics data.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.1643-1646
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• 2008

In this study, an elastic network model is established in order to find dominant factors which reflect thermostability of protein structures. The connections in the elastic network model are selected with respect to the free energy between alpha-carbons, which is representatives of residues in the elastic network model. We carried out normal mode analysis and compared eigenvalues of the stiffness matrix from the elastic network model. In most cases, thermophilic proteins are observed to have higher values of lowest natural frequency than mesophiles and psychrophiles have. As a result, the thermophiles are calculated to be stiffer than other proteins in view of dynamic vibration.