Protein-Protein Interaction Prediction with Identification of Putative Interaction Patterns
Date Issued
2007
Date
2007
Author(s)
Tsai, Meng-Jia
DOI
en-US
Abstract
Protein-protein interaction and interaction site information are key points to realize biological processes. Experimental approaches for detecting protein-protein interactions are far behind the tremendous number of possible interactions. Computational approaches for predicting protein-protein interactions are able to have reasonable accuracies but are usually not able to identify interaction sites. Currently, many methods based on three-dimensional (3D) structures are capable of elucidating interaction interfaces. However, the 3D structure-based methods are computationally intensive and rely on the structures of proteins which may not be readily available. Features and patterns from primary structure can be applied to predict interactions, even potential interaction sites. Therefore, we propose an Apriori-like algorithm to identify possibly interaction-related pairs of short peptides from protein sequence and known interactions. Subsequently, the discovered pairs are able to predict interactions and to infer interaction sites. We concentrate on tri-gram interaction- related and non-interaction-related peptide pairs in the different species, and obtain acceptable performance for high-throughput and high-confidence predictions, with accuracies of ~65% and ~85%, respectively. Moreover, in the 207 hetero-sequenced pairs of chains with 3D structures, some discovered pairs are highlighted in their respective 3D structures. The results presented suggest that these pairs are correlated to binding sites and reasonable for interaction prediction.
Subjects
預測蛋白質交互作用
預測蛋白質交互作用位置
Apriori演算法
序列基礎的預測
Protein-protein interaction prediction
Protein-protein interaction site prediction
Apriori-like algorithm
Sequence-based prediction method
High-confidence prediction system
Type
thesis
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