• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.156-160
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• 2005

We introduce a fully automatic clustering method to classier candidate paralog clusters from a set of protein sequences within one genome. A set of protein sequences is represented as a set of nodes, each represented by the amino acid sequence for a protein with the sequence similarities among them constituting a set of edges in a graph of protein relationships. We use graph-based clustering methods to identify structurally consistent sets of nodes which are strongly connected with each other. Our results are consistent with those from current leading systems such as COG/KOG and KEGG based on manual curation. All the results are viewable at http://www.cs.rutgers.edu/${\sim}$seabee.

• Journal of Microbiology
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• v.38 no.3
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• pp.176-179
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• 2000

A challenge phage system was used to study the DNA-protein interaction between C4-dicarboxylic acid transport protein D(DCTD) or $\sigma$54, and a $\sigma$54 -dependent promoter, dctAp. R. meliloti dctA promoter regulatory region replaced the Omnt site on the phage. S. typhimurium strains overproducing either DCTD or $\sigma$54 directed this challenge phage towards lysogency, indicating that DCTD or E$\sigma$54 recognized the dctA promoter on the phage and repressed transcription of the ant gene. These challenge phage constructs will be useful for examining interactions between DCTD(or $\sigma$54) and the dctA promoter region.

• Journal of the Korean Magnetic Resonance Society
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• v.10 no.1
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• pp.96-104
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• 2006

The gene coding for APG8a (At4g21980), a protein from Arabidopsis thaliana, is involved in the autophagy process. The protein is an interesting candidate for structure determination by NMR spectroscopy. Toward this end, APG8a has been produced recombinantly in Escherichia coli and typical NMR experiments such as $^{15}N-HSQC$, HNCA, HN(CO)CA, CBCA(CO)NH, HCCH-TOCSY, HNCO were performed. The backbone resonances, HN, N, CA, CB, and C' were sequence-specifically assigned, and the secondary structures including 3 $\alpha$ helices and $4\beta$ strands were deduced based on the assignments. Due to the intrinsic flexibility or the effect of the denaturant, the backbone resonances were not fully observed. Since the structure calculation by NMR data was not possible, the 3-dimensional model was built based on the sequence homology, and compared with the NMR results. The overall structure of the model could explain and complement the NMR derived secondary structures.

• Journal of the Korean Magnetic Resonance Society
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• v.18 no.1
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• pp.36-40
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• 2014

Predicting secondary structure of protein through assigned backbone chemical shifts has been used widely because of its convenience and flexibility. In spite of its usefulness, chemical shift based analysis has some defects including isotopic shifts and solvent interaction. Here, it is shown that corrected chemical shift analysis for secondary structure of protein. It is included chemical shift correction through consideration of deuterium isotopic effect and calculate chemical shift index using probability-based methods. Enhanced method was applied successfully to one of the proteins from Mycobacterium tuberculosis. It is suggested that correction of chemical shift analysis could increase accuracy of secondary structure prediction of protein and small molecule in solution.

• Mass Spectrometry Letters
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• v.6 no.2
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• pp.31-37
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• 2015

Phosphorylation upon protein is well known to a key regulator that implicates in modulating many cellular processes like growth, migration, and differentiation. Up to date, grafting of multidimensional separation techniques onto advanced mass spectrometry (MS) has emerged as a promising tool for figuring out the biological functions of phosphorylation in a cell. However, advanced MS-based phosphoproteomics is still challenging, due to its intrinsic issues, i.e., low stoichiometry, less susceptibility in positive ion mode, and low abundance in biological sample. To overcome these bottlenecks, diverse techniques (e.g., SCX, HILIC, ERLIC, IMAC, TiO₂, etc.) are continuously developed for on-/off-line enrichment of phosphorylated protein (or peptide) from biological samples, thereby helping qualitative/quantitative determination of phosphorylated protein and its phosphorylated sites. In this review, we introduce to the overall views of enrichment tools that are universally used to selectively isolate targeted phosphorylated protein (or peptide) from ordinary ones before MS-based phospoproteomic analysis.

• Journal of Radiopharmaceuticals and Molecular Probes
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• v.2 no.2
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• pp.69-72
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• 2016

Since the translocator protein (TSPO) is involved in neurodegeneration diseases, many scientists' interest has been focused on the development of a ligand targeting TSPO. A novel compound based on pyrazolo[1,5 -a] pyrimidine structure, DPA-714, has been studied and considered as a TSPO ligand with high affinity. In this highlight review, several researches for the novel radioligand for the translocator protein are illustrated.

