structural similarity and classification of protein interaction interfaces蛋白质交互接口的结构相似性和分类.pdfVIP

Structural Similarity and Classification of Protein Interaction Interfaces 1 1 1 1,2 Nan Zhao , Bin Pang , Chi-Ren Shyu , Dmitry Korkin * 1 Informatics Institute and Department of Computer Science, University of Missouri, Columbia, Missouri, United States of America, 2 Bond Life Science Center, University of Missouri, Columbia, Missouri, United States of America Abstract Interactions between proteins play a key role in many cellular processes. Studying protein-protein interactions that share similar interaction interfaces may shed light on their evolution and could be helpful in elucidating the mechanisms behind stability and dynamics of the protein complexes. When two complexes share structurally similar subunits, the similarity of the interaction interfaces can be found through a structural superposition of the subunits. However, an accurate detection of similarity between the protein complexes containing subunits of unrelated structure remains an open problem. Here, we present an alignment-free machine learning approach to measure interface similarity. The approach relies on the feature-based representation of protein interfaces and does not depend on the superposition of the interacting subunit pairs. Specifically, we develop an SVM classifier of similar and dissimilar interfaces and derive a feature-based interface similarity measure. Next, the similarity measure is applied to a set of 2,806 62,806 binary complex pairs to build a hierarchical classification of protein-protein interactions. Finally, we explore case studies of similar interfaces from each level of the hierarchy, considering cases when the subunits forming interactions are either homologous or structurally unrelated. The analysis has suggested that the positions of cha