ELMInstanceMapper

ELMInstanceMapper maps predicted Eukaryotic Linear Motifs (ELMs) from query protein sequences onto annotated ELM instances to identify short linear peptide motifs in eukaryotic proteomes and support motif-level functional inference.

Key Features:

• Focus on Short Linear Motifs: Targets short linear peptide motifs in multidomain proteins relevant for cell compartment targeting, protein-protein interactions, and post-translational modifications such as phosphorylation, acetylation, and glycosylation.
• Logical Filtering System: Applies filters for cell compartment specificity, avoidance of globular domain clashes, and taxonomic range to reduce false positives, often by an order of magnitude.
• Sequence Comparison Algorithms: Compares query sequences against a database of annotated ELM instances using advanced sequence-comparison algorithms.
• Integration with the ELM Server: Leverages the Eukaryotic Linear Motif (ELM) server/database as the source of annotated motif instances.

Scientific Applications:

• Protein Function Analysis: Maps motif instances onto proteins to infer functional roles of specific motifs within multidomain proteins.
• Post-translational Modification Studies: Identifies potential sites for phosphorylation, acetylation, and glycosylation to inform studies of protein regulation.
• Protein-Protein Interaction Research: Highlights motifs involved in interactions to support analyses of cellular signaling pathways and interaction networks.

Methodology:

Leverages the Eukaryotic Linear Motif (ELM) server; performs sequence comparison using advanced algorithms to match query sequences against a database of annotated ELM instances; applies logical filters for cell compartment specificity, domain clash avoidance, and taxonomic range to refine results.