期刊名称：Proceedings of the National Academy of Sciences
印刷版ISSN：0027-8424
电子版ISSN：1091-6490
出版年度：2004
卷号：101
期号：11
页码：3797-3802
DOI：10.1073/pnas.0308656100
语种：English
出版社：The National Academy of Sciences of the United States of America
摘要：Measures of structural similarity between known protein structures provide an objective basis for classifying protein folds and for revealing a global view of the protein structure universe. Here, we describe a rapid method to measure structural similarity based on the profiles of representative local features of C{alpha} distance matrices of compared protein structures. We first extract a finite number of representative local feature (LF) patterns from the distance matrices of all protein fold families by medoid analysis. Then, each C{alpha} distance matrix of a protein structure is encoded by labeling all its submatrices by the index of the nearest representative LF patterns. Finally, the structure is represented by the frequency distribution of these indices, which we call the LF frequency (LFF) profile of the protein. The LFF profile allows one to calculate structural similarity scores among a large number of protein structures quickly, and also to construct and update the "map" of the protein structure universe easily. The LFF profile method efficiently maps complex protein structures into a common Euclidean space without prior assignment of secondary structure information or structural alignment.
关键词：protein structural similarity ; protein distance matrix ; local protein structural features profile ; protein fold ; protein fold space
