Abstract
Cells express thousands of macromolecules, and their functioning relies on multiple networks of intermolecular interactions. These interactions can be experimentally determine at different spatial and temporal resolutions. But, physical interfaces are not often delineated directly especially in high-throughput experiments. However, numerous three-dimensional structures of complexes have been already solved and sequence conservation allows comparative modeling of additional complexes. A large fraction of protein-protein interactions involves domain and so-called SLiMs (for Short Linear Motifs). Often, SLiMs lie in disordered regions or loops. Their small size and loosely folded nature prevent straightforward detection. SLiMAn (Short Linear Motif Analysis), a new web server is provided to help thorough analysis of interactomics data. Starting from a list of putative interactants such as the output of an interactomics study, SLiMs (from ELM) and SLiM-recognition domains (from Pfam) are extracted and potential pairing are displayed. Additionally, filters are available to dig into the predicted results such as the motif E-value, IUpred2 scoring functions for disorder or BioGRID interaction matches. When structural templates are available, a given SLiM and its recognition domain can be modeled using SCWRL. We illustrate, here, the use of SLiMAn on three distinct examples including one real-case study. We oversee wide-range applications for SLiMAn in the context of massive analysis of protein-protein interactions at proteome-wide scale. This new web server is made freely available at http://sliman.cbs.cnrs.fr.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
↵* E-mail: reys{at}cbs.cnrs.fr; Phone: +(33) 4 67 41 77 12. Fax: +(33) 4 67 41 79 13
† Short Linear Motifs Analysis
