• 한국콘텐츠학회논문지
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• 제8권1호
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• pp.259-271
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• 2008

본 논문에서는 단백질-단백질 상호작용과 도메인 분석을 통해 기능이 알려지지 않은 미지 단백질의 기능을 예측할 수 있는 알고리즘을 제안한다. 먼저 MIPS 데이터베이스로부터 효모에 대한 단백질-단백질 상호작용(PPI) 네트러크를 구축한다. 구축된 PPI 네트워크는(단백질 3,637개, 상호작용 10,391개) 많은 상호작용을 갖는 소수의 단백질들을 갖으면서 단백질 클러스터의 고유한 모듈성을 보이는 스케일 프리 네트워크와 계층적 네트워크의 특성을 보인다 단백질-단백질 상호작용 데이터베이스는 Y2보(Yeast Two Hybrid) 실험 등으로 얻어졌기 때문에 부정확한 데이터를 포함하고 있다. 따라서 본 논문에서는 세포상의 localization을 고려하여 부정확한 데이터를 정제하여 PPI 네트워크를 재구축한다. 그리고 허브 단백질과 네트워크 구조를 분석하여 네트워크로부터 구조적 모듈을 발견하고 이를 정의한다. 또한 이러한 구조적 모듈로부터 단백질의 도메인을 분석하여 기능적 모듈을 밝히고, 높은 확실성을 가지는 기능적 모듈을 기반으로 미지 단백질에 대한 기능을 예측한다.

• IMMUNE NETWORK
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• 제2권3호
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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.

• 통합자연과학논문집
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• 제11권2호
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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.

• 정보과학회 컴퓨팅의 실제 논문지
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• 제23권3호
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• pp.194-198
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• 2017

본 논문에서는 학술 문헌에서 표현된 단백질 간 상호 작용(Protein-Protein Interaction) 정보를 자동으로 추출하기 위한 확장된 형태의 Convolutional Neural Network (CNN) 모델을 제안한다. 이 모델은 기존에 관계 추출(Relation Extraction)을 위해 고안된 단순 자질 기반의 CNN 모델을 확장하여 다양한 전역 자질들을 추가적으로 적용함으로써 성능을 개선할 수 있는 장점이 있다. PPI 추출 성능 평가를 위해서 많이 활용되고 있는 준거 평가 컬렉션인 AIMed를 이용한 실험에서 F-스코어 기준으로 78.0%를 나타내어 현재까지 도출된 세계 최고 성능에 비해 8.3% 높은 성능을 나타내었다. 추가적으로 CNN 모델이 복잡한 언어 처리를 통한 자질 추출 작업을 하지 않고도 단백질간 상호 작용 추출에 높은 성능을 나타냄을 보였다.

• Bulletin of the Korean Chemical Society
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• 제28권6호
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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.

• EDISON SW 활용 경진대회 논문집
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• 제5회(2016년)
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• pp.163-166
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• 2016

Hydrophobicity is the key concept to understand the water plays in protein folding, protein aggregation, and protein-protein interaction. Traditionally, the hydrophobicity of protein is defined based on the scales of the hydrophobicity of residue, assuming that the hydrophobicity of free amino acids is maintained. Here, we explore how the hydrophobicity of constituting amino acids in protein rely on the protein context, in particular, on the total charge and secondary structures of a protein. To this end, we calculate and investigate the hydration free energy 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 total charge being positive or negative. We also observe that amino acids in the ${\beta}-sheets$ display more enhanced the hydrophobicity than amino acids in the loop, whereas those in the ${\alpha}-helix$ do not clearly show such a tendency. And the salt-bridge forming amino acids also exhibit increase of the hydrophobicity than that with no salt bridge. 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.

