Computational Prediction of Disordered Protein Motifs Using SLiMSuite

Richard J Edwards; Kirsti Paulsen; Carla M Aguilar Gomez; Åsa Pérez-Bercoff

doi:10.1007/978-1-0716-0524-0_3

Computational Prediction of Disordered Protein Motifs Using SLiMSuite

Methods Mol Biol. 2020:2141:37-72. doi: 10.1007/978-1-0716-0524-0_3.

Authors

Richard J Edwards¹, Kirsti Paulsen², Carla M Aguilar Gomez², Åsa Pérez-Bercoff²

Affiliations

¹ School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, NSW, Australia. richard.edwards@unsw.edu.au.
² School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, NSW, Australia.

PMID: 32696352
DOI: 10.1007/978-1-0716-0524-0_3

Abstract

Short linear motifs (SLiMs) are important mediators of interactions between intrinsically disordered regions of proteins and their interaction partners. Here, we detail instructions for the computational prediction of SLiMs in disordered protein regions, using the main tools of the SLiMSuite package: (1) SLiMProb identifies and calculates enrichment of predefined motifs in a set of proteins; (2) SLiMFinder predicts SLiMs de novo in a set of proteins, accounting for evolutionary relationships; (3) QSLiMFinder increases SLiMFinder sensitivity by focusing SLiM prediction on a specific query protein/region; (4) CompariMotif compares predicted SLiMs to known SLiMs or other SLiM predictions to identify common patterns. For each tool, command-line and online server examples are provided. Detailed notes provide additional advice on different applications of SLiMSuite, including batch running of multiple datasets and conservation masking using alignments of predicted orthologues.

Keywords: Domain-motif interactions; Minimotif; Motif prediction; Protein–protein interactions; SLiM; Short linear motif.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Amino Acid Motifs
Amino Acid Sequence
Computational Biology / methods*
Intrinsically Disordered Proteins / chemistry*
Search Engine
Sequence Alignment
Software*

Substances

Intrinsically Disordered Proteins