• 사상체질의학회지
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• 제35권4호
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• pp.10-22
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• 2023

Objectives The aim of this study is to explore the mechanism of action and target diseases of Sasang constitutional prescriptions using a multiscale interactome approach. Methods The compound and target information of Sasang constitutional prescriptions were retrieved from various databases such as the TM-MC, STITCH, and TTD. Key targets for Sasang constitutional prescriptions were identified by selecting the top 100 targets based on the number of simple paths within the constructed network. Diffusion profiles for Sasang constitutional prescriptions and diseases were calculated based on a biased random walk algorithm. Potential diseases and key mechanisms of Sasang constitutional prescriptions were identified by analyzing diffusion profiles. Results We identified 144 Sasang constitutional prescriptions and their targets, finding 80 herbs with effective biological targets. A cluster analysis based on selecting up to 100 key targets for each prescription revealed a more cohesive grouping of prescriptions according to Sasang constitution. We then predicted potential diseases for 62 Sasang constitutional prescriptions using diffusion profiles calculated on a multiscale interactome. Finally, our analysis of diffusion profiles revealed key targets and biological functions of prescriptions in obesity and diabetes. Conclusions This study demonstrates the effectiveness of a multiscale interactome approach in elucidating the complex mechanisms and potential therapeutic applications of prescriptions in Sasang constitutional medicine.

• Molecules and Cells
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• 제41권2호
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• pp.150-159
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• 2018

Animals use their odorant receptors to receive chemical information from the environment. Insect odorant receptors differ from the G protein-coupled odorant receptors in vertebrates and nematodes, and very little is known about their protein-protein interactions. Here, we introduce a mass spectrometric platform designed for the large-scale analysis of insect odorant receptor protein-protein interactions. Using this platform, we obtained the first Orco interactome from Drosophila melanogaster. From a total of 1,186 identified proteins, we narrowed the interaction candidates to 226, of which only two-thirds have been named. These candidates include the known olfactory proteins Or92a and Obp51a. Around 90% of the proteins having published names likely function inside the cell, and nearly half of these intracellular proteins are associated with the endomembrane system. In a basic loss-of-function electrophysiological screen, we found that the disruption of eight (i.e., Rab5, CG32795, Mpcp, Tom70, Vir-1, CG30427, Eaat1, and CG2781) of 28 randomly selected candidates affects olfactory responses in vivo. Thus, because this Orco interactome includes physiologically meaningful candidates, we anticipate that our platform will help guide further research on the molecular mechanisms of the insect odorant receptor family.

• Genomics & Informatics
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• 제1권1호
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• pp.7-19
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• 2003

The latest measure of the relative evolutionary age of protein structure families was applied (based on taxonomic diversity) using the protein structural interactome map (PSIMAP). It confirms that, in general, protein domains, which are hubs in this interaction network, are older than protein domains with fewer interaction partners. We apply a hypothesis of 'biological network evolution' to explain the positive correlation between interaction and age. It agrees to the previous suggestions that proteins have acquired an increasing number of interaction partners over time via the stepwise addition of new interactions. This hypothesis is shown to be consistent with the scale-free interaction network topologies proposed by other groups. Closely co-evolved structural interaction and the dynamics of network evolution are used to explain the highly conserved core of protein interaction pathways, which exist across all divisions of life.

• Journal of Microbiology and Biotechnology
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• 제24권5호
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• pp.714-718
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• 2014

Apoptosis is the process of programmed cell death executed by specific proteases, the caspases, which mediate the cleavage of various vital proteins. Elucidating the consequences of this endoproteolytic cleavage is crucial to understanding cell death and other related biological processes. Although a number of possible roles for caspase-6 have been proposed, the identities and functions of proteins that interact with caspase-6 remain uncertain. In this study, we established a cell line expressing tandem affinity purification (TAP)-tagged caspase- 6 and then used LC-MS/MS proteomic analysis to analyze the caspase-6 interactome. Eight candidate caspase-6-interacting proteins were identified. Of these, five proteins (hnRNP-M, DHX38, ASPP2, MTA2, and UACA) were subsequently examined by co-immunoprecipitation for interactions with caspase-6. Thus, we identified two novel members of the caspase-6 interactome: hnRNP-M and MTA2.

