• 인지과학
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• 제28권4호
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• pp.299-314
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• 2017

In-silico 기반의 약물-표적 단백질 연관관계 예측은 신약 탐색 단계에서 매우 중요하다. 그러나 기존의 예측모델은 입력 값이 고정적이며 표적 단백질의 특질 값이 가공된 데이터로 한정됨으로써 예측 모델의 확장성과 유연성이 부족하다. 본 논문에서는 약물-표적 단백질 연관관계를 예측하는 확장 가능한 형태의 머신러닝 모델을 소개한다. 확장 가능한 머신러닝 모델의 핵심 아이디어는 쌍기반의 뉴럴 네트워크로써, 약물과 단백질의 미가공 데이터를 사용하여 특질을 추출하고 특질 값을 각각의 뉴럴 네트워크 레이어에 입력한다. 이 방법은 추가적인 지식없이 자동적으로 약물과 단백질의 특질을 추출한다. 또한 쌍기반 레이어는 특질 값을 풍부한 저차원의 벡터로 향상 시킴으로써 입력 값의 차이로 인한 편향 학습을 방지한다. PubChem BioAssay(PCBA) 데이터 셋에 기반한 5-폴드 교차 검증법을 통하여 제안한 모델의 성능을 평가했으며, 이전의 모델보다 우월한 성능을 보였다.

• 한국자기공명학회논문지
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• 제20권1호
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• pp.22-26
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• 2016

FANCJ is a DNA helicase which contributes genome stability by resolving G-quadruplex DNA from 5' to 3' direction. In addition to main ATPase helicase core, FANCJ has the protein binding region at its C-terminal part. BRCA1 and BLM are the binding partner of FANCJ and these protein-protein interactions contribute genomic stability and the proper response to replication stress. As the first attempt for studying FANCJ-BLM interaction, we prepared BLM binding region of FANCJ and characterized with CD and NMR spectroscopy. FANCJ (881-941) with N-ter 6xHis was purified as the oligomer. Secondary structure prediction based on CD data revealed that FANCJ (881-941) composed with ${\beta}$ sheet, turn and coils.$^1H-^{15}N$ HSQC spectra showed nonhomogeneous peak intensities with less number of peaks comparing than the number of amino acids in the construct. It indicated that optimization should be necessary for detailed further structural studies.

• 대한수의학회지
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• 제24권1호
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• pp.24-30
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• 1984

The protective effects of high levels of dietary iron, copper, zinc or protein on lead toxicity were studied In chicks. Growth retardation, reduction of feed intake, anemia and accumulation of lead in the bone and kidney were observed in chicks fed a diet containing 500mg lead as chloride per kg of feed for 42 days. Early changes due to ingested lead were inhibition of red blood cell ${\delta}$-aminolevulinic acid dehydrase at all doses and no effect of iron, copper, zinc or protein addition were observed. Tibia lead accumulation was reduced in chicks receiving additional dietary iron or zinc compared to the lead only group but increased in chicks given supplementary protein. Decreased body weight gain was overcome by supplementary zinc or protein in chicks fed lead but not by supplementary iron. Overall the results of this study show that lead poisoning can be partly reduced by providing supplementary iron, zinc or protein, but the interaction of these element remained to be elucidated.

• 통합자연과학논문집
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• 제10권3호
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• pp.125-130
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• 2017

Glucagon like pepide-2, one of the GLPs, is involved in various metabolic functions in the gastrointestinal tract. It plays a major role in the regulation of mucosal epithelium and the intestinal crypt cell proliferation. Because of their therapeutic importance towards the diseases in the gastrointestinal tract, it becomes necessary to study their interaction with its receptor, GLP-2R. In this study, we have developed protein-protein docking complexes of GLP-2 - GLP-2 receptor. Homology models of GLP-2 are developed, and a reliable model out of the predicted models was selected after model validation. The model was bound with the receptor, to study the important interactions of the complex. This study could be useful in developing novel and potent drugs for the diseases related with GLP-2.

• 한국응용약물학회:학술대회논문집
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• 한국응용약물학회 2008년도 Proceedings of the Convention
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• pp.77-86
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• 2008

It's been known that overexpression of the oncoprotein Her2 (eu/ErbB2), transmembrane receptor protein, occurs in human breast cancer. Her2-positive breast cancer patients who have Her2 overexpression show less therapeutic efficacy with enhanced metathesis and increased resistance to chemotherapy. So far, a humanized monoclonal antibody against Her2 protein called Herceptin is the only drug approved by Food and Drug Administration for treatment of Her2-overexpressing breast tumors. However, antibody therapy of Herceptin may not be ideal method for therapeutic intervention of Her2 protein expression. The therapeutic intervention of Her2 protein expression may be more efficiently achieved by inhibiting the expression of Her2 gene rather than by down-regulating the Her2 protein already overexpressed. Here, we found that the interaction of two proteins of ESX (an epithelial-restricted transcription factor) and DRIP130/CRSP130/Sur2 (a Ras-linked subunit of human mediator complexes) mediates the expression of Her2 gene. The association of ESX with Sur2 is mediated by a small hydrophobic face of 8-amino acid helix in ESX, suggesting that the ESX-Sur2 interaction can be a new novel target for Her2-positive cancer. The process to develop potent ESX-Sur2 interaction inhibitors targeting for Her2-positive cancer therapeutics will be discussed.

