SLiMAn

SLiMAn analyzes short linear motifs (SLiMs) and their recognition domains to identify and characterize SLiM-mediated protein interactions within interactomes.

Key Features:

• Database integration: Uses ELM for SLiM annotation and Pfam for recognition-domain annotation to link motifs with known recognition elements.
• Interactome input: Accepts lists of putative interactants, typically derived from high-throughput interactomics studies, as the basis for analysis.
• SLiM extraction and pairing: Extracts SLiMs and predicts potential SLiM–recognition domain pairings based on database annotations.
• Advanced filtering: Filters predicted interactions using motif E-values, IUPred2 disorder scores, and matches with known interactions from BioGRID.
• Structural modeling: Builds SLiM–domain interface models using SCWRL when structural templates are available.

Scientific Applications:

• Interactome exploration: Identification and annotation of SLiM-mediated interactions within large-scale protein–protein interaction datasets.
• Study of transient interactions: Detection and characterization of transient or weak interactions often mediated by SLiMs in disordered regions.
• Complementing conventional methods: Revealing SLiM-driven interactions that may be overlooked by sequence-conservation or domain-centric approaches.

Methodology:

Extracting SLiMs and their recognition domains from input data; displaying potential pairings based on ELM and Pfam annotations; filtering predictions using motif E-values, IUPred2 scores, and BioGRID matches; and performing structural modeling of SLiM–domain interfaces with SCWRL when templates are available.