• 한국유전체학회:학술대회논문집
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• 한국유전체학회 2005년도 The 14th Korea Genome Conference
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• pp.18-18
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• 2005

• BMB Reports
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• 제49권6호
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• pp.319-324
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• 2016

RNA polymerase II C-terminal domain phosphatases are newly emerging family of phosphatases that contain FCPH domain with Mg⁺²-binding DXDX(T/V) signature motif. Its subfamily includes small CTD phosphatases (SCPs). Recently, we identified several interacting partners of human SCP1 with appearance of dephosphorylation and O-GlcNAcylation. In this study, using an established cell line with inducible CTDSPL2 protein (a member of the new phosphatase family), proteomic screening was conducted to identify binding partners of CTDSPL2 in nuclear extract through immunoprecipitation of CTDSPL2 with its associated. This approach led to the identification of several interacting partners of CTDSPL2. This will provide a better understanding on CTDSPL2.

• Asian Pacific Journal of Cancer Prevention
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• 제15권10호
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• pp.4301-4305
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• 2014

Tanshinone IIA is a pharmacologically active ingredient extracted from Danshen, a Chinese traditional medicine. Its molecular mechanisms are still unclear. The present study utilized computational approaches to uncover the potential targets of this compound. In this research, PharmMapper server was used as the inverse docking tool andnd the results were verified by Autodock vina in PyRx 0.8, and by DRAR-CPI, a server for drug repositioning via the chemical-protein interactome. Results showed that the retinoic acid receptor alpha ($RAR{\alpha}$), a target protein in acute promyelocytic leukemia (APL), was in the top rank, with a pharmacophore model matching well the molecular features of Tanshinone IIA. Moreover, molecular docking and drug repurposing results showed that the complex was also matched in terms of structure and chemical-protein interactions. These results indicated that $RAR{\alpha}$ may be a potential target of Tanshinone IIA for APL. The study can provide useful information for further biological and biochemical research on natural compounds.

• Genomics & Informatics
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• 제19권1호
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• pp.3.1-3.12
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• 2021

Functional interpretation of noncoding genetic variants associated with complex human diseases and traits remains a challenge. In an effort to enhance our understanding of common germline variants associated with lung cancer, we categorize regulatory elements based on eight major cell types of human lung tissue. Our results show that 21.68% of lung cancer-associated risk variants are linked to noncoding regulatory elements, nearly half of which are cell type-specific. Integrative analysis of high-resolution long-range chromatin interactome maps and single-cell RNA-sequencing data of lung tumors uncovers number of putative target genes of these variants and functionally relevant cell types, which display a potential biological link to cancer susceptibility. The present study greatly expands the scope of functional annotation of lung cancer-associated genetic risk factors and dictates probable cell types involved in lung carcinogenesis.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2000년도 International Symposium on Bioinformatics
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• pp.56-58
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• 2000

Post-genomics may be defined in different ways depending on how one views the challenges after the genome. A popular view is to follow the concept of the central dogma in molecular biology, namely from genome to transcriptome to proteome. Projects are going on to analyze gene expression profiles both at the mRNA and protein levels and to catalog protein 3D structure families, which will no doubt help the understanding of information in the genome. However complete, such catalogs of genes, RNAs, and proteins only tell us about the building blocks of life. They do not tell us much about the wiring (interaction) of building blocks, which is essential for uncovering systemic functional behaviors of the cell or the organism. Thus, an alternative view of post-genomics is to go up from the molecular level to the cellular level, and to understand, what I call, the "interactome"or a complete picture of molecular interactions in the cell. KEGG (http://www.genome.ad.jp/kegg/) is our attempt to computerize current knowledge on various cellular processes as a collection of "generalized"protein-protein interaction networks, to develop new graph-based algorithms for predicting such networks from the genome information, and to actually reconstruct the interactomes for all the completely sequenced genomes and some partial genomes. During the reconstruction process, it becomes readily apparent that certain pathways and molecular complexes are present or absent in each organism, indicating modular structures of the interactome. In addition, the reconstruction uncovers missing components in an otherwise complete pathway or complex, which may result from misannotation of the genome or misrepresentation of the KEGG pathway. When combined with additional experimental data on protein-protein interactions, such as by yeast two-hybrid systems, the reconstruction possibly uncovers unknown partners for a particular pathway or complex. Thus, the reconstruction is tightly coupled with the annotation of individual genes, which is maintained in the GENES database in KEGG. We are also trying to expand our literature surrey to include in the GENES database most up-to-date information about gene functions.

• 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.