SpaK/SpaR Two-component System Characterized by a Structure-driven Domain-fusion Method and in Vitro Phosphorylation Studies
| Autor: | Carol L. Ecale Zhou, J. Norman Hansen, Adam Zemla, Anu Chakicherla, Martha Ligon Dang, Virginia Rodriguez |
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| Rok vydání: | 2009 |
| Předmět: |
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Molecular Protein Conformation Recombinant Fusion Proteins Computational Biology/Macromolecular Structure Analysis Sequence alignment Computational biology Protein Serine-Threonine Kinases Biology Cell Biology/Cell Signaling Protein–protein interaction 03 medical and health sciences Cellular and Molecular Neuroscience Protein structure Bacterial Proteins Protein Interaction Mapping Escherichia coli Genetics Protein Interaction Domains and Motifs Homology modeling Phosphorylation Spar lcsh:QH301-705.5 Molecular Biology Ecology Evolution Behavior and Systematics 030304 developmental biology 0303 health sciences Ecology 030306 microbiology Histidine kinase Computational Biology Reproducibility of Results Genetics and Genomics/Bioinformatics Two-component regulatory system DNA-Binding Proteins Response regulator lcsh:Biology (General) Models Chemical Biochemistry/Bioinformatics Biochemistry/Macromolecular Assemblies and Machines Computational Theory and Mathematics Biochemistry Structural Homology Protein Modeling and Simulation Bacillus subtilis Transcription Factors Research Article |
| Zdroj: | PLoS Computational Biology PLoS Computational Biology, Vol 5, Iss 6, p e1000401 (2009) |
| ISSN: | 1553-7358 |
| DOI: | 10.1371/journal.pcbi.1000401 |
| Popis: | Here we introduce a quantitative structure-driven computational domain-fusion method, which we used to predict the structures of proteins believed to be involved in regulation of the subtilin pathway in Bacillus subtilis, and used to predict a protein-protein complex formed by interaction between the proteins. Homology modeling of SpaK and SpaR yielded preliminary structural models based on a best template for SpaK comprising a dimer of a histidine kinase, and for SpaR a response regulator protein. Our LGA code was used to identify multi-domain proteins with structure homology to both modeled structures, yielding a set of domain-fusion templates then used to model a hypothetical SpaK/SpaR complex. The models were used to identify putative functional residues and residues at the protein-protein interface, and bioinformatics was used to compare functionally and structurally relevant residues in corresponding positions among proteins with structural homology to the templates. Models of the complex were evaluated in light of known properties of the functional residues within two-component systems involving His-Asp phosphorelays. Based on this analysis, a phosphotransferase complexed with a beryllofluoride was selected as the optimal template for modeling a SpaK/SpaR complex conformation. In vitro phosphorylation studies performed using wild type and site-directed SpaK mutant proteins validated the predictions derived from application of the structure-driven domain-fusion method: SpaK was phosphorylated in the presence of 32P-ATP and the phosphate moiety was subsequently transferred to SpaR, supporting the hypothesis that SpaK and SpaR function as sensor and response regulator, respectively, in a two-component signal transduction system, and furthermore suggesting that the structure-driven domain-fusion approach correctly predicted a physical interaction between SpaK and SpaR. Our domain-fusion algorithm leverages quantitative structure information and provides a tool for generation of hypotheses regarding protein function, which can then be tested using empirical methods. Author Summary Because proteins so frequently function in coordination with other proteins, identification and characterization of the interactions among proteins are essential for understanding how proteins work. Computational methods for identification of protein-protein interactions have been limited by the degree to which proteins are similar in sequence. However, methods that leverage structure information can overcome this limitation of sequence-based methods; the three-dimensional information provided by structure enables identification of related proteins even when their sequences are dissimilar. In this work we present a quantitative method for identification of protein interacting partners, and we demonstrate its use in modeling the structure of a hypothetical complex between two proteins that function in a bacterial signaling system. This quantitative approach comprises a tool for generation of hypotheses regarding protein function, which can then be tested using empirical methods, and provides a basis for high-throughput prediction of protein-protein interactions, which could be applied on a whole-genome scale. |
| Databáze: | OpenAIRE |
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