• 한국생물정보학회:학술대회논문집
• /
• 한국생물정보시스템생물학회 2000년도 International Symposium on Bioinformatics
• /
• pp.23-27
• /
• 2000

Protein interaction is an important research topic in Bioinformatics. A novel computational method of protein interaction was developed. It shows the diverse pattern of protein protein interaction,

• 한국생물정보학회:학술대회논문집
• /
• 한국생물정보시스템생물학회 2002년도 제1차워크샵
• /
• pp.5-23
• /
• 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.

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

• Bioinformatics and Biosystems
• /
• 제1권2호
• /
• pp.128-133
• /
• 2006

This paper compares domain combination based protein-protein interaction prediction method with domain based protein-protein interaction method. The prediction accuracy and reliability of the methods are compared using the same prediction technique and interaction data. According to the comparison, domain combination based prediction method has showed superior prediction accuracy to domain based prediction method for protein pairs with fully overlapped domains with protein pairs in learning sets. When we consider that domain combination based method has the effects of assigning a weight to each domain interaction, it implies that we can improve the prediction accuracies of currently available domain or domain combination based protein interaction prediction methods further by developing more advanced weight assignment techniques. Several significant facts revealed from the comparative studies are also described in this paper.

• 한국정보과학회논문지:소프트웨어및응용
• /
• 제31권12호
• /
• pp.1602-1610
• /
• 2004

다양한 유전체 프로젝트로 말미암아 엄청난 서열 데이타들이 쏟아지고, 이에 따라 핵산 및 단백질 수준의 서열 데이타 분석이 매우 중요하게 인식되고 있다. 특히 최근에는 단백질이 단순하게 개별적인 기능을 가진 독립적인 요소가 아닌 전체 단백질 상호작용 네트워크 상에서 다른 객체들과 유기적인 관계를 갖으며 나름대로의 중요한 역할을 수행하고 있다는 점에 초점을 맞추어 연구가 진행되고 있다. 특히 단백질 상호작용 관계 분석을 위해서는 실제로 상호작용이 일어나는 도메인 모듈 정보가 아주 중요하게 작용하는데, 본 논문에서는 이러한 점을 고려하여 우리가 개발한 단백질 기능 및 상호작용 분석을 위한 PIVS(Protein-protein interaction Inference and Visualization System)에 대해 소개하고 있다 PIVS는 기존의 단백질 상호작용 데이타베이스들을 합쳐서 통합 데이타베이스를 생성하고, 다양한 전처리 과정으로 통합 데이타베이스 서열의 기능 및 주석 정보를 추출하여 로컬 데이타베이스화 하였다. 그리고 특히 단백질 상호작용 관계 분석을 위해 중요하게 작용하는 도메인 모듈 정보들을 추출하여 로컬 데이터베이스를 구축하였고, 기존의 단백질 상호작용 관계 데이타를 이용하석 도메인 사이의 상호작용 관계 정보도 수집하여 분석하였다. PIVS는 단백질의 종합적인 분석 정보, 즉, 기능 및 주석, 도메인, 상호작용 관계 정보 등을 손쉽고 편리하게 얻고자 하는 사용자에게 매우 유용하게 사용될 수 있을 것이다.

• 생명과학회지
• /
• 제14권6호
• /
• pp.997-1002
• /
• 2004

이 논문은 단백질의 기능분석을 위해 핵심적으로 요구되는 단백질 상호작용 관계정보 및 기능정보 등을 체계적으로 제공할 수 있는 WASPIFA (Web-based Assistant System for Protein-protein Interaction and function Analysis) 시스템에 대해서 다루고 있다. WASPIFA 시스템은 특정 분야에 국한해서 단편적 정보를 제공하는 기존의 단백질 기능 및 상호작용 분석 시스템과는 달리 분석하고자 하는 서열의 종합적인 정보 즉, 기능정보 및 주석정보, 도메인 정보, 상호작용 관계정보 등을 제공한다. 일반 검색 및 분석 시스템에서 제공하지 못하는 종합적인 정보들은 다양한 전처리 과정을 통해서 얻어진 데이터 및 정보 등을 시스템 내에 로컬 데이터베이스화해 놓은 것이다. 최종 사용자는 종합적인 정보를 통해서 올바른 평가와 판단을 통해서 효과적인 단백질 상호작용 분석과 기능분석을 행할 수 있다. 또한 자동관리 및 데이터 갱신 기능을 갖추고 있어 시스템 관리자가 효율적으로 시스템을 유지 및 관리할 수 있다.

