firestar WS

Firestar WS predicts catalytic and ligand-binding residues in protein sequences using structural templates and alignment-based evidence to identify functionally important residues.

Key Features:

• Automated workflow: Provides automated prediction of functional residues from sequence-to-template alignments to support batch analyses.
• Enhanced prediction coverage: Expanded FireDB coupled with incorporations of alignments generated using HHsearch increases template and ligand coverage for residue prediction.
• Ligand biological-relevance classification: FireDB ligands are classified by biological relevance to provide context for predicted binding sites.
• High-throughput capability: Supports processing of large protein datasets for large-scale functional-residue annotation.
• Alignment reliability integration: Leverages alignment reliability metrics alongside structural templates to inform residue-level predictions.

Scientific Applications:

• Structural biology: Identification of catalytic and ligand-binding residues to annotate protein function from structural and sequence evidence.
• Drug discovery: Prediction of potential ligand-binding sites that can guide identification of therapeutic molecule targets.
• Enzyme mechanism research: Pinpointing residues critical for catalysis to support studies of enzyme function and mechanism.

Methodology:

Alignments between target sequences and FireDB templates are generated using HHsearch and PSI-BLAST, and profile generation uses a local 70% non-redundant database to support prediction of functional residues.