https://scholars.lib.ntu.edu.tw/handle/123456789/593650
標題: | Clustering and visualizing similarity networks of membrane proteins | 作者: | Geng-Ming Hu TE-LUN MAI Chi-Ming Chen |
關鍵字: | membrane proteins; network clustering; protein function; protein similarity networks; protein structure; sequence homology | 公開日期: | 2015 | 出版社: | Wiley | 卷: | 83 | 期: | 8 | 起(迄)頁: | 1450-1461 | 來源出版物: | Proteins: Structure, Function, and Bioinformatics | 摘要: | We proposed a fast and unsupervised clustering method, minimum span clustering (MSC), for analyzing the sequence-structure-function relationship of biological networks, and demonstrated its validity in clustering the sequence/structure similarity networks (SSN) of 682 membrane protein (MP) chains. The MSC clustering of MPs based on their sequence information was found to be consistent with their tertiary structures and functions. For the largest seven clusters predicted by MSC, the consistency in chain function within the same cluster is found to be 100%. From analyzing the edge distribution of SSN for MPs, we found a characteristic threshold distance for the boundary between clusters, over which SSN of MPs could be properly clustered by an unsupervised sparsification of the network distance matrix. The clustering results of MPs from both MSC and the unsupervised sparsification methods are consistent with each other, and have high intracluster similarity and low intercluster similarity in sequence, structure, and function. Our study showed a strong sequence-structure-function relationship of MPs. We discussed evidence of convergent evolution of MPs and suggested applications in finding structural similarities and predicting biological functions of MP chains based on their sequence information. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/593650 | ISSN: | 0887-3585 | DOI: | 10.1002/prot.24832 |
顯示於: | 生命科學系 |
在 IR 系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。