Abstract
AbstractShort linear motifs (SLiMs) in proteins are short functionally independent sequence stretches with a defined function and required for proteins to interact with their environment. Their functional importance makes it interesting to analyse SLiM features further, such as their structural or evolutionary properties, to understand better how SLiMs evolve to shape protein functions.We developed an automated pipeline to analyse 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, positional and amino acid property conservation. To store and easily mine data from the evo-MOTiF pipeline, we developed the evo-MOTiF database, which currently holds ∼9500 motifs, combining data from ELM, PhosphoSitePlus, as well as from cross-linking mass-spectrometry (XL-MS) experiments. The evo-MOTiF database distinguishes itself further by allowing effortless filtering for SLiMs with specific properties, such as disorder, or conservation in evolution and by providing evolutionary, as well as structural information for SLiMs. Preliminary analysis of SLiM features reveals weak negative correlation between disorder and overall, positional, as well as amino acid property conservation, which is in support of previous observations on smaller datasets.The evo-MOTiF pipeline and database are freely available athttps://gitlab.com/habermann_lab/slimsandhttp://etnadb.ibdm.univ-mrs.fr/index.php, respectively.
Publisher
Cold Spring Harbor Laboratory