LRRpredictor—a new LRR motif detection method for irregular motifs of plant NLR proteins using an ensemble of classifiers

Eliza C. Martin, Octavina C.A. Sukarta, Laurentiu Spiridon, Laurentiu G. Grigore, Vlad Constantinescu, Robi Tacutu, Aska Goverse*, Andrei Jose Petrescu*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

13 Citations (Scopus)

Abstract

Leucine-rich-repeats (LRRs) belong to an archaic procaryal protein architecture that is widely involved in protein–protein interactions. In eukaryotes, LRR domains developed into key recognition modules in many innate immune receptor classes. Due to the high sequence variability imposed by recognition specificity, precise repeat delineation is often difficult especially in plant NOD-like Receptors (NLRs) notorious for showing far larger irregularities. To address this problem, we introduce here LRRpredictor, a method based on an ensemble of estimators designed to better identify LRR motifs in general but particularly adapted for handling more irregular LRR environments, thus allowing to compensate for the scarcity of structural data on NLR proteins. The extrapolation capacity tested on a set of annotated LRR domains from six immune receptor classes shows the ability of LRRpredictor to recover all previously defined specific motif consensuses and to extend the LRR motif coverage over annotated LRR domains. This analysis confirms the increased variability of LRR motifs in plant and vertebrate NLRs when compared to extracellular receptors, consistent with previous studies. Hence, LRRpredictor is able to provide novel insights into the diversification of LRR domains and a robust support for structure-informed analyses of LRRs in immune receptor functioning.

Original languageEnglish
Article number286
JournalGenes
Volume11
Issue number3
DOIs
Publication statusPublished - 8 Mar 2020

Keywords

  • Leucine-rich repeat prediction
  • LRR motif
  • LRR structure
  • NOD-like receptors
  • R proteins
  • Supervised learning

Fingerprint

Dive into the research topics of 'LRRpredictor—a new LRR motif detection method for irregular motifs of plant NLR proteins using an ensemble of classifiers'. Together they form a unique fingerprint.

Cite this