• 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.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2003.10a
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• pp.7-16
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• 2003

In this paper, we propose a probabilistic framework to predict the interaction probability of proteins. The notion of domain combination and domain combination pair is newly introduced and the prediction model in the framework takes domain combination pair as a basic unit of protein interactions to overcome the limitations of the conventional domain pair based prediction systems. The framework largely consists of prediction preparation and service stages. In the prediction preparation stage, two appearance pro-bability matrices, which hold information on appearance frequencies of domain combination pairs in the interacting and non-interacting sets of protein pairs, are constructed. Based on the appearance probability matrix, a probability equation is devised. The equation maps a protein pair to a real number in the range of 0 to 1. Two distributions of interacting and non-interacting set of protein pairs are obtained using the equation. In the prediction service stage, the interaction probability of a protein pair is predicted using the distributions and the equation. The validity of the prediction model is evaluated fur the interacting set of protein pairs in Yeast organism and artificially generated non-interacting set of protein pairs. When 80% of the set of interacting protein pairs in DIP database are used as foaming set of interacting protein pairs, very high sensitivity(86%) and specificity(56%) are achieved within our framework.

• Proceedings of the Korean Information Science Society Conference
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• 2010.11a
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• pp.23-24
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• 2010

• 대한약리학회:학술대회논문집
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• 2006.10a
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• pp.113.2-113.2
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• 2006

• Proceedings of the Korea Crystallographic Association Conference
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• 2001.11a
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• pp.8-8
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• 2001

• Proceedings of the Botanical Society of Korea Conference
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• 1998.07a
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• pp.117.2-118
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• 1998

• BMB Reports
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• v.43 no.11
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• pp.720-725
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• 2010

The small ubiquitin-like modifier (SUMO) proteins have been implicated in the pathology of a number of diseases, including neurodegenerative diseases. The conjugation machinery for SUMOylation consists of a number of proteins which are redox sensitive. Here, under oxidative stress ($100{\mu}M$ hydrogen peroxide), antioxidant ($100{\mu}M$ ascorbate) or control conditions 169 proteins were identified by electospray ionisation fourier transform ion cyclotron resonance mass spectrometry. The majority of these proteins (70%) were found to contain SUMOylation consensus sequences. From the remaining proteins a small number (12%) were found to contain possible SUMO interacting motifs. The proteins identified included DNA and RNA binding proteins, structural proteins and proteasomal proteins. Several of the proteins identified under oxidative stress conditions had previously been identified as SUMOylated proteins, thus validating the method presented.

• Biomedical Science Letters
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• v.12 no.4
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• pp.405-411
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• 2006

Heterotrimeric GTP binding proteins (G proteins) mediate signal transduction generated by neurotransmitter and hormones. Among G-proteins, Go is classified as a member of the Go/Gi family and the most abundant heterotrimeric G protein in brain. Most of the mechanistic analyses on the activation of Go indicated its action to be mediated by the $G{\beta}{\gamma}$ dimer because downstream effectors for its ${\alpha}$ subunit have not been clearly defined. To determine the downstream effectors of alpha subunits of Go ($Go{\alpha}$), we used yeast two-hybrid system to screen $Go{\alpha}$ interacting partners in cDNA library from the human brain. A brain specific high mobility group box containing protein (BHX), A possible transcription factor, was identified as a $Go{\alpha}$ interacting protein. We confirmed interaction between $Go{\alpha}$ and BHX employing in vitro affinity binding assay. Moreover, active form of $Go{\alpha}$ preferentially interacts with BHX than inactive farm. Our findings indicate that $Go{\alpha}$ could modulate gene expression via interaction with BHX during neuronal or brain development.

• BMB Reports
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• v.44 no.6
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• pp.369-374
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• 2011

MHC-I molecules play a critical role in immune surveillance against viruses by presenting peptides to cytotoxic T lymphocytes. Although the mechanisms by which MHC-I molecules assemble and acquire peptides in the ER are well characterized, how MHC-I molecules traffic to the cell surface remains poorly understood. To identify novel proteins that regulate the intracellular transport of MHC-I molecules, MHC-I-interacting proteins were isolated by affinity purification, and their identity was determined by mass spectrometry. Among the identified MHC-I-associated proteins was Tmp21, the human ortholog of yeast Emp24p, which mediates the ER-Golgi trafficking of a subset of proteins. Here, we show that Tmp21 binds to human classical and non-classical MHC-I molecules. The Tmp21-MHC-I complex lacks ${\beta}_2$-microglobulin, and the number of the complexes is increased when free MHC-I heavy chains are more abundant. Taken together, these results suggest that Tmp21 is a novel protein that preferentially binds to ${\beta}_2$-microglobulin-free MHC-I heavy chains.

• Biomedical Science Letters
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• v.26 no.1
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• pp.1-7
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• 2020

Alzheimer's disease (AD) is the most common neurodegenerative disorder and is expected to become more and more widespread as life expectancy increases. New therapeutic target, as well as the identification of mechanisms responsible for pathology, is urgently needed. Recently, microglial actin cytoskeleton has been proposed as a beneficial role in axon regeneration of brain injury. This review highlights in understanding of the characteristics of microglial actin cytoskeleton and discuss the role of specific actin-interacting proteins and receptors in AD. The precise mechanisms and functional aspects of motility by microglia require further study, and the regulation of microglial actin cytoskeleton might be a potential therapeutic strategy for neurological diseases.