Dataset Information

SCOWLP classification: structural comparison and analysis of protein binding regions.

ABSTRACT: BACKGROUND: Detailed information about protein interactions is critical for our understanding of the principles governing protein recognition mechanisms. The structures of many proteins have been experimentally determined in complex with different ligands bound either in the same or different binding regions. Thus, the structural interactome requires the development of tools to classify protein binding regions. A proper classification may provide a general view of the regions that a protein uses to bind others and also facilitate a detailed comparative analysis of the interacting information for specific protein binding regions at atomic level. Such classification might be of potential use for deciphering protein interaction networks, understanding protein function, rational engineering and design. DESCRIPTION: Protein binding regions (PBRs) might be ideally described as well-defined separated regions that share no interacting residues one another. However, PBRs are often irregular, discontinuous and can share a wide range of interacting residues among them. The criteria to define an individual binding region can be often arbitrary and may differ from other binding regions within a protein family. Therefore, the rational behind protein interface classification should aim to fulfil the requirements of the analysis to be performed.We extract detailed interaction information of protein domains, peptides and interfacial solvent from the SCOWLP database and we classify the PBRs of each domain family. For this purpose, we define a similarity index based on the overlapping of interacting residues mapped in pair-wise structural alignments. We perform our classification with agglomerative hierarchical clustering using the complete-linkage method. Our classification is calculated at different similarity cut-offs to allow flexibility in the analysis of PBRs, feature especially interesting for those protein families with conflictive binding regions. The hierarchical classification of PBRs is implemented into the SCOWLP database and extends the SCOP classification with three additional family sub-levels: Binding Region, Interface and Contacting Domains. SCOWLP contains 9,334 binding regions distributed within 2,561 families. In 65% of the cases we observe families containing more than one binding region. Besides, 22% of the regions are forming complex with more than one different protein family. CONCLUSION: The current SCOWLP classification and its web application represent a framework for the study of protein interfaces and comparative analysis of protein family binding regions. This comparison can be performed at atomic level and allows the user to study interactome conservation and variability. The new SCOWLP classification may be of great utility for reconstruction of protein complexes, understanding protein networks and ligand design. SCOWLP will be updated with every SCOP release. The web application is available at http://www.scowlp.org.

SUBMITTER: Teyra J

PROVIDER: S-EPMC2259299 | biostudies-literature | 2008

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

SCOWLP classification: structural comparison and analysis of protein binding regions.

Teyra Joan J Paszkowski-Rogacz Maciej M Anders Gerd G Pisabarro M Teresa MT

BMC bioinformatics 20080108

<h4>Background</h4>Detailed information about protein interactions is critical for our understanding of the principles governing protein recognition mechanisms. The structures of many proteins have been experimentally determined in complex with different ligands bound either in the same or different binding regions. Thus, the structural interactome requires the development of tools to classify protein binding regions. A proper classification may provide a general view of the regions that a prote ...[more]

PMID: 18182098

Similar Datasets

Project description:A combination of cDNA sequencing of the complete coding region, protein comparisons, binding site mapping, and electron microscopic imaging has permitted the formulation of a structural model of cytotactin. Cytotactin is a large extracellular matrix glycoprotein that displays a restricted tissue distribution during development. Although there appears to be a single cytotactin gene, multiple cytotactin polypeptides and mRNAs are detected in a variety of tissues. We report here the sequences and relationships of cDNAs that encode the complete amino acid sequences of two cytotactin polypeptides in chicken brain. The translated cDNA sequences agree with those obtained by direct analysis of cytotactin and fragments of the molecule. All regions of the polypeptides appear to be identical except for a 273 amino acid segment found in the larger but not in the smaller. At their amino termini, both polypeptides contain a cysteine-rich segment that probably includes those residues that link monomers into hexamers. This segment is followed by 13 epidermal growth factor-like (EGFL) repeats and then 8 consecutive segments that each resemble the type III repeats found in fibronectin. At their carboxyl termini, the polypeptides are similar to the beta and gamma chains of fibrinogen, including a calcium-binding segment. The additional sequence in the large polypeptide is inserted after the fifth type III repeat and includes three additional type III repeats. On RNA transfer blot analyses, cytotactin cDNA probes detected a 6.4-kilobase (kb) component in both brain and gizzard and larger mRNAs in both tissues, but those in gizzard were larger by about 1 kb than those in brain. A probe specific to the insert did not hybridize to the 6.4-kb mRNA in either tissue but detected the larger mRNAs in both tissues. At least a portion of the insert is thus present in both tissues, but there may be additional inserts in the gizzard mRNAs. The proposed model of cytotactin specifies the orientation of the polypeptides, the localization of interchain disulfide bonds, the structural elements constituting the thin and thick segments (EGFL repeats and type III repeats, respectively), the terminal fibrinogen-like nodular region, and the relative location of the cell-binding region.

Dataset Information

SCOWLP classification: structural comparison and analysis of protein binding regions.

Publications

SCOWLP classification: structural comparison and analysis of protein binding regions.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets