prrdb2

prrdb2 provides a comprehensive repository of pattern recognition receptors (PRRs) and their pathogen-associated molecular pattern (PAMP) ligands, aggregating sequences, annotations, experimental PDB structures and predicted models to support research on innate immune recognition.

Key Features:

• Database content: Approximately 2,700 total entries encompassing PRRs and PAMPs.
• PRR count: Curated entries include 467 unique pattern recognition receptors (PRRs).
• PAMP count: Curated entries include 827 pathogen-associated molecular patterns (PAMPs).
• Curation sources: Data were manually extracted from around 600 research articles and public databases.
• Entry annotations: Each entry contains name, sequence, origin, source, type and related annotation details.
• Cross-references: Entries include links to external resources such as Swiss-Prot and PubChem.
• Experimental structures: Integration of approximately 4,500 experimentally determined structures from the Protein Data Bank (PDB).
• Predicted structures: Predicted structural models provided for 110 PRRs lacking experimental structures.
• Similarity search algorithms: Sequence similarity searches implemented using BLAST and Smith-Waterman.
• Data browsing and categorization: Data are organized for filtering and retrieval by receptor, ligand and source.

Scientific Applications:

• Innate immunity research: Resource for studying interactions between PRRs and PAMP ligands in innate immune recognition.
• Structure–function analysis: Use of PDB structures and predicted models to analyze structural aspects of PRRs and complexes.
• Comparative sequence analysis: Identification of homologs and sequence relationships via BLAST and Smith-Waterman similarity searches.
• Ligand–receptor mapping: Annotation and cross-referencing to Swiss-Prot and PubChem to link ligand chemistry and receptor biology.

Methodology:

Manual extraction and curation from ~600 research articles and public databases; mapping entries to Swiss-Prot and PubChem; integration of ~4,500 PDB structures; prediction of structures for 110 PRRs; and implementation of sequence similarity searches using BLAST and Smith-Waterman.