• Journal of Information Processing Systems
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• v.8 no.3
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• pp.459-470
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• 2012

Recently, high-throughput technologies such as the two-hybrid system, protein chip, Mass Spectrometry, and the phage display have furnished a lot of data on protein-protein interactions (PPIs), but the data has not been accurate so far and the quantity has also been limited. In this respect, computational techniques for the prediction and validation of PPIs have been developed. However, existing computational methods do not take into account the fact that a PPI is actually originated from the interactions of domains that each protein contains. So, in this work, the information on domain modules of individual proteins has been employed in order to find out the protein interaction relationship. The system developed here, WASPI (Web-based Assistant System for Protein-protein interaction Inference), has been implemented to provide many functional insights into the protein interactions and their domains. To achieve those objectives, several preprocessing steps have been taken. First, the domain module information of interacting proteins was extracted by taking advantage of the InterPro database, which includes protein families, domains, and functional sites. The InterProScan program was used in this preprocess. Second, the homology comparison with the GO (Gene Ontology) and COG (Clusters of Orthologous Groups) with an E-value of $10^{-5}$, $10^{-3}$ respectively, was employed to obtain the information on the function and annotation of each interacting protein of a secondary PPI database in the WASPI. The BLAST program was utilized for the homology comparison.

• Rapid Communication in Photoscience
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• v.4 no.1
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• pp.1-8
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• 2015

For understanding molecular mechanisms of photochemical reactions, in particular reactions of proteins with biological functions, it is important to elucidate both the initial reactions from the photoexcited states and the series of subsequent chemical reactions, e.g., conformation, intermolecular interactions (hydrogen bonding, hydrophobic interactions), and inter-protein interactions (oligomer formation, dissociation reactions). Although time-resolved detection of such dynamics is essential, these dynamics have been very difficult to track by traditional spectroscopic techniques. Here, relatively new approaches for probing the dynamics of protein photochemical reactions using time-resolved transient grating (TG) are reviewed. By using this method, a variety of spectrally silent dynamics can be detected and such data provide a valuable description about the reaction scheme. Herein, a blue light sensor protein TePixD is the exemplar. The initial photochemistry for TePixD occurs around the chromophore and is detected readily by light absorption, but subsequent reactions are spectrally silent. The TG experiments revealed conformational changes and changes in inter-protein interactions, which are essential for TePixD function. The TG experiments also showed the importance of fluctuations of the intermediates as the driving force of the reaction. This technique is complementary to optical absorption detection methods. The TG signal contains a variety of unique information, which is difficult to obtain by other methods. The advantages and methods for signal analyses are described in detail in this review.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2002.06a
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• pp.5-23
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• 2002

Motivation: Protein-protein interaction plays a critical role in the biological processes. The identification of interacting proteins by bioinformatical methods can provide new lead In the functional studies of uncharacterized proteins without performing extensive experiments. Results: Protein-protein interactions are predicted by a computational algorithm based on the weighted scoring system for domain interactions between interacting protein pairs. Here we propose potential interaction domain (PID) pairs can be extracted from a data set of experimentally identified interacting protein pairs. where one protein contains a domain and its interacting protein contains the other. Every combinations of PID are summarized in a matrix table termed the PID matrix, and this matrix has proposed to be used for prediction of interactions. The database of interacting proteins (DIP) has used as a source of interacting protein pairs and InterPro, an integrated database of protein families, domains and functional sites, has used for defining domains in interacting pairs. A statistical scoring system. named "PID matrix score" has designed and applied as a measure of interaction probability between domains. Cross-validation has been performed with subsets of DIP data to evaluate the prediction accuracy of PID matrix. The prediction system gives about 50% of sensitivity and 98% of specificity, Based on the PID matrix, we develop a system providing several interaction information-finding services in the Internet. The system, named PreDIN (Prediction-oriented Database of Interaction Network) provides interacting domain finding services and interacting protein finding services. It is demonstrated that mapping of the genome-wide interaction network can be achieved by using the PreDIN system. This system can be also used as a new tool for functional prediction of unknown proteins.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.431-436
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• 2005