• Journal of Integrative Natural Science
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• v.9 no.1
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• pp.35-40
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• 2016

Protein phosphatase manganese dependent 1D (PPM1D) is one of the Ser/Thr protein phosphatases belongs to the PP2C family. They play an important role in cancer tumorigenesis of various tumors including neuroblastoma, pancreatic adenocarcinoma, medulloblastoma, breast cancer, prostate cancer and ovarian cancer. Even though PPM1D is involved in the pathophysiology of various tumors, the three dimensional protein structure is still unknown. Hence in the present study, homology modelling of PPM1D was performed. 20 different models were modelled using single- and multiple-template based homology modelling and validated using different techniques. Best models were selected based on the validation. Three models were selected and found to have similar structures. The predicted models may be useful as a tool in studying the pathophysiological role of PPM1D.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2004.11a
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• pp.265-271
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• 2004

The interaction network of protein -protein plays an important role to understand the various biological functions of cells. Currently, the high -throughput experimental techniques (two -dimensional gel electrophoresis, mass spectroscopy, yeast two -hybrid assay) provide us with the vast amount of data for protein-protein interaction at the proteome scale. In order to recognize the role of each protein in their network, the efficient bioinformatical and computational analysis methods are required. We propose a systematic and mathematical method which can analyze the protein -protein interaction network rigorously and enable us to capture the biological and physical essence of a topological character and stability of protein -protein network, and sensitivity of each protein along the biological pathway of their network. We set up a Laplacian matrix of spectral graph theory based on the protein-protein network of yeast proteome, and perform an eigenvalue analysis and apply a perturbation method on a Laplacian matrix, which result in recognizing the center of protein cluster, the identity of hub proteins around it and their relative sensitivities. Identifying the topology of protein -protein network via a Laplacian matrix, we can recognize the important relation between the biological pathway of yeast proteome and the formalism of master equation. The results of our systematic and mathematical analysis agree well with the experimental findings of yeast proteome. The biological function and meaning of each protein cluster can be explained easily. Our rigorous analysis method is robust for understanding various kinds of networks whether they are biological, social, economical...etc

• KSBB Journal
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• v.22 no.6
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• pp.393-400
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• 2007

Analysis of protein interactions/functions in a microarray format has been of great potential in drug discovery, diagnostics, and cell biology, because it is amenable to large-scale and high-throughput biological assays in a rapid and economical way. In recent years, the protein microarray have broaden their utility towards the global analysis of protein interactions on a proteome scale, the functional activity analysis based on protein interactions and post-translational modifications (PTMs), and the discovery of biomarkers through profiling of protein expression between sample and reference pool. As a promising tool for proteomics, the protein microarray technology has advanced outstandingly over the past decade in terms of surface chemistry, acquisition of relevant proteins on a proteomic level, and detection methods. In this article, we briefly describe various techniques for development of protein microarray, and introduce developmental state of protein microarray and its applications.

• Genomics & Informatics
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• v.19 no.4
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• pp.43.1-43.12
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• 2021

Campylobacter jejuni is one of the most prevalent organisms associated with foodborne illness across the globe causing campylobacteriosis and gastritis. Many proteins of C. jejuni are still unidentified. The purpose of this study was to determine the structure and function of a non-annotated hypothetical protein (HP) from C. jejuni. A number of properties like physiochemical characteristics, 3D structure, and functional annotation of the HP (accession No. CAG2129885.1) were predicted using various bioinformatics tools followed by further validation and quality assessment. Moreover, the protein-protein interactions and active site were obtained from the STRING and CASTp server, respectively. The hypothesized protein possesses various characteristics including an acidic pH, thermal stability, water solubility, and cytoplasmic distribution. While alpha-helix and random coil structures are the most prominent structural components of this protein, most of it is formed of helices and coils. Along with expected quality, the 3D model has been found to be novel. This study has identified the potential role of the HP in 2-methylcitric acid cycle and propionate catabolism. Furthermore, protein-protein interactions revealed several significant functional partners. The in-silico characterization of this protein will assist to understand its molecular mechanism of action better. The methodology of this study would also serve as the basis for additional research into proteomic and genomic data for functional potential identification.