• BMB Reports
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• 제35권6호
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• pp.562-567
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• 2002

In order to find the cellular interaction factors of the Heliothis armigera nuclear polyhedrosis virus capsid protein VP39, a Heliothis armigera cell cDNA library was constructed. Then VP39 was used as bait. The host actin gene was isolated from the cDNA library with the yeast two-hybrid system. This demonstrated that VP39 could interact with its host actin in yeast. In order to corroborate this interaction in vivo, the vp39 gene was fused with the green fluorescent protein gene in plasmid pEGFP39. The fusion protein was expressed in the Hz-AM1 cells under the control of the Autographa californica multiple nucleopolyhedrovirus immediate early gene promoter. The host actin was labeled specifically by the red fluorescence substance, tetramethy rhodamine isothicyanete-phalloidin. Observation under a fluorescence microscopy showed that VP39, which was indicated by green fluorescence, began to appear in the cells 6 h after being transfected with pEGFP39. Red actin cables were also formed in the cytoplasm at the same time. Actin was aggregated in the nucleus 9 h after the transfection. The green and red fluorescence always appeared in the same location of the cells, which demonstrated that VP39 could combine with the host actin. Such a combination would result in the actin skeleton rearrangement.

• Journal of Microbiology and Biotechnology
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• 제31권8호
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• pp.1183-1189
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• 2021

Autodisplay of a multimeric protein complex on a cell surface is limited by intrinsic factors such as the types and orientations of anchor modules. Moreover, improper folding of proteins to be displayed often hinders functional cell surface display. While overcoming these drawbacks, we ultimately extended the applicability of the autodisplay platform to the display of a protein complex. We designed and constructed a cell surface attachment (CSA) system that uses a non-covalent protein-protein interaction. We employed the high-affinity interaction mediated by an orthogonal cohesin-dockerin (Coh-Doc) pair from Archaeoglobus fulgidus to build the CSA system. Then, we validated the orthogonal Coh-Doc binding by attaching a monomeric red fluorescent protein to the cell surface. In addition, we evaluated the functional anchoring of proteins fused with the Doc module to the autodisplayed Coh module on the surface of Escherichia coli. The designed CSA system was applied to create a functional attachment of dimeric α-neoagarobiose hydrolase to the surface of E. coli cells.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권3호
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• pp.771-791
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• 2022

Protein-protein interaction (PPI) extraction from original text is important for revealing the molecular mechanism of biological processes. With the rapid growth of biomedical literature, manually extracting PPI has become more time-consuming and laborious. Therefore, the automatic PPI extraction from the raw literature through natural language processing technology has attracted the attention of the majority of researchers. We propose a PPI extraction model based on the large pre-trained language model and adversarial training. It enhances the learning of semantic and syntactic features using BioBERT pre-trained weights, which are built on large-scale domain corpora, and adversarial perturbations are applied to the embedding layer to improve the robustness of the model. Experimental results showed that the proposed model achieved the highest F1 scores (83.93% and 90.31%) on two corpora with large sample sizes, namely, AIMed and BioInfer, respectively, compared with the previous method. It also achieved comparable performance on three corpora with small sample sizes, namely, HPRD50, IEPA, and LLL.

• Genomics & Informatics
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• 제21권1호
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• pp.6.1-6.8
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• 2023

Glaucoma is the second leading cause of irreversible blindness, and primary open-angle glaucoma (POAG) is the most common type. Due to inadequate diagnosis, treatment is often not administered until symptoms occur. Hence, approaches enabling earlier prediction or diagnosis of POAG are necessary. We aimed to identify novel drugs for glaucoma through bioinformatics and network analysis. Data from 36 samples, obtained from the trabecular meshwork of healthy individuals and patients with POAG, were acquired from a dataset. Next, differentially expressed genes (DEGs) were identified to construct a protein-protein interaction (PPI) network. In both stages, the genes were enriched by studying the critical biological processes and pathways related to POAG. Finally, a drug-gene network was constructed, and novel drugs for POAG treatment were proposed. Genes with p < 0.01 and |log fold change| > 0.3 (1,350 genes) were considered DEGs and utilized to construct a PPI network. Enrichment analysis yielded several key pathways that were upregulated or downregulated. For example, extracellular matrix organization, the immune system, neutrophil degranulation, and cytokine signaling were upregulated among immune pathways, while signal transduction, the immune system, extracellular matrix organization, and receptor tyrosine kinase signaling were downregulated. Finally, novel drugs including metformin hydrochloride, ixazomib citrate, and cisplatin warrant further analysis of their potential roles in POAG treatment. The candidate drugs identified in this computational analysis require in vitro and in vivo validation to confirm their effectiveness in POAG treatment. This may pave the way for understanding life-threatening disorders such as cancer.

• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2004년도 추계 종합학술대회 논문집
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• pp.511-515
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• 2004

Post-genome 시대에는 유전체뿐만 아니라 단백질에 대한 연구의 필요성이 증대되고 있다. 특히 단백질-단백질 상호작용 및 단백질 네트워크에 대한 연구를 기반으로 전체 생물 시스템을 분석하는 연구가 중요한 이슈로 떠오르고 있다. 기존에 생물학자들이 실험을 통해서 증명한 사실들을 논문이나 기타 매체를 통해서 공개를 하고 있다. 하지만 공개된 정보의 양이 방대하므로 생물학자들이 정보를 효율적으로 이용하지 못하는 경우가 많다. 인터넷의 발달로 하루에도 수 없이 쏟아져 나오는 연구 성과들에 쉽게 접근이 가능해졌다. 이러한 매체로부터 생물학적 의미를 가지는 정보를 효과적으로 추출하는 일이 중요하게 대두되었다. 따라서 본 연구에서는 인터넷상에 공개된 다량의 논문 및 기타정보 매체로부터 단백질-단백질 상호작용 정보를 추출한 데이터베이스로부터 단백질의 네트워크를 구성하고 단백질 네트워크를 통해서 생물학적 의미를 가지는 여러 가지 경로 분석 알고리즘을 설계하고 구현한다.