Living cells are sustained not by individual activities but rather by coordinated summative efforts of different biological functional modules. While recent research works have focused largely on finding individual functional modules, this paper attempts to explore the connections or relationships between different cellular functions through cross-function domain interaction maps. Exploring such a domain interaction map can help understand the underlying inter-function communication mechanisms. To construct a cross-function domain interaction map from existing genome-wide protein-protein interaction datasets, we propose a two-step procedure. First, we infer conserved domain-domain interactions from genome-wide protein-protein interactions of yeast, worm and fly. We then build a cross-function domain interaction map that shows the connections of different functions through various conserved domain interactions. The domain interaction maps reveal that conserved domain-domain interactions can be found in most detected cross-functional relationships and a f9w domains play pivotal roles in these relationships. Another important discovery in the paper is that conserved domains correspond to highly connected protein hubs that connect different functional modules together.

• Genomics & Informatics
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• v.7 no.3
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• pp.141-147
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• 2009

Developed proteome-scale ortholog and paralog prediction methods are mainly based on sequence similarity. However, it is known that even the closest BLAST hit often does not mean the closest neighbor. For this reason, we added conserved interaction information to find orthologs. We propose a genome-scale, automated ortholog prediction method, named OrthoInterBlast. The method is based on both sequence and interaction similarity. When we applied this method to fly and yeast, 17% of the ortholog candidates were different compared with the results of Inparanoid. By adding protein-protein interaction information, proteins that have low sequence similarity still can be selected as orthologs, which can not be easily detected by sequence homology alone.

• Journal of KIISE:Computing Practices and Letters
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• v.10 no.4
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• pp.299-308
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• 2004

In this paper, we propose a probabilistic framework to predict the interaction probability of proteins. The notion of domain combination and domain combination pair is newly introduced and the prediction model in the framework takes domain combination pair as a basic unit of protein interactions to overcome the limitations of the conventional domain pair based prediction systems. The framework largely consists of prediction preparation and service stages. In the prediction preparation stage, two appearance probability matrices, which hold information on appearance frequencies of domain combination pairs in the interacting and non-interacting sets of protein pairs, are constructed. Based on the appearance probability matrix, a probability equation is devised. The equation maps a protein pair to a real number in the range of 0 to 1. Two distributions of interacting and non-interacting set of protein pairs are obtained using the equation. In the prediction service stage, the interaction probability of a Protein pair is predicted using the distributions and the equation. The validity of the prediction model is evaluated for the interacting set of protein pairs in Yeast organism and artificially generated non-interacting set of protein pairs. When 80% of the set of interacting protein pairs in DIP database are used as teaming set of interacting protein pairs, very high sensitivity(86%) and specificity(56%) are achieved within our framework.

• Journal of the Korean Vacuum Society
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• v.16 no.1
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• pp.52-57
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• 2007

The interaction force between biomolecules(DNA-DNA, antigen-antibody, ligand-receptor, protein-protein) defines not only biomolecular function, but also their mechanical properties and hence bio-sensor. Atomic force microscopy(AFM) is nowadays frequently applied to determine interaction forces between biological molecules and biomolecular force measurements, obtained for example using AFM can provide valuable molecular-level information on the interactions between biomolecules. A proper modification of an AFM tip and/or a substrate with biomolecules permits the direct measurement of intermolecular interactions, such as DNA-DNA, protein-protein, and ligand-receptor, etc. and a microcantilever-based sensor appeared as a promising approach for ultra sensitive detection of biomolecular interactions.

