• Journal of Applied Biological Chemistry
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• v.63 no.4
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• pp.291-295
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• 2020

In order to increase the utilization of defatted sesame meal (DSM), a by-product of sesame oil production, the conditions of extraction of insoluble proteins from DSM by enzyme treatment were investigated. As a result of comparing the treatment results of proteolytic enzymes Alcalase, Flavorzyme, Neutrase, and Protamex with control, Protamex was effective in increasing the total solid and protein content. At the reaction conditions of Protamex (50 ℃, pH 6.0), the dosage of enzymes was appropriate for 1% of DSM and 3 h of enzyme reaction time. To improve the efficiency of enzymatic treatment, the protein content extracted increased as the heat treatment temperature increased, and slightly increased above 110 ℃. As a result of investigating the effect of the combination treatment of cell lytic enzyme (Tunicase) and protease (Protamex) on protein solubilization, it was most effective to treat the cell lytic enzyme after processing the protease. After heat treatment (110 ℃, 10 min), sequential treatment of Protamex and Tunicase increased the protein content by about 3.5 times (9.85→35.58 mg/mL) of the non-heated control and 2.2 times (15.83→35.58 mg/mL) of the heat treated control.

• Annual Conference of KIPS
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• 2008.05a
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• pp.455-458
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• 2008

단백질체학에서 2-DE는 조직내의 단백질을 규명하는 단백질 분리 기술로서 2-DE에 의하여 생성된 단백질 이미지에서 스팟 매칭을 진행하여 상이한 단백질 젤 내에 존재하는 동일한 단백질 클래스를 찾을 수 있다. 그러나 단백질 2-DE 이미지는 실험 환경의 변화에 민감하여 이미지의 위치적인 변형이나 먼지, 공기방울 등으로 인해 많은 에러 정보를 포함할 수 있다. 이러한 에러는 스팟 매칭에 치명적인 영향을 주어 낮은 정확도를 가지게 된다. 본 논문에서는 단백질 2-DE 이미지 분석을 위한 스팟 매칭에서의 정확도를 향상시키기 위하여 기준점 학습과 기준점 추출의 두 단계로 이루어진 자동화된 기준점 추출 방법을 사용하여 스팟 매칭의 정확도를 향상시킬 수 있는 최적의 기준점을 선정하는 방법을 제안하며 선정된 기준점을 기반으로 다수의 기준 이미지를 선택하여 스팟 매칭을 반복적으로 진행함으로써 확률 기반의 정확한 스팟 매칭 결과를 도출하고자 한다. 특히 데이터 마이닝 기법에서 사용되는 최소지지도 값을 적용함으로써 지지도가 높은 스팟 매칭 결과를 빈발한 스팟 매칭으로 판정한다. 제안한 스팟 매칭 정확도 향상 기법의 정확도를 평가하기 위하여 실제 단백질 2-DE 젤 이미지 데이터를 사용하여 입력 기준점의 개수와 최소 지지도의 증가에 따른 정확도의 변화를 분석하였다.

• KIISE Transactions on Computing Practices
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• v.23 no.3
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• pp.194-198
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• 2017

In this paper, we propose a revised Deep Convolutional Neural Network (DCNN) model to extract Protein-Protein Interaction (PPIs) from the scientific literature. The proposed method has the merit of improving performance by applying various global features in addition to the simple lexical features used in conventional relation extraction approaches. In the experiments using AIMed, which is the most famous collection used for PPI extraction, the proposed model shows state-of-the art scores (78.0 F-score) revealing the best performance so far in this domain. Also, the paper shows that, without conducting feature engineering using complicated language processing, convolutional neural networks with embedding can achieve superior PPIE performance.

• The KIPS Transactions:PartB
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• v.15B no.4
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• pp.375-382
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• 2008

A protein's subcellular localization is considered an essential part of the description of its associated biomolecular phenomena. As the volume of biomolecular reports has increased, there has been a great deal of research on text mining to detect protein subcellular localization information in documents. It has been argued that linguistic information, especially syntactic information, is useful for identifying the subcellular localizations of proteins of interest. However, previous systems for detecting protein subcellular localization information used only shallow syntactic parsers, and showed poor performance. Thus, there remains a need to use a full syntactic parser and to apply deep linguistic knowledge to the analysis of text for protein subcellular localization information. In addition, we have attempted to use semantic information from the WordNet thesaurus. To improve performance in detecting protein subcellular localization information, this paper proposes a three-step method based on a full syntactic dependency parser and WordNet thesaurus. In the first step, we constructed syntactic dependency paths from each protein to its location candidate, and then converted the syntactic dependency paths into dependency trees. In the second step, we retrieved root information of the syntactic dependency trees. In the final step, we extracted syn-semantic patterns of protein subtrees and location subtrees. From the root and subtree nodes, we extracted syntactic category and syntactic direction as syntactic information, and synset offset of the WordNet thesaurus as semantic information. According to the root information and syn-semantic patterns of subtrees from the training data, we extracted (protein, localization) pairs from the test sentences. Even with no biomolecular knowledge, our method showed reasonable performance in experimental results using Medline abstract data. Our proposed method gave an F-measure of 74.53% for training data and 58.90% for test data, significantly outperforming previous methods, by 12-25%.