• 한국생물정보학회:학술대회논문집
• /
• 한국생물정보시스템생물학회 2005년도 BIOINFO 2005
• /
• pp.313-318
• /
• 2005

Estimating the reliability of protein-protein interaction data sets obtained by high-throughput technologies such as yeast two-hybrid assays and mass spectrometry is of great importance. We develop a maximum likelihood estimation method that uses both protein localization and gene expression data to estimate the reliability of protein interaction data sets. By integrating protein localization data and gene expression data, we can obtain more accurate estimates of the reliability of various interaction data sets. We apply the method to protein physical interaction data sets and protein complex data sets. The reliability of the yeast two-hybrid interactions by Ito et al. (2001) is 27%, and that by Uetz et at.(2000) is 68%. The reliability of the protein complex data sets using tandem affinity purification-mass spec-trometry (TAP) by Gavin et at. (2002) is 45%, and that using high-throughput mass spectrometric protein complex identification (HMS-PCI) by Ho et al. (2002) is 20%. The method is general and can be applied to analyze any protein interaction data sets.

• 한국콘텐츠학회논문지
• /
• 제9권5호
• /
• pp.332-336
• /
• 2009

유전체 분석에서 중요한 부분 중 하나는 기능이 알려지지 않은 미지 단백질에 대한 기능 예측이다. 단백질-단백질 상호작용 네트워크를 분석하는 것은 미지 단백질에 대한 기능을 보다 쉽게 예측할 수 있게 한다. 단백질-단백질 상호작용 네트워크로부터 미지 단백질의 기능을 예측하기 위한 다양한 연구들이 시도되어 왔다. 카이-제곱(Chi-square) 방식은 단백질-단백질 상호작용 네트워크를 통해 기능을 예측하고자 하는 연구 중 대표적인 방식이다. 하지만 카이-제곱 방식은 네트워크의 토폴로지를 반영하지 않아 네트워크 크기에 따라 예측의 정확성이 떨어지는 문제점이 있다. 따라서 본 논문에서는 카이-제곱 방식을 보완하여 정확성을 높인 새로운 기능 예측 방법을 제안한다 이를 위해 MIPS, DIP 그리고 SGD와 같은 공개된 단백질 상호작용 데이터베이스들로부터 데이터를 수집하여 분석하였다. 그리고 제안된 방식의 우수성을 입증하기 위해 각 데이터베이스들에 대해 카이-제곱방식과 제안하는 보완된 카이-제곱(Modified Chi-square)방식으로 예측해보고 이들의 정확성을 평가하였다.

• Journal of Information Processing Systems
• /
• 제8권3호
• /
• pp.459-470
• /
• 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.

• Journal of Microbiology and Biotechnology
• /
• 제27권3호
• /
• pp.644-647
• /
• 2017

Peptidyl prolyl cis/trans isomerases (PPIases) catalyze the cis/trans isomerization of peptidyl-prolyl peptide bonds preceding prolines. We investigated the protein-protein interaction between a 22 kDa PPIase (VaFKBP22, an FK506-binding protein) and the molecular chaperone DnaK derived from Vibrio anguillarum O1 (VaDnaK) using GST pull-down assays and a bacterial two-hybrid system for in vivo and in vitro studies, respectively. Furthermore, we analyzed the three-dimensional structure of the protein-protein interaction. Based on our results, VaFKBP22 appears to act as a cochaperone of VaDnaK, and contributes to protein folding and stabilization via its peptidyl-prolyl cis/trans isomerization activity.