• Bulletin of the Korean Chemical Society
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• v.32 no.5
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• pp.1640-1644
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• 2011

Water-soluble mutant of intrinsically insoluble protein, crambin, was produced by mutagenesis based on the sequence analysis with homologous proteins. Thr1, Phe13, and Lys33 of crambin were substituted for Lys, Tyr, and Lys, respectively. The resultant mutant was soluble in aqueous buffer as well as in dodecylphosphocholine (DPC) micelle solution. The $^1H-^{15}N$ spectrum of the mutant crambin showed spectral similarity to that of the wild-type protein except for local regions proximal to the sites of mutation. Solution structure of water-soluble mutant crambin was determined in aqueous buffer by NMR spectroscopy. The structure was almost identical to the wild-type structure determined in non-aqueous solvent. Subtle difference in structure was very local and related to the change of the intra- and inter-protein hydrophobic interaction of crambin. The structural details for the enhanced solubility of crambin in aqueous solvent by the mutation were provided and discussed.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.5
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• pp.721-733
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• 2019

Objective: The objectives of this study were to investigate the thermal gelation properties and molecular forces of actomyosin extracted from two classes of chicken breast meat qualities (normal and pale, soft and exudative [PSE]-like) during heating process to further improve the understanding of the variations of functional properties between normal and PSE-like chicken breast meat. Methods: Actomyosin was extracted from normal and PSE-like chicken breast meat and the gel strength, water-holding capacity (WHC), protein loss, particle size and distribution, dynamic rheology and protein thermal stability were determined, then turbidity, active sulfhydryl group contents, hydrophobicity and molecular forces during thermal-induced gelling formation were comparatively studied. Results: Sodium dodecyl sulphate-polyacrylamide gel electrophoresis showed that protein profiles of actomyosin extracted from normal and PSE-like meat were not significantly different (p>0.05). Compared with normal actomyosin, PSE-like actomyosin had lower gel strength, WHC, particle size, less protein content involved in thermal gelation forming (p<0.05), and reduced onset temperature ($T_o$), thermal transition temperature ($T_d$), storage modulus (G') and loss modulus (G"). The turbidity, reactive sulfhydryl group of PSE-like actomyosin were higher when heated from $40^{\circ}C$ to $60^{\circ}C$. Further heating to $80^{\circ}C$ had lower transition from reactive sulfhydryl group into a disulfide bond and surface hydrophobicity. Molecular forces showed that hydrophobic interaction was the main force for heat-induced gel formation while both ionic and hydrogen bonds were different significantly between normal and PSE-like actomyosin (p<0.05). Conclusion: These changes in chemical groups and inter-molecular bonds affected protein-protein interaction and protein-water interaction and contributed to the inferior thermal gelation properties of PSE-like meat.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.243-248
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• 2005

도메인 조합에 기반한 단백질 상호작용 예측 기법은 효모와 같은 특정 종에 대하여 우수한예측 정확도를 보이는 것으로 알려졌으나, 인간과 같은 고등 생명체의 단백질에 대한 상호작용 예측을 수행하기 위하여는 여러종에 대한 기법의 적절성검증과 최적의 학습집단 구성 방안에 대한 연구가 선행되어야 한다. 본 논문에서는, 초파리 단백질을 이용한 예측 정확도 검증으로 도메인 조합 기법의 일반화 가능성을 타진 하고 이종간의 상호작용 예측실험 및 정확도 검증을 통하여 비교적 연구가 덜 되어진 종의 단백질 상호작용 예측을 위한 학습집단 구성 방법에 대하여 기술한다. 초파리 실험에서는 10351개의 상호작용이 있는 단백질 쌍 가운데, 80%와 20%를 각각 학습집단 및 실험집단으로 사용하였으며, 상호작용이 없는단백질 쌍의 학습집단은 1배에서 5배까지 변화시키면서 예측 정확도를 관찰하였다. 이 결과77.58%의 민감도와 92.61%의 특이도를 확인하였다. 이종간의 상호작용 예측 실험은 효모, 초파리, 효모, 초파리에 해당하는 학습집단 각각을 바탕으로 Human, Mouse, E. coli, C. elegans 등의 단백질 상호작용 예측을 수행하였다. 실험 곁과 학습집단의 도메인이 실험집단의 도메인과 많이 겹칠수록 높은 정확도를 보여주었으며, 도메인 집단간의 유사도를 나타내기 위해 고안한 Domain Overlapping Rate(DOR) 는 상호작용 예측 정확도의 중요한 요소임을 찾아내었다.