LRRsearch

LRRsearch predicts leucine-rich repeat (LRR) motifs in nucleotide-binding oligomerization domain-like receptors (NLRs) to support analysis of ligand-receptor interactions and innate immune recognition.

Key Features:

• Position-Specific Scoring Matrix (PSSM): Uses a PSSM tailored to the 11-residue leucine-rich repeat highly conserved segment (LRR-HCS) for motif detection.
• Error Minimization: Reports prediction error rates minimized to ≤5%, reducing false negatives and false positives in LRR identification.
• Comprehensive Data Library: Integrates a reference library of 421 proteins distributed among five known NLR families for comparative analysis and validation.

Scientific Applications:

• Innate immunity research: Enables identification of LRR motifs involved in pathogen-associated molecular pattern (PAMP) recognition and downstream signaling in NLRs.
• Ligand–receptor interaction studies: Supports analysis of LRR regions that contribute to ligand binding and receptor specificity in NLRs.
• Computational biology and comparative analysis: Facilitates motif identification and comparative studies of LRR-containing proteins across protein families in immunology, molecular biology, and bioinformatics.

Methodology:

Applies a position-specific scoring matrix (PSSM) focused on the highly conserved 11-residue LRR segment (LRR-HCS) to predict LRR motifs, addressing biases of traditional sequence-comparison or alignment methods.