protein motifs

Protein motifs (also called short linear motifs in proteins or SLiMs) are involved in virtually every interaction a protein makes. They are required for binding to other proteins, ligands, are sites for post-translational modifications, protein degradation or localization. As they are so short and mostly function independently of the rest of the protein's sequence or structure, they are ideal evolutionary 'hotspots' for evolving novel protein functions. Yet, depending on their localization in the protein, they might experience different evolutionary pressures: a protein motif in a disordered region might evolve more easily than one in a fully structured region.

While we know a universe of proteins, we know only of very few protein motifs, which have been experimentally verified, in relation. Thus, most of our current hypothesis on the structural context of SLiMs or how they evolve is based on a view examples.

However novel experimental techniques (mostly based on Mass-Spec) have uncovered a broader range of functional motifs that we can use for studying them.

We look at motif evolution in a structural context and do so in a comprehensive manner, considering all so-far known protein motifs that are experimentally verified. We want to understand how motifs evolve in different structural contexts and identify novel motifs that lead to phenotypic changes of their 'host' protein.

Protein motifs are defined as self-sufficient functional units. They are typically only between 3 and 23 amino acids long and have various functions in proteins. They can serve as cleavage sites, are required for proteasomal degradation, are involved in docking and ligand binding, serve as signals for post-translational modification or are signals for subcellular localization.

Their shortness and the fact that they typically lack substantial sequence conservation makes them very difficult to find de novo – i.e. without prior information on the localization or nature of the motif. We are using evolutionary restricted Hidden Markov Model (HMM) comparison in combination with a hierarchical model of motif trees to identify short functional motifs in proteins de novo (Prytuliak, et al., NAR 2017;45 (W1):W470-W477, 2017, doi: 10.1093/nar/gkx341). In collaboration with wet-lab researchers, we experimentally test our predicted motifs.

We have meanwhile developed a stand-alone version of HH-MOTiF that can be downloaded from our git-repository. The stand-alone version allows local usage and processing of large datasets.