Dataset Information

The streptococcal binding site in the gelatin-binding domain of fibronectin is consistent with a non-linear arrangement of modules.

ABSTRACT: Fibronectin-binding proteins (FnBPs) of Staphylococcus aureus and Streptococcus pyogenes mediate invasion of human endothelial and epithelial cells in a process likely to aid the persistence and/or dissemination of infection. In addition to binding sites for the N-terminal domain (NTD) of fibronectin (Fn), a number of streptococcal FnBPs also contain an upstream region (UR) that is closely associated with an NTD-binding region; UR binds to the adjacent gelatin-binding domain (GBD) of Fn. Previously, UR was shown to be required for efficient streptococcal invasion of epithelial cells. Here we show, using a Streptococcus zooepidemicus FnBP, that the UR-binding site in GBD resides largely in the (8)F1(9)F1 module pair. We also show that UR inhibits binding of a peptide from the ?1 chain of type I collagen to (8)F1(9)F1 and that UR binding to (8)F1 is likely to occur through anti-parallel ?-zipper formation. Thus, we propose that streptococcal proteins that contain adjacent NTD- and GBD-binding sites form a highly unusual extended tandem ?-zipper that spans the two domains and mediates high affinity binding to Fn through a large intermolecular interface. The proximity of the UR- and NTD-binding sequences in streptococcal FnBPs is consistent with a non-linear arrangement of modules in the tertiary structure of the GBD of Fn.

SUBMITTER: Atkin KE

PROVIDER: S-EPMC2978626 | biostudies-literature | 2010 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The streptococcal binding site in the gelatin-binding domain of fibronectin is consistent with a non-linear arrangement of modules.

Atkin Kate E KE Brentnall Andrew S AS Harris Gemma G Bingham Richard J RJ Erat Michele C MC Millard Christopher J CJ Schwarz-Linek Ulrich U Staunton David D Vakonakis Ioannis I Campbell Iain D ID Potts Jennifer R JR

The Journal of biological chemistry 20100915 47

Fibronectin-binding proteins (FnBPs) of Staphylococcus aureus and Streptococcus pyogenes mediate invasion of human endothelial and epithelial cells in a process likely to aid the persistence and/or dissemination of infection. In addition to binding sites for the N-terminal domain (NTD) of fibronectin (Fn), a number of streptococcal FnBPs also contain an upstream region (UR) that is closely associated with an NTD-binding region; UR binds to the adjacent gelatin-binding domain (GBD) of Fn. Previou ...[more]

PMID: 20843804

Similar Datasets

Project description:BackgroundHow transcription factors (TFs) interact with cis-regulatory sequences and interact with each other is a fundamental, but not well understood, aspect of gene regulation.Methodology/principal findingsWe present a computational method to address this question, relying on the established biophysical principles. This method, STAP (sequence to affinity prediction), takes into account all combinations and configurations of strong and weak binding sites to analyze large scale transcription factor (TF)-DNA binding data to discover cooperative interactions among TFs, infer sequence rules of interaction and predict TF target genes in new conditions with no TF-DNA binding data. The distinctions between STAP and other statistical approaches for analyzing cis-regulatory sequences include the utility of physical principles and the treatment of the DNA binding data as quantitative representation of binding strengths. Applying this method to the ChIP-seq data of 12 TFs in mouse embryonic stem (ES) cells, we found that the strength of TF-DNA binding could be significantly modulated by cooperative interactions among TFs with adjacent binding sites. However, further analysis on five putatively interacting TF pairs suggests that such interactions may be relatively insensitive to the distance and orientation of binding sites. Testing a set of putative Nanog motifs, STAP showed that a novel Nanog motif could better explain the ChIP-seq data than previously published ones. We then experimentally tested and verified the new Nanog motif. A series of comparisons showed that STAP has more predictive power than several state-of-the-art methods for cis-regulatory sequence analysis. We took advantage of this power to study the evolution of TF-target relationship in Drosophila. By learning the TF-DNA interaction models from the ChIP-chip data of D. melanogaster (Mel) and applying them to the genome of D. pseudoobscura (Pse), we found that only about half of the sequences strongly bound by TFs in Mel have high binding affinities in Pse. We show that prediction of functional TF targets from ChIP-chip data can be improved by using the conservation of STAP predicted affinities as an additional filter.Conclusions/significanceSTAP is an effective method to analyze binding site arrangements, TF cooperativity, and TF target genes from genome-wide TF-DNA binding data.

Project description:BACKGROUND: Accurate small molecule binding site information for a protein can facilitate studies in drug docking, drug discovery and function prediction, but small molecule binding site protein sequence annotation is sparse. The Small Molecule Interaction Database (SMID), a database of protein domain-small molecule interactions, was created using structural data from the Protein Data Bank (PDB). More importantly it provides a means to predict small molecule binding sites on proteins with a known or unknown structure and unlike prior approaches, removes large numbers of false positive hits arising from transitive alignment errors, non-biologically significant small molecules and crystallographic conditions that overpredict ion binding sites. DESCRIPTION: Using a set of co-crystallized protein-small molecule structures as a starting point, SMID interactions were generated by identifying protein domains that bind to small molecules, using NCBI's Reverse Position Specific BLAST (RPS-BLAST) algorithm. SMID records are available for viewing at http://smid.blueprint.org. The SMID-BLAST tool provides accurate transitive annotation of small-molecule binding sites for proteins not found in the PDB. Given a protein sequence, SMID-BLAST identifies domains using RPS-BLAST and then lists potential small molecule ligands based on SMID records, as well as their aligned binding sites. A heuristic ligand score is calculated based on E-value, ligand residue identity and domain entropy to assign a level of confidence to hits found. SMID-BLAST predictions were validated against a set of 793 experimental small molecule interactions from the PDB, of which 472 (60%) of predicted interactions identically matched the experimental small molecule and of these, 344 had greater than 80% of the binding site residues correctly identified. Further, we estimate that 45% of predictions which were not observed in the PDB validation set may be true positives. CONCLUSION: By focusing on protein domain-small molecule interactions, SMID is able to cluster similar interactions and detect subtle binding patterns that would not otherwise be obvious. Using SMID-BLAST, small molecule targets can be predicted for any protein sequence, with the only limitation being that the small molecule must exist in the PDB. Validation results and specific examples within illustrate that SMID-BLAST has a high degree of accuracy in terms of predicting both the small molecule ligand and binding site residue positions for a query protein.

Dataset Information

The streptococcal binding site in the gelatin-binding domain of fibronectin is consistent with a non-linear arrangement of modules.

Publications

The streptococcal binding site in the gelatin-binding domain of fibronectin is consistent with a non-linear arrangement of modules.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure