• Proceedings of the Korean Society for Bioinformatics Conference
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• 2003.10a
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• pp.17-25
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• 2003

Determining the binding sites in protein-nucleic acid complexes is essential to the complete understanding of protein-nucleic acid interactions and to the development of new drugs. We have developed a set of algorithms for analyzing protein-nucleic acid interactions and for predicting potential binding sites in protein-nucleic acid complexes. The algorithms were used to analyze the hydrogen-bonding interactions in protein-RNA and protein-DNA complexes. The analysis was done both at the atomic and residue level, and discovered several interesting interaction patterns and differences between the two types of nucleic acids. The interaction patterns were used for predicting potential binding sites in new protein-RNA complexes.

• Journal of Integrative Natural Science
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• v.11 no.2
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• pp.101-106
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• 2018

Corticotropin - releasing hormone receptor 1 (CRHR1) forms an integral part of the pathophysiology of disorders like post-traumatic stress disorder, stress, anxiety, addiction, and depression. Hence it is essential to look for new, potent and structure-specific inhibitors of CRHR1. We have analysed the protein-protein interaction complexes of the CRHR1 receptor with its native ligand CRF and full agonist Sauvagine. The structure of Sauvagine was predicted using homology modelling. We have identified that the residues TYR253, ASP254, GLU256, GLY265, ARG1014 and LY1060 are important in the formation of protein-protein complex formation. Future studies on these residues could throw light on the crucial structural features required for the formation of CRHR1-inhibitor complex and in studies that try to solve the structural complexities of CRHR1.

• Journal of the Korean Magnetic Resonance Society
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• v.22 no.4
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• pp.76-81
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• 2018

Investigation of the protein-protein interaction mode at atomic resolution is essential for understanding on the underlying functional mechanisms of proteins as well as for discovering druggable compounds blocking deleteriou interprotein interactions. Solution NMR spectroscopy provides accurate and precise information on intermolecular interactions even for weak and transient interactions, and it is also markedly useful for examining the change in the conformation and dynamics of target proteins upon binding events. In this mini-review, we comprehensively describe three unique and powerful methods of solution NMR spectroscopy, paramagnetic relaxation enhancement (PRE), pseudo-contact shift (PCS), and residual dipolar coupling (RDC), for the study on protein-protein interactions.

• Bulletin of the Korean Chemical Society
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• v.28 no.6
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• pp.1005-1009
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• 2007

Leukotriene B4 (LTB4) is a potent chemoattractant for leukocytes and considered to be an inflammatory mediator. Human BLT2 (hBLT2) is a low-affinity G-protein coupled receptor for LTB4 and mediates pertussis toxin-sensitive chemotactic cell movement. Here, we dissected the interaction between hBLT2 and G-protein alpha subunits using GST fusion proteins containing intracellular regions of hBLT2 and various Gα protein including Gα i1, Gα i2, Gα i3, Gα s1, Gα o1, and Gα z. Among the tested Gα subunits, Gα i3 showed the highest binding to the third intracellular loop region of hBLT2 with a dissociation constant (KD) of 5.0 × 10?6 M. These results suggest that Gα i3 has the highest affinity to hBLT2, and the third intracellular loop region of hBLT2 is the major component for the interaction with Gα i3.

• BMB Reports
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• v.38 no.4
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• pp.381-385
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• 2005

Severe acute respiratory syndrome (SARS) is an emerging infectious disease associated with a novel coronavirus (CoV) that was identified and molecularly characterized in 2003. Previous studies on various coronaviruses indicate that protein-protein interactions amongst various coronavirus proteins are critical for viral assembly and morphogenesis. It is necessary to elucidate the molecular mechanism of SARS-CoV replication and rationalize the anti-SARS therapeutic intervention. In this study, we employed an in vitro GST pull-down assay to investigate the interaction between the membrane (M) and the nucleocapsid (N) proteins. Our results show that the interaction between the M and N proteins does take place in vitro. Moreover, we provide an evidence that 12 amino acids domain (194-205) in the M protein is responsible for binding to N protein. Our work will help shed light on the molecular mechanism of the virus assembly and provide valuable information pertaining to rationalization of future anti-viral strategies.