• 한국식물병리학회:학술대회논문집
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• 한국식물병리학회 2003년도 정기총회 및 추계학술발표회
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• pp.29-29
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• 2003

Incompatible plant-pathogen interactions result in the rapid cell death response known as hypersensitive response (HR) and activation of host defense-related genes. To understand the molecular and cellular mechanism controlling defense response better, several approaches including isolation and characterization of novel genes, promoter analysis of those genes, protein-protein interaction analysis and reverse genetic approach etc. By using the yeast two-hybrid system a clone named Tsipl, Tsil -interacting protein 1, was isolated whose translation product apparently interacted with Tsil, an EREBP/AP2 type DNA binding protein. RNA gel blot analysis showed that the expression of Tsipl was increased by treatment with NaCl, ethylene, salicylic acid, or gibberellic acid. Transient expression analysis using a Tsipl::smGFP fusion gene in Arabidopsis protoplasts indicated that the Tsipl protein was targeted to the outer surface of chloroplasts. The targeted Tsipl::smGFP proteins were diffused to the cytoplasm of protoplasts in the presence of salicylic acid (SA) The PEG-mediated co-transfection analysis showed that Tsipl could interact with Tsil in the nucleus. These results suggest that Tsipl-Tsil interaction might serve to regulate defense-related gene expression. Basically the useful promoters are valuable tools for effective control of gene expression related to various developmental and environmental condition.(중략)

• BMB Reports
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• 제38권4호
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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.

• BMB Reports
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• 제51권10호
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• pp.526-531
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• 2018

Protein-Protein Interactions (PPIs) play essential roles in diverse biological processes and their misregulations are associated with a wide range of diseases. Especially, the growing attention to PPIs as a new class of therapeutic target is increasing the need for an efficient method of cell-based PPI analysis. Thus, we newly developed a robust PPI assay (SeePPI) based on the co-translocation of interacting proteins to the discrete subcellular compartment 'processing body' (p-body) inside living cells, enabling a facile analysis of PPI by the enriched fluorescent signal. The feasibility and strength of SeePPI (${\underline{S}}ignal$ ${\underline{e}}nhancement$ ${\underline{e}}xclusively$ on ${\underline{P}}-body$ for ${\underline{P}}rotein-protein$ ${\underline{I}}nteraction$) assay was firmly demonstrated with FKBP12/FRB interaction induced by rapamycin within seconds in real-time analysis of living cells, indicating its recapitulation of physiological PPI dynamics. In addition, we applied p53/MDM2 interaction and its dissociation by Nutlin-3 to SeePPI assay and further confirmed that SeePPI was quantitative and well reflected the endogenous PPI. Our SeePPI assay will provide another useful tool to achieve an efficient analysis of PPIs and their modulators in cells.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2003년도 제2차 연례학술대회 발표논문집
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• pp.26-51
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• 2003

Large scale protein interaction maps provide a new, global perspective with which to analyse protein function. PSIMAP, the Protein Structural Interactome Map, is a database of all the structurally observed interactions between superfamilies of protein domains with known three-dimensional structure in thePDB. PSIMAP incorporates both functional and evolutionary information into a single network. It makes it possible to age protein domains in terms of taxonomic diversity, interaction and function. One consequence of it is to predict the most important protein domain structure in evolution. We present a global analysis of PSIMAP using several distinct network measures relating to centrality, interactivity, fault-tolerance, and taxonomic diversity. We found the following results: ${\bullet}$ Centrality: we show that the center and barycenter of PSIMAP do not coincide, and that the superfamilies forming the barycenter relate to very general functions, while those constituting the center relate to enzymatic activity. ${\bullet}$ Interactivity: we identify the P-loop and immunoglobulin superfamilies as the most highly interactive. We successfully use connectivity and cluster index, which characterise the connectivity of a superfamily's neighbourhood, to discover superfamilies of complex I and II. This is particularly significant as the structure of complex I is not yet solved. ${\bullet}$ Taxonomic diversity: we found that highly interactive superfamilies are in general taxonomically very diverse and are thus amongst the oldest. This led to the prediction of the oldest and most important protein domain in evolution of lift. ${\bullet}$ Fault-tolerance: we found that the network is very robust as for the majority of superfamilies removal from the network will not break up the network. Overall, we can single out the P-loop containing nucleotide triphosphate hydrolases superfamily as it is the most highly connected and has the highest taxonomic diversity. In addition, this superfamily has the highest interaction rank, is the barycenter of the network (it has the shortest average path to every other superfamily in the network), and is an articulation vertex, whose removal will disconnect the network. More generally, we conclude that the graph-theoretic and taxonomic analysis of PSIMAP is an important step towards the understanding of protein function and could be an important tool for tracing the evolution of life at the molecular level.