Protein structure comparison, an important problem in structural biology, has two main applications: (i) comparing two protein structures in order to identify the similarities and differences between them, and (ii) searching for structures similar to a query structure. Many web-based resources for both applications are available, but all are based on rigid structural alignment algorithms. FATCAT server implements the recently developed flexible protein structure comparison algorithm FATCAT, which automatically identifies hinges and internal rearrangements in two protein structures. The server provides access to two algorithms: FATCAT-pairwise for pairwise flexible structure comparison and FATCAT-search for database searching for structurally similar proteins. Given two protein structures [in the Protein Data Bank (PDB) format], FATCAT-pairwise reports their structural alignment and the corresponding statistical significance of the similarity measured as a P-value. Users can view the superposition of the structures online in web browsers that support the Chime plug-in, or download the superimposed structures in PDB format. In FATCAT-search, users provide one query structure and the server returns a list of protein structures that are similar to the query, ordered by the P-values. In addition, FATCAT server can report the conformational changes of the query structure as compared to other proteins in the structure database. FATCAT server is available at

This un-edited manuscript has been accepted for publication in Biophysical Journal and is freely available on BioFAST at www.biophysj.org. The final copyedited version of the paper may be found at www.biophysj.org.

Protein structures are flexible, changing their shapes not only upon substrate binding, but also during evolution as a collective effect of mutations, deletions and insertions. A new generation of protein structure comparison algorithms allows for such flexibility; they go beyond identifying the largest common part between two proteins and find hinge regions and patterns of flexibility in protein families. Here we present a Flexible Structural Neighborhood (FSN), a database of structural neighbors of proteins deposited in PDB as seen by a flexible protein structure alignment program FATCAT, developed previously in our group. The database, searchable by a protein PDB code, provides lists of proteins with statistically significant structural similarity and on lower menu levels provides detailed alignments, interactive superposition of structures and positions of hinges that were identified in the comparison. While superficially similar to other structural protein alignment resources, FSN provides a unique resource to study not only protein structural similarity, but also how protein structures change. FSN is available from a server

Here we describe the use of a structure fragment library for the 1D representation of protein structure. This study focuses on the added value gained from such a description. We show the new local structure language adds resolution to the traditional three state (helix, strand and coil) secondary structure description, and provides a high degree of accuracy in recognizing structural similarities when used with a pair wise alignment benchmark. The results of this study have immediate applications towards fast structure recognition, and for fold prediction and classification. Background The computational representation of a protein's 3D structure is a challenging problem because of varying and often conflicting considerations. A representation is goal driven: it is clear that the representation needed for quick over-the-web wire frame backbone display is not the same required for a detailed analysis of a protein-ligand interaction that may include detailed simulations of chemical processes. With the recent explosion of solved protein structures, there is a growing need for a simpler representation of protein structure. This representation should accommodate the high throughput computational functions required by the growing size of protein structure databases, but without undue sacrifice of accuracy. Large structure database scanning is very expensive [1, 2] and fast pre-filtering for negatives can reduce search time

Insertions and the emergence of novel protein structure: a

Abstract not found

We have developed a feedback algorithm for protein structure alignment between two protein backbones. A web portal implementing this method has been constructed and is freely available for use at