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Detalle de: Integration of evolutionary and desolvation energy analysis identifies functional sites in a plant immunity protein

Title Integration of evolutionary and desolvation energy analysis identifies functional sites in a plant immunity protein
Abstract

Plant immune responses often depend on leucine-rich repeat receptors that recognize microbe-associated molecular patterns or pathogen-specific virulence proteins, either directly or indirectly. When the recognition is direct, a molecular arms race takes place where plant receptors continually and rapidly evolve in response to virulence factor evolution. A useful model system to study ligand-receptor coevolution dynamics at the protein level is represented by the interaction between pathogen-derived polygalacturonases (PGs) and plant polygalacturonase-inhibiting proteins (PGIPs). We have applied codon substitution models to PGIP sequences of different eudicotyledonous families to identify putative positively selected sites and then compared these sites with the propensity of protein surface residues to interact with protein partners, based on desolvation energy calculations. The 2 approaches remarkably correlated in pinpointing several residues in the concave face of the leucine-rich repeat domain. These residues were mutated into alanine and their effect on the recognition of several PGs was tested, leading to the identification of unique hotspots for the PGIP-PG interaction. The combined approach used in this work can be of general utility in cases where structural information about a pattern-recognition receptor or resistance-gene product is available.

Apa Reference Casasoli, M., Federici, L., Spinelli, F., Di Matteo, A., Vella, N., Scaloni, F., Fernandez-Recio, J., Cervone, F., & De Lorenzo, G. (2009). Integration of evolutionary and desolvation energy analysis identifies functional sites in a plant immunity protein. Proceedings of the National Academy of Sciences, 106(18), 7666–7671. 10.1073/pnas.0812625106
Doi 10.1073/pnas.0812625106
Publication Date 5 May 2009
Publication Type Article
Researcher Juan Fernández Recio
Ontology Molecular evolution, Molecular Interactions/Docking
Research Groups Structural Bioinformatics, Modeling and Biological Mechanisms
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