• 한국생물공학회:학술대회논문집
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• 2005.10a
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• pp.737-738
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• 2005

• IMMUNE NETWORK
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• v.2 no.3
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• pp.125-132
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• 2002

In the past, bioinformatics was often regarded as a difficult and rather remote field, practiced only by computer scientists and not a practical tool available to biologists. However, the various on-going genome projects have had a serious impact on biological sciences in various ways and now there is little doubt that bioinformatics is an essential part of the research environment, with a wealth of biological information to analyze and predict. Fully sequenced genomes made us to have additional insights into the functional properties of the encoded proteins and made it possible to develop new tools and schemes for functional biology on a proteomic scale. Among those are the yeast two-hybrid system, mass spectrometry and microarray: the technology of choice to detect protein-protein interactions. These functional insights emerge as networks of interacting proteins, also known as "pathway informatics" or "interactomics". Without exception it is no longer possible to make advances in the signaling/regulatory pathway studies without integrating information technologies with experimental technologies. In this paper, we will introduce the databases of protein interaction worldwide and discuss several challenging issues regarding the actual implementation of databases.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2004.11a
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• pp.234-243
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• 2004

단백질-단백질 상호작용(PPI :Protein-Protein Interaction) 데이터는 생물체가 어떠한 메커니즘으로 생명을 유지하는지에 대한 정보를 담고 있다. 최근에는 생물학자들의 실험에 의해 많은 데이터가 축적되어 있으며, 데이터베이스로 구축되어 인터넷에 공개되어 있다. PPI 데이터는 단백질를 노드(node)로, 상호작용은 에지(edge)로 갖는 그래프(Graph) 구조로 표현 가능하다. 본 논문에서는 사용자가 PPI 데이터를 쉽게 가공하고 분석할 수 있도록 그래프 이론 기반에 기반하여 구현한 Proteinca(PROTEin INteraction CAbaret) 시스템에 대해 소개한다. Proteinca에 대한 자세한 정보는 http://jade.cs.pusan.ac.kr/${\sim}$proten에서 볼 수 있다.

• Proceeding of EDISON Challenge
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• 2014.03a
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• pp.103-113
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• 2014

Hydrophobicity is the key concept to understand the role of water in protein folding, protein self-assembly, and protein-ligand interaction. Conventionally, hydrophobicity of amino acids in a protein has been argued based on hydrophobicity scales determined for individual free amino acids, assuming that those scales are unaltered when amino acids are embedded in a protein. Here, we investigate how the hydrophobicity of constituent amino acids depends on the protein context, in particular, on the total charge and secondary structures of a protein. To this end, we compute and analyze the hydration free energy - free energy change upon hydration quantifying the hydrophobicity - of three short proteins based on the integral-equation theory of liquids. We find that the hydration free energy of charged amino acids is significantly affected by the protein total charge and exhibits contrasting behavior depending on the protein net charge being positive or negative. We also observe that amino acids in the central ${\beta}$-strand sandwiched by ${\beta}$-sheets display more enhanced hydrophobicity than free amino acids, whereas those in the ${\alpha}$-helix do not clearly show such a tendency. Our results provide novel insights into the hydrophobicity of amino acids, and will be valuable for rationalizing and predicting the strength of water-mediated interaction involved in the biological activity of proteins.

• BMB Reports
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• v.49 no.6
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• pp.325-330
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• 2016

T-complex protein 10A homolog 2 (TCP10L) was previously demonstrated to be a potential tumor suppressor in human hepatocellular carcinoma (HCC). However, little is known about the molecular mechanism. MAX dimerization protein 1 (MAD1) is a key transcription suppressor that is involved in regulating cell cycle progression and Myc-mediated cell transformation. In this study, we identified MAD1 as a novel TCP10L-interacting protein. The interaction depends on the leucine zipper domain of both TCP10L and MAD1. TCP10L, but not the interaction-deficient TCP10L mutant, synergizes with MAD1 in transcriptional repression, cell cycle G1 arrest and cell growth suppression. Mechanistic exploration further revealed that TCP10L is able to stabilize intracellular MAD1 protein level. Consistently, the MAD1-interaction-deficient TCP10L mutant exerts no effect on stabilizing the MAD1 protein. Taken together, our results strongly indicate that TCP10L stabilizes MAD1 protein level through direct interaction, and they cooperatively regulate cell cycle progression.