• Genomics & Informatics
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• v.2 no.2
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• pp.99-106
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• 2004

In this paper we introduce PubMiner, an intelligent machine learning based text mining system for mining biological information from the literature. PubMiner employs natural language processing techniques and machine learning based data mining techniques for mining useful biological information such as protein­protein interaction from the massive literature. The system recognizes biological terms such as gene, protein, and enzymes and extracts their interactions described in the document through natural language processing. The extracted interactions are further analyzed with a set of features of each entity that were collected from the related public databases to infer more interactions from the original interactions. An inferred interaction from the interaction analysis and native interaction are provided to the user with the link of literature sources. The performance of entity and interaction extraction was tested with selected MEDLINE abstracts. The evaluation of inference proceeded using the protein interaction data of S. cerevisiae (bakers yeast) from MIPS and SGD.

• Journal of Life Science
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• v.6 no.3
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• pp.185-192
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• 1996

Bacteriophage T7 gene 2.5 protein, a single-stranded DNA binding protein, is required for T7 DNA replication, recombination, and repair. T7 gene 2.5 protein has two distinctive domains, DNA binding and C-terminal domain, directly involved in protein-protein interaction. Gene 2.5 protein participates in the DNA replication of Bacteriophage T7, which makes this protein essential for the T7 growth and DNA replication. What gene 2.5 protein makes important at T7 growth and DNA replication is its binding affinity to single-stranded DNA and the protein-protein important at T7 DNA replication proteins which are essential for the T7 DNA synthesis. We have constructed pGST2.5(WT) encoding the wild-type gene 2.5 protein and pGST2.5$\Delta $21C lacking C-terminal 21 amino acid residues. The purified GST-fusion proteins, GST2.5(WT) and GST2.5(WT)$\Delta$21C, were used for whether the carboxyl-terminal domain participates in the protein-protein interactions or not. GST2.5(WT) and GST2.5$\Delta$21C showed the difference in the protein-protein interaction. GST2.5(WT) interacted with T7 DNA polymerase and gene 4 protein, but GST2.5$\Delta$21C did not interact with either protein. Secondly, GST2.5(WT) interacts with gene 4 proteins (helicase/primase) but not GST2.5$\Delta$21C. these results proved the involvement of the carboxyl-terminal domain of gene 2.5 protein in the protein-protein interaction. We clearly conclude that carboxy-terminal domain of gene 2.5 protein is firmly involved in protein-protein interactions in T7 replication proteins.

• Preventive Nutrition and Food Science
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• v.3 no.2
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• pp.143-151
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• 1998

Protein -surfactant interactions have been investigate by measuring ζ-potential of $\beta$-lactoglobulin-coated emulsion droplets and $\beta$-lactoglobulin in solution in the rpesenceof surfactant, with particular emphasis on the effect of protein heat treatment(7$0^{\circ}C$, 30min). When ionic surfactant (SDS or DATEM) is added to the protein solution, the ζ-potential of the mixture is found to increase with increasing surfactant concentration, indicating surfactant binding to the protein molecules. For heat-denatured protein,it has been observed that the ζ-potential tends to be lower than that of the native protein. The effect of surfactant on emulsions is rather complicated .With SDS, small amounts of surfactant addition induce a sharp increase in zeta potential arising from the specific interaction of surfactant with protein. With further surfacant addition, there is a gradual reductio in the ζ-potential, presumably caused by the displacement of adsorped protein (and protein-surfactant complex) from the emulsion droplet surfac by the excess of SDS molecules. At even higher surfactant concentrations, the measured zeta potential appears to increase slightly, possibly due to the formation of a surfactant measured zeta potential appears to increase slightly, possibly due to the formation of surfactant micellar structure at the oil droplet surface. This behaviour contrastswith the results of the corresponding systems containing the anionic emulsifier DATEM, in which the ζ-potential of the system is found to increase continuously with R, particularly at very low surfactant concentration. Overall, such behaviour is consisten with a combination of complexation and competitive displacement between surfactant and protein occurring at the oil-water interface. In addition, it has also been found that above the CMC, there is a time-dependent increase in the negative ζ-potential of emulsion droplets in solutions of SDS, possibly due to the solublization of oil droplets into surfactant micelles in the aqueous bulk phase.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.313-318
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• 2005

Estimating the reliability of protein-protein interaction data sets obtained by high-throughput technologies such as yeast two-hybrid assays and mass spectrometry is of great importance. We develop a maximum likelihood estimation method that uses both protein localization and gene expression data to estimate the reliability of protein interaction data sets. By integrating protein localization data and gene expression data, we can obtain more accurate estimates of the reliability of various interaction data sets. We apply the method to protein physical interaction data sets and protein complex data sets. The reliability of the yeast two-hybrid interactions by Ito et al. (2001) is 27%, and that by Uetz et at.(2000) is 68%. The reliability of the protein complex data sets using tandem affinity purification-mass spec-trometry (TAP) by Gavin et at. (2002) is 45%, and that using high-throughput mass spectrometric protein complex identification (HMS-PCI) by Ho et al. (2002) is 20%. The method is general and can be applied to analyze any protein interaction data sets.

