Short linear motifs (SLiMs) in proteins are short functionally independent sequence stretches with a defined function and are required for proteins to interact with their environment. Their functional importance makes it interesting to analyze SLiM features further, such as their structural or evolutionary properties, to understand better how SLiMs evolve to shape protein functions. I will talk about an automated pipeline we just developed to analyze features of SLiMs, called evo-MOTiF. This pipeline takes as input a single protein sequence and its associated SLiM(s) and returns a set of scores associated with SLiM features, including their disorder, as well as their overall and positional conservation. To store and easily mine data from the evo-MOTiF pipeline, we developed the evo-MOTiF database, which currently holds ~7700 motifs, combining data from ELM, PhosphoSitePlus, as well as from cross-linking mass-spectrometry (XL-MS) experiments. Users can easily search for SLiMs with certain properties such as disorder, or conservation in evolution and by providing evolutionary, or structural information for SLiMs by filtering data in the evo-MOTiF database. I will show a preliminary analysis of SLiM features, revealing weak negative correlation between disorder and overall, as well as positional conservation, which is in support of previous observations on smaller datasets, and discuss potentials and limits of the evo-MOTiF pipeline and database. I will also show how evo-MOTiF can be used to find taxon-specific SLiMs that could give rise to novel phenotypes, on the example of the Myxococcus xanthus Kill system. The evo-MOTiF pipeline and database are freely available at https://gitlab.com/habermann_lab/slims and http://etnadb.ibdm.univ-mrs.fr/index.php, respectively. We recently submitted a pre-print of the evo-MOTiF pipeline and database to biorXiv: https://www.biorxiv.org/content/10.1101/2022.08.29.505684v1.article-info.
Published on September 12, 2022