In Silico Prediction of Ligand-Binding Sites of Plant Receptor Kinases Using Conservation Mapping

Plasma membrane-bound plant receptor-like kinases (RLKs) can be categorized based on their ligand-binding extracellular domain. The largest group encompasses RLKs having ectodomains with leucine-rich repeats (LRRs). The LRR-RLKs can further be assigned to classes mainly based on the number of LRRs. Many of the receptors of the classes X and XI with more than 20 LRRs are activated by small secreted peptide ligands. To understand how peptide signaling works, it is of interest to identify the amino acids of the receptor that are directly involved in ligand interaction. Such residues have most likely been conserved over evolutionary time and can therefore be predicted to be conserved in receptor orthologues of different plant species. Here we present an in silico method to identify such residues. This involves a simplified method for identification of orthologues and a web-based program for identifying the most conserved amino acids aside from the leucines that structure the ectodomain. The method has been validated for the LRR-RLKs HAESA (HAE) and PHYTOSULFOKINE RECEPTOR1 (PSKR1) for which conservation-mapping results closely matched recent structure-based identification of ligand and co-receptor-interacting residues.