eBAS

eBAS identifies and classifies conserved protein sequence motifs (eMOTIFs) to enable motif-based analysis, functional annotation, and evolutionary comparison of proteomes.

Key Features:

• High sensitivity and specificity: The EMOTIF database comprises over 170,000 curated eMOTIFs that represent highly specific and sensitive protein sequence motifs for detecting biochemical properties.
• Comprehensive motif collection: Motifs were derived from more than 15,941 sequence alignments sourced from BLOCKS+ (as of June 23, 2000) and PRINTS (version 27.0).
• Advanced search algorithms: Search algorithms use eMOTIF patterns to perform sensitive motif-based searches that detect divergent sequences sharing functional characteristics beyond global sequence similarity.
• Batch processing capability: The system performs batch analyses across large datasets, enabling motif scanning of multiple proteins or entire proteomes.

Scientific Applications:

• Protein function prediction: Identification of conserved eMOTIFs supports inference of biochemical functions for uncharacterized proteins.
• Evolutionary studies: Detection of conserved positions across divergent sequences facilitates studies of evolutionary conservation and functional divergence.
• Functional annotation: Annotation of protein sequences with matched eMOTIFs assists assignment of biochemical properties and domain-level functions.

Methodology:

The emotif-maker algorithm (Nevill-Manning et al.) derives conserved sequence motifs from protein sequence alignments; motifs are cataloged into the EMOTIF database and the tool's search algorithms use those eMOTIF patterns to perform sensitive motif-based searches across large datasets.