Computational Modelling Group

Interactome-wide prediction of short linear protein interaction motifs in humans

1st September 2007
Richard Edwards

A variety of bioinformatics and protein sequence modelling approaches are being combined to predict the location and nature short protein-protein interaction motifs from "omics" data.

Short linear motifs (SLiMs) are functional peptide microdomains, typically 3-10 amino acids in length, which usually occur in regions of intrinsic disorder. They are known to mediate many important protein-protein interactions, particularly in signaling pathways. With the exceptions of a few well-studied examples, however, we still know comparatively little about the abundance and variety of functional motifs. It is therefore of great interest to discover new interaction motifs that may form the basis of future reagents, and even drugs, to disrupt or regulate important interactions. We are using software we have developed, SLiMFinder, to mine the known human interaction data through probabilistic modeling of convergent evolution for novel SLiMs that might mediate protein interactions.

This work is being performed in collaboration with Denis Shields at University College Dublin and Norman Davey at the European Molecular Biology Laboratory.


Life sciences simulation: Bioinformatics, Biomedical, Biomolecular Organisation, Evolution, Systems biology

Programming languages and libraries: Python, R

Computational platforms: Iridis, Linux, Windows