Evidence for the concerted evolution between short linear protein motifs and their flanking regions

Abstract

Background: Linear motifs are short modules of protein sequences that play a crucial role in mediating and regulating many protein-protein interactions. The function of linear motifs strongly depends on the context, e.g. functional instances mainly occur inside flexible regions that are accessible for interaction. Sometimes linear motifs appear as isolated islands of conservation in multiple sequence alignments. However, they also occur in larger blocks of sequence conservation, suggesting an active role for the neighbouring amino acids.

Results: The evolution of regions flanking 116 functional linear motif instances was studied. The conservation of the amino acid sequence and order/disorder tendency of those regions was related to presence/absence of the instance. For the majority of the analysed instances, the pairs of sequences conserving the linear motif were also observed to maintain a similar local structural tendency and/or to have higher local sequence conservation when compared to pairs of sequences where one is missing the linear motif. Furthermore, those instances have a higher chance to co-evolve with the neighbouring residues in comparison to the distant ones. Those findings are supported by examples where the regulation of the linear motif-mediated interaction has been shown to depend on the modifications (e.g. phosphorylation) at neighbouring positions or is thought to benefit from the binding versatility of disordered regions.

Conclusion: The results suggest that flanking regions are relevant for linear motif-mediated interactions, both at the structural and sequence level. More interestingly, they indicate that the prediction of linear motif instances can be enriched with contextual information by performing a sequence analysis similar to the one presented here. This can facilitate the understanding of the role of these predicted instances in determining the protein function inside the broader context of the cellular network where they arise.

Figure 1. Frequency distribution of IU P_diff for the P_LM and A_LM sets.

Frequency is calculated per instance as the proportion of sequence pairs falling in a given IU P_diff range. Error bars indicate the standard deviation of the frequency when averaging over all the instances in that range. Significant difference (p-value<0.00001) between P_LM and A_LM distributions is marked by the asterisk.

Figure 2. Frequency profiles for the P_LM and A_LM sets.

Distribution of IU P_diff as a function of sequence conservation: locCons (A,B) and globCons (C,D). Colour represents the frequency of sequence pairs whose local structure and sequence conservation values fall in a given range of IU P_diff and locCons/globCons, averaged over all the instances.

Figure 3. Examples of evolutionary patterns of the regions flanking LM.

IU P_diff versus locCons and globCons for the sequence pairs in P_LM (black dots) and A_LM (blue asterisks) sets per instance. Three groups with distinct evolutionary behaviour can be identified: instances whose P_LM and A_LM frequency profiles of IU P_diff versus locCons are less correlated than the corresponding IU P_diff versus globCons profiles (A); instances where the contrary is true (B); instances that, additionally, have a significantly different IU P_diff distribution (C,D).

Figure 4. Frequency of coupling between LM and neighbouring or distant residues.

Box plots show the distribution of the frequency of coupling for instances in Table 2. A. Distribution for instances whose presence/absence is better described by the local rather than the global sequence conservation (i.e. locCons correlation<globCons correlation) B. Distribution for instances with globCons correlation<locCons correlation.