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CX, DPX and PRIDE: WWW servers for the analysis and comparison of protein 3D structures.

ABSTRACT: The WWW servers at http://www.icgeb.org/protein/ are dedicated to the analysis of protein 3D structures submitted by the users as the Protein Data Bank (PDB) files. CX computes an atomic protrusion index that makes it possible to highlight the protruding atoms within a protein 3D structure. DPX calculates a depth index for the buried atoms and makes it possible to analyze the distribution of buried residues. CX and DPX return PDB files containing the calculated indices that can then be visualized using standard programs, such as Swiss-PDBviewer and Rasmol. PRIDE compares 3D structures using a fast algorithm based on the distribution of inter-atomic distances. The options include pairwise as well as multiple comparisons, and fold recognition based on searching the CATH fold database.

SUBMITTER: Vlahovicek K

PROVIDER: S-EPMC1160123 | biostudies-literature | 2005 Jul

REPOSITORIES: biostudies-literature

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CX, DPX and PRIDE: WWW servers for the analysis and comparison of protein 3D structures.

Vlahovicek Kristian K Pintar Alessandro A Parthasarathi Laavanya L Carugo Oliviero O Pongor Sándor S

Nucleic acids research 20050701 Web Server issue

The WWW servers at http://www.icgeb.org/protein/ are dedicated to the analysis of protein 3D structures submitted by the users as the Protein Data Bank (PDB) files. CX computes an atomic protrusion index that makes it possible to highlight the protruding atoms within a protein 3D structure. DPX calculates a depth index for the buried atoms and makes it possible to analyze the distribution of buried residues. CX and DPX return PDB files containing the calculated indices that can then be visualize ...[more]

PMID: 15980464

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Project description:Comparing and classifying the three-dimensional (3D) structures of proteins is of crucial importance to molecular biology, from helping to determine the function of a protein to determining its evolutionary relationships. Traditionally, 3D structures are classified into groups of families that closely resemble the grouping according to their primary sequence. However, significant structural similarities exist at multiple levels between proteins that belong to these different structural families. In this study, we propose a new algorithm, CLICK, to capture such similarities. The method optimally superimposes a pair of protein structures independent of topology. Amino acid residues are represented by the Cartesian coordinates of a representative point (usually the C(α) atom), side chain solvent accessibility, and secondary structure. Structural comparison is effected by matching cliques of points. CLICK was extensively benchmarked for alignment accuracy on four different sets: (i) 9537 pair-wise alignments between two structures with the same topology; (ii) 64 alignments from set (i) that were considered to constitute difficult alignment cases; (iii) 199 pair-wise alignments between proteins with similar structure but different topology; and (iv) 1275 pair-wise alignments of RNA structures. The accuracy of CLICK alignments was measured by the average structure overlap score and compared with other alignment methods, including HOMSTRAD, MUSTANG, Geometric Hashing, SALIGN, DALI, GANGSTA(+), FATCAT, ARTS and SARA. On average, CLICK produces pair-wise alignments that are either comparable or statistically significantly more accurate than all of these other methods. We have used CLICK to uncover relationships between (previously) unrelated proteins. These new biological insights include: (i) detecting hinge regions in proteins where domain or sub-domains show flexibility; (ii) discovering similar small molecule binding sites from proteins of different folds and (iii) discovering topological variants of known structural/sequence motifs. Our method can generally be applied to compare any pair of molecular structures represented in Cartesian coordinates as exemplified by the RNA structure superimposition benchmark.

Project description:BackgroundProtein surfaces serve as an interface with the molecular environment and are thus tightly bound to protein function. On the surface, geometric and chemical complementarity to other molecules provides interaction specificity for ligand binding, docking of bio-macromolecules, and enzymatic catalysis.As of today, there is no accepted general scheme to represent protein surfaces. Furthermore, most of the research on protein surface focuses on regions of specific interest such as interaction, ligand binding, and docking sites. We present a first step toward a general purpose representation of protein surfaces: a novel surface patch library that represents most surface patches (~98%) in a data set regardless of their functional roles.ResultsSurface patches, in this work, are small fractions of the protein surface. Using a measure of inter-patch distance, we clustered patches extracted from a data set of high quality, non-redundant, proteins. The surface patch library is the collection of all the cluster centroids; thus, each of the data set patches is close to one of the elements in the library.We demonstrate the biological significance of our method through the ability of the library to capture surface characteristics of native protein structures as opposed to those of decoy sets generated by state-of-the-art protein structure prediction methods. The patches of the decoys are significantly less compatible with the library than their corresponding native structures, allowing us to reliably distinguish native models from models generated by servers. This trend, however, does not extend to the decoys themselves, as their similarity to the native structures does not correlate with compatibility with the library.ConclusionsWe expect that this high-quality, generic surface patch library will add a new perspective to the description of protein structures and improve our ability to predict them. In particular, we expect that it will help improve the prediction of surface features that are apparently neglected by current techniques.The surface patch libraries are publicly available at http://www.cs.bgu.ac.il/~keasar/patchLibrary.

Dataset Information

CX, DPX and PRIDE: WWW servers for the analysis and comparison of protein 3D structures.

Publications

CX, DPX and PRIDE: WWW servers for the analysis and comparison of protein 3D structures.

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