• Proceedings of the KAIS Fall Conference
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• 2010.05b
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• pp.1197-1200
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• 2010

Post-genomic 시대에 접어들면서 단백질의 기능의 주석이 중요한 문제로 떠오르기 시작하였다. 이런 단백질 기능을 예측하기 위해 단백질 상호작용(Protein-Protein interaction) 데이터를 이용한 방법들이 지난 10여 년간 발표되어왔다. 단백질 상호작용(Protein-Protein interaction) 데이터는 단백질들 간의 서열 등의 특징을 이용해 상호간의 연결 관련성이 있는 단백질끼리의 관계를 네트워크로 나타낸 자료이다. 현재 이러한 단백질 상호작용(Protein-Protein interaction) 데이터들은 MIPS, DIP, BioGrid등 약 5~6군데에서 제공되고 있다. 각각의 데이터는 다른 형식을 가지고 있고, 중복되는 정보도 포함하고 있다. 여러 연구 방법에서 데이터를 사용할 때 한군데에서만 추출하기 보다는 여러 데이터에서 추출하는 경우가 많기 때문에 다른 형식의 데이터를 이용하는데 불필요한 수고가 들어가게 된다. 때문에 여러군데의 데이터를 한 가지 형식으로 맞추어 통합적으로 구축하여 연구 시 데이터 사용에 용이하도록 설계 하였다. 또한 발표된 단백질 기능 예측 방법에 대한 정리를 통해 앞으로의 연구를 하는데 있어서 필요한 자료를 얻고 열람할 수 있도록 설계하였다. 이를 통해 관련 연구를 하거나 관심이 있는 사람들의 데이터를 검색하는데 많은 도움이 될 것이다.

• Journal of Life Science
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• v.18 no.3
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• pp.318-322
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• 2008

This paper deals with an efficient management and automatic update sub-system for WASPIFA (Web-based Assistant System for Protein-protein Interaction and Function Analysis) system that had been developed in the past and now provides the comprehensive information on protein-protein interaction and protein function. Protein interacting data has increased exponentially, so that it costs enormous time and effort. In other words, it is actually impossible to manually update and manage an analysis system based on protein interacting data. Even though there exists a good analysis system, it could be useless if it was able to be updated timely and managed properly. Unfortunately, in most cases, biologists without professional knowledge on their analysis systems have to cope with a great difficulty in running them. In this respect, the efficient management and automatic update subsystem of protein interacting and its related data has been developed to facilitate experimental biologists as well as bioinformaticians to update and manage the WASPIFA system.

• Journal of the Korean Magnetic Resonance Society
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• v.15 no.1
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• pp.80-89
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• 2011

3D structures of STAM1 UIM-ubiquitin complex were presented to predict and analyze the interaction between UIM and ubiquitin. To generate the protein-peptide complex structure, the RosettaDock method was used with and without NMR restraints. High resolution complex structure was acquired successfully and evaluated electrostatic interaction in the protein-peptide binding with several charged residues at the binding site. From docking results, the Rosettadock method could be useful to acquire essential information of protein-protein or protein-peptide interaction with minimal biological evidences.

• Journal of Integrative Natural Science
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• v.11 no.1
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• pp.9-13
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• 2018

KiSS1-derived peptide receptor, a GPCR protein, binds with the hormone Kisspeptin plays a major role in the neuroendocrine regulation of reproduction. It is important in the onset of puberty and triggers the release of gonadotrophin-releasing hormone. It is a potential drug target for the disorders related to GnRH, hence, analysing the structural features of the receptor becomes important. The three dimensional of the receptor modelled in a previous study was utilised. In this study, we have analysed the protein - protein interaction of the receptor with Kisspeptin 10 and 15. The study revealed the important residues which are involved in the interaction. The result of this study could be helpful in understanding the mechanism of Kiss1 receptor activation and the pathophysiology of the disorders related to the receptor.

