Unit

UNIT 8.22 Exploring Short Linear Motifs Using the ELM Database and Tools

  1. Marc Gouw1,
  2. Hugo Sámano-Sánchez1,
  3. Kim Van Roey1,
  4. Francesca Diella1,
  5. Toby J. Gibson1,
  6. Holger Dinkel1,2

Published Online: 27 JUN 2017

DOI: 10.1002/cpbi.26

Current Protocols in Bioinformatics

Current Protocols in Bioinformatics

How to Cite

Gouw, M., Sámano-Sánchez, H., Van Roey, K., Diella, F., Gibson, T.J., & Dinkel, H. (2017). Exploring short linear motifs using the ELM database and tools. Current Protocols in Bioinformatics, 58, 8.22.18.22.35. doi: 10.1002/cpbi.26

Author Information

  1. 1

    Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany

  2. 2

    Leibniz-Institute on Aging—Fritz Lipmann Institute (FLI), Jena, Germany

Publication History

  1. Published Online: 27 JUN 2017

Abstract

The Eukaryotic Linear Motif (ELM) resource is dedicated to the characterization and prediction of short linear motifs (SLiMs). SLiMs are compact, degenerate peptide segments found in many proteins and essential to almost all cellular processes. However, despite their abundance, SLiMs remain largely uncharacterized. The ELM database is a collection of manually annotated SLiM instances curated from experimental literature. In this article we illustrate how to browse and search the database for curated SLiM data, and cover the different types of data integrated in the resource. We also cover how to use this resource in order to predict SLiMs in known as well as novel proteins, and how to interpret the results generated by the ELM prediction pipeline. The ELM database is a very rich resource, and in the following protocols we give helpful examples to demonstrate how this knowledge can be used to improve your own research. © 2017 by John Wiley & Sons, Inc.

Keywords:

  • short linear motifs;
  • bioinformatics;
  • protein-protein interaction;
  • molecular switches;
  • cell regulation