Local feature frequency profile: A method to measure structural similarity in proteins

In Geol Choi, Jaimyoung Kwon, Sung Hou Kim

Research output: Contribution to journalArticlepeer-review

70 Citations (Scopus)


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 Cα 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 Cα 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.

Original languageEnglish
Pages (from-to)3797-3802
Number of pages6
JournalProceedings of the National Academy of Sciences of the United States of America
Issue number11
Publication statusPublished - 2004 Mar 16
Externally publishedYes


  • Local protein structural features profile
  • Protein distance matrix
  • Protein fold
  • Protein fold space
  • Protein structural similarity

ASJC Scopus subject areas

  • General


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