• Journal of Applied Biological Chemistry
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• v.42 no.3
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• pp.125-129
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• 1999

The changes in gel characteristics of soy protein and succinylated soy protein due to various specific interaction-altering reagents which affect the formation and textural properties of gels, were studied. The reagents were added to 15% soy protein solutions prior to heat treatment. Succinylated soy protein formed harder gel without the addition of reagents. Hardly no gels were formed with urea, indicating that hydrogen bonds significantly contributed to the formation and hardness of the gel and the effects of urea on the hardness of succinylated soy protein gel were more significant. Disulfide bonds were important in the formation of hard gels whether they were succinylated or not, but the contributions of hydrophobic interactions to gel hardness were relatively insignificant. The hardness reducing effects of NaCl and NaSCN were more significant in succinylated soy protein gel. As such, electrostatic interactions were important for succinylated soy protein to form hard gel but not for unmodified soy protein.

• Archives of Pharmacal Research
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• v.4 no.2
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• pp.99-107
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• 1981

To investigate the protein binding characteristics of ibuprofenlysine, the effects of drub conentration, pH, ionic strength and protein concentration on the binding of drug to protein concentration on the binding of drug to protein were studied by fluorescence probe method. The conformational change of protein was investigated by circular dichroism (CD) measurement. As the concentration of drug increases, the association constant decreases. These may be due to complex formation of the probe and drug, or the interaction of the protein-probe complex and drug. The association constant for ibuprofenlysine increased with increasing protein concentration. These finding suggest a sharing of one ibuprofenlysine molecule by more than one protein molecule in the binding. The binding between ibuprofenlysine and protein was dependent on pH and ionic strength. It seems that both hydrophobic binding and some electrostatic forces are involved in the binding of ibuprofenlysing to protein.

• 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.

• Korean Journal of Food Science and Technology
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• v.19 no.2
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• pp.89-96
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• 1987

The denaturation mechanism of the protein during heating of myosin and paramyosin extracted from the ordinary muscle of yellowtail (Seriola qrinqueradits) and the adductor muscle of whelk (Neptunea arthritica cuming) were investigated by analyzing the hydrophobicity, solubility, SH group and protein-protein interaction. The free hydrophobic residue of the two proteins were increased by increase of heating temperature up to $65^{\circ}C$ and then decreased for further temperature raise. The protein-protein interaction was proportional to the increment of the free hydrophobic residue. The aggregation of protein was begun from $65^{\circ}C$ with the decrease of the free hydrophobic residues. The results of Arrhenius equation for the data on proteinprotein interaction showed that the denaturation course was made up with multi-steps in the myosin and two-steps in the paramyosin. The number of free hydrophobic residue and SH group, solubility and protein-protein interaction were significantly differed with the denaturation temperature (p<0.01).

• 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

• Proceeding of EDISON Challenge
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• 2016.03a
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• pp.90-95
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• 2016

Heat Shock 70kDa Protein 1-Like(HSPA1L)는 Heat-shock protein70(HSP70) family에 속하는 chaperone protein으로 polypeptide folding, assembly, protein degradation 등 다양한 biological processes에 관여하고 있다. HSPA1L은 human methyltransferase-like protein 21A(METTL21A)에 의해 lysine residue에 methylation이 일어나게 되는데, 암세포에서 일반적인 HSPA1L은 주로 세포질에서 발견되는 반면 methylated HSPA1L의 경우 주로 핵에서 발견이 됨으로써 HSPA1L methylation이 암 세포 성장에 중요할 역할을 할 것이라 추측되며 anti-cancer drug target으로 주목 받고 있다. 하지만 현재 HSPA1L의 구조가 부분적으로만 밝혀져 있어 HSPA1L와 METTL21A가 어떤 residue들이 interaction 하여 binding을 하는지에 대해서 아직 밝혀 지지 않았다. 이로 인해 anti-cancer drug target으로서의 연구에 제한이 있다. 이번 연구에서는 homology modeling(Galaxy-TBM, Galaxy-refine)을 통해 HSPA1L 전체 구조를 밝혀 낸 후, HSPA1L 와 METTL21A를 protein-protein docking을 통해 binding pose 예측을 하였다. 이러한 binding pose를 protein interaction analysis하여 HSPA1L과 METTL21A binding에 관여하는 중요 residue들을 밝혀 냈다. 이러한 structural information은 methylated HSPA1L와 암 세포 성장간의 연관성, 더 나아가 anti-cancer drug 개발로 까지도 이어 질 수 있을 것이라 생각한다.