• Journal of Microbiology and Biotechnology
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• v.18 no.4
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• pp.631-638
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• 2008

Tandem affinity purification (TAP) method combined with LC-MS/MS is the most accurate and reliable way to study the interaction of proteins or proteomics in a genome-wide scale. For the first time, we used a TAP-tag as a mutagenic tool to disrupt protein interactions at the specific site. Although lots of commonly used mutational tools exist to study functions of a gene, such as deletional mutations and site-directed mutagenesis, each method has its own demerit. To test the usefulness of a TAP-tag as a mutagenic tool, we applied a TAP-tag to RNA polymerase II, which is the key enzyme of gene expression and is controlled by hundreds of transcription factors even to transcribe a gene. Our experiment is based on the hypothesis that there will be interrupted interactions between Pol II and transcription factors owing to the TAP-tag attached at the C-terminus of each subunit of Pol II, and the abnormality caused by interrupted protein interactions can be observed by measuring a cell-cycle of each yeast strain. From ten different TAP-tagged strains, Rpb7- and Rpb12-TAP-tagged strains show severe defects in growth rate and morphology. Without a heterodimer of Rpb4/Rpb7, only the ten subunits Pol II can conduct transcription normally, and there is no previously known function of Rpb7. The observed defect of the Rpb7-TAP-tagged strain shows that Rpb7 forms a complex with other proteins or compounds and the interruption of the interaction can interfere with the normal cell cycle and morphology of the cell and nucleus. This is a novel attempt to use a TAP-tag as a proteomic tool to study protein interactions.

• Molecules and Cells
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• v.27 no.6
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• pp.629-634
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• 2009

G protein-coupled receptors (GPCRs) are part of multi-protein networks called 'receptosomes'. These GPCR interacting proteins (GIPs) in the receptosomes control the targeting, trafficking and signaling of GPCRs. PDZ domain proteins constitute the largest protein family among the GIPs, and the predominant function of the PDZ domain proteins is to assemble signaling pathway components into close proximity by recognition of the last four C-terminal amino acids of GPCRs. We present here a machine learning based approach for the identification of GPCR-binding PDZ domain proteins. In order to characterize the network of interactions between amino acid residues that contribute to the stability of the PDZ domain-ligand complex and to encode the complex into a feature vector, amino acid contact matrices and physicochemical distance matrix were constructed and adopted. This novel machine learning based method displayed high performance for the identification of PDZ domain-ligand interactions and allowed the identification of novel GPCR-PDZ domain protein interactions.

• Mass Spectrometry Letters
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• v.9 no.2
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• pp.51-55
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• 2018

Capture of non-glycoproteins during lectin affinity chromatography is frequently observed, although it would seem to be anomalous. In actuality, lectin affinity chromatography works at post-translational modification (PTM) sites on a glycoprotein which is not involved in protein-protein interactions (PPIs). In this study, serial affinity column set (SACS) using lectins followed by proteomics methods was used to identify PPI mechanisms of captured proteins in human plasma. MetaCore, STRING, Ingenuity Pathway Analysis (IPA), and IntAct were individually used to elucidate the interactions of the identified abundant proteins and to obtain the corresponding interaction maps. The abundant non-glycoproteins were captured with the binding to the selected glycoproteins. Therefore, depletion process in sample pretreatment for abundant protein removal should be considered with more caution because it may lose precious disease-related low abundant proteins through PPIs of the removed abundant proteins in human plasma during the depletion process in biomarker discovery. Glycoproteins bearing specific glycans are frequently associated with cancer and can be specifically isolated by lectin affinity chromatography. Therefore, SACS using Lycopersicon esculentum lectin (LEL) can also be used to study disease interactomes.

• Bulletin of the Korean Chemical Society
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• v.31 no.5
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• pp.1223-1227
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• 2010

In this study, the orientational behavior of thermotropic liquid crystals (LC) supported on a film of protein receptors was examined. Avidin was roller printed and covalently immobilized onto the surface of gold using NHS/EDC chemistry. The orientation of nematic 4-cyano-4'-pentylbiphenyl (5CB) was found to be parallel to the plane of the printed avidin surface before incubation with a solution of biotin. However, protein-receptor complexation induced a random orientation of 5CB, where protein-receptor complexes disturbed the nanoscale topography of the printed protein surface. Atomic force microscopy and ellipsometry was used to confirm printing and the specific interaction of proteins. These results demonstrate that the combination of LC and roller printing can be used to detect specific interactions between biomolecules by manipulating the orientational behavior of LC to the printed protein surfaces.

• The Korea Genome Conference
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• 2002.08a
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• pp.47-47
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• 2002

• 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.