Dataset Information

The FSSP database: fold classification based on structure-structure alignment of proteins.

ABSTRACT: The FSSP database presents a continuously updated classification of 3-D protein folds based on an all-against-all comparison of structures currently in the Protein Data Bank (PDB) [Bernstein et al. (1977) J. Mol. Biol., 112, 535- 542]. The database currently contains an extended structural family for each of 600 representative protein chains which have <25% mutual sequence identity. The results of the exhaustive pairwise structure comparisons are reported in the form of a fold tree generated by hierarchical clustering and as a series of structurally representative sets of folds at varying levels of uniqueness. For each query structure from the representative set, there is a database entry containing structure-structure alignments with its structural neighbours in the representative set and its sequence homologs in the PDB. All alignments are based purely on the 3-D co-ordinates of the proteins and are derived by an automatic structure comparison program (Dali). The FSSP database is accessible electronically on the World Wide Web and by anonymous ftp.

SUBMITTER: Holm L

PROVIDER: S-EPMC145583 | biostudies-other | 1996 Jan

REPOSITORIES: biostudies-other

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The FSSP database: fold classification based on structure-structure alignment of proteins.

Holm L L Sander C C

Nucleic acids research 19960101 1

The FSSP database presents a continuously updated classification of 3-D protein folds based on an all-against-all comparison of structures currently in the Protein Data Bank (PDB) [Bernstein et al. (1977) J. Mol. Biol., 112, 535- 542]. The database currently contains an extended structural family for each of 600 representative protein chains which have <25% mutual sequence identity. The results of the exhaustive pairwise structure comparisons are reported in the form of a fold tree generated by ...[more]

PMID: 8594580

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Project description:BackgroundIt has been proposed that secondary structure information can be used to classify (to some extend) protein folds. Since this method utilizes very limited information about the protein structure, it is not surprising that it has a higher error rate than the approaches that use full 3D fold description. On the other hand, the comparing of 3D protein structures is computing intensive. This raises the question to what extend the error rate can be decreased with each new source of information, especially if the new information can still be used with simple alignment algorithms. We consider the question whether the information about closed loops can improve the accuracy of this approach. While the answer appears to be obvious, we had to overcome two challenges. First, how to code and to compare topological information in such a way that local alignment of strings will properly identify similar structures. Second, how to properly measure the effect of new information in a large data sample. We investigate alternative ways of computing and presenting this information.ResultsWe used the set of beta proteins with at most 30% pairwise identity to test the approach; local alignment scores were used to build a tree of clusters which was evaluated using a new log-odd cluster scoring function. In particular, we derive a closed formula for the probability of obtaining a given score by chance. Parameters of local alignment function were optimized using a genetic algorithm. Of 81 folds that had more than one representative in our data set, log-odds scores registered significantly better clustering in 27 cases and significantly worse in 6 cases, and small differences in the remaining cases. Various notions of the significant change or average change were considered and tried, and the results were all pointing in the same direction.ConclusionWe found that, on average, properly presented information about the loop topology improves noticeably the accuracy of the method but the benefits vary between fold families as measured by log-odds cluster score.

Dataset Information

The FSSP database: fold classification based on structure-structure alignment of proteins.

Publications

The FSSP database: fold classification based on structure-structure alignment of proteins.

Similar Datasets

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