• Parasites, Hosts and Diseases
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• v.25 no.2
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• pp.159-167
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• 1987

To analyse the antigen specificity of patients sera from 24 confirmed neurocysticercosis and a monoclonal antibody, SDS-PAGE using 10~15% linear gradient gel and EITB were done. Cystic fluid, saline extracts of scolex and of whole worm of C. cellulosae, saline extracts of sparganum, hydatid cyst fluid, saline extracts of Fasciola, Clonorchis and Paragonimus were used as antigen. Of protein bands in cystic fluid of C. cellulosae, patient sera reacted frequently to bands of 152, 94, 64, 48, 24, 15, 10 and 7kDa proteins. To saline extracts of scolex and whole worm of C. cellulosae, patients sera reacted frequently to 94, 64, 52, 39, 34, 15 and 10kDa bands. Two bands in sparganum extract (130 and 64kDa) and two bands in hydatid cyst fluid (52 and 27kDa) were cross-reacting bands with sera from cysticercosis patients. Saline extracts of Fasciola, ClonorchiJ and Paragonimus did 'not exhibit cross-reacting bands. Monoclonal antibody to cystic fluid of C. cellulosae was found to react with low molecular weight proteins of 15, 10 and 7kDa.

• The Korean Journal of Mycology
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• v.36 no.2
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• pp.178-182
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• 2008

Although the number of patients with Acanthamoeba keratitis has increased dramatically since the widespread use of contact lens, it is still very hard to cure the disease. The proteases from the Acanthamoeba were reported to play important role in the pathogenesis of keratitis. In this study, the inhibitors for extracellular serine proteases of A. castellanii were screened from the extracts of 230 mushroom samples collected from various regions of Korea. The mushrooms were extracted with methanol and water ($65^{\circ}C$). Filtered and concentrated extracts (0.3 mg/ml) were preincubated with proteases before addition of peptide substrate N-succinyl-ala-ala-pro-phe p-anilide. The selected extracts showing strong inhibitory effects were characterized. Although inhibition with single extract was not so high enough, the complete inhibition was achieved with combination of two extracts. The selected extract showed little effect on other serine proteases such as thrombin (human and bovine) and on general protease such as protease K.

• Parasites, Hosts and Diseases
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• v.29 no.1
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• pp.1-8
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• 1991

Out of many component proteins in crude saline extract of Spirometra mansoni plerocercoid (sparganum) , 36 kDa and 29 kDa proteins were found to be the most antigenic and were already purified by immunoaffinity chromatography using monoclonal antibody as a ligand. In this study, a single step purification of these potent antigenic proteins of sparganum extract was investigated. When the crude saline extract was charged to gelatin-Sepharose 4B affinity column, 36 kDa and 29 kDa protein fractions were bound. SDS-polyacrylamide gel electrophoresis (PAGE) and SDS-PAGE/immunoblot confirmed that the bound protein to gelatin was serologically pure. When evaluated by ELISA with patients sera, the purified protein of 36 and 29 kDa also showed improved antigenicity.

• Korean journal of food and cookery science
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• v.13 no.5
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• pp.623-626
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• 1997

The purpose of this study was to investigate the properties of proteolytic enzymes extracted from mulberry (Morus alba L.). The protease activity of the enzymes from mulberry was 2,358 unit/g. The enzymes showed strong activities toward hemoglobin and collagen. The optimum temperature and pH of the enzymes were 50$^{\circ}C$ and 6.0, respectively. The enzymes were stable at the temperature range of 30$^{\circ}C$ to 60$^{\circ}C$ and the pH from 5.0 to 7.0 for 1 hr at 37$^{\circ}C$ of incubation and also retained whole activity after incubation for 1 hr at 60$^{\circ}C$.

• Proceedings of the Korea Contents Association Conference
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• 2011.05a
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• pp.341-342
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• 2011

선행연구에서 우리는 암과 관련된 단백질-단백질 상호작용 네트워크와 단백질-질병 네트워크를 통해서 핵심 단백질 60개를 추출했다. 이 단백질들을 조절하여 암을 제어하기 위한 방법으로 miRNA(microRNA)를 이용하기위해 단백질과 상호작용하는 miRNA와 miRNA 서열정보를 추출하였다. 한 단백질과 상호작용하는 miRNA의 수가 많았기 때문에 각각의 miRNA에 대해 우선순위를 주어서 가중치를 부여했는데, 기준으로는 miRNA 서열길이, 수소결합 수 등으로 잡아주었다. 이 방법을 사용함으로써 밝혀지지 않은 단백질과 miRNA의 상호작용 서열을 찾는데 이용가능 할 것이다.

• Proceedings of the Korea Contents Association Conference
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• 2016.05a
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• pp.191-192
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• 2016

DNA 염기서열 자체에는 변화가 없으나 크로마틴의 변형을 통하여 유전자의 발현 양상이 변하는 현상을 후성유전이라 한다. 최근에 이런 후성유전학적 변이가 암 발생과 밀접한 연관이 있는 것으로 알려졌다. 본 연구에서는 암 관련 단백질과 암 관련 후성유전 단백질 상호작용 네트워크를 통하여 암과 후성 유전적 관계를 분석하고자 하였다. 먼저 상호작용 네트워크를 기반으로 허브에 해당하는 히스톤 변형 단백질 20개를 추출하였다. 추출한 20개 단백질을 KEGG pathway에 적용하여 암 관련 단백질과의 상관관계를 분석하였다. 암 관련 단백질 발현양상을 확인할 수 있는 Expression Atlas로부터 발현이 증가하거나 감소하는 단백질을 분류하고, 발현 정보를 KEGG pathway 위에 있는 단백질에 적용함으로써 후성유전학적 암 발생 기전을 도출하였다.