Richard J Edwards, Ranjeeta Menon, Nicolas Palopoli & Jason WH Wong
Molecular mimicry is a well-established example of convergent evolution by which viruses evolve protein motifs that interact with host molecular machinery to hijack cellular functions. These short linear motifs (SLiMs) have only a handful of critical positions and a single point mutation is often sufficient to create or destroy a motif occurrence. This may have direct effects, such as eliminating a key regulatory interaction, or more subtle indirect effects by altering/blocking neighbouring interactions. There is much overlap in the breakdown of regulation caused by viruses and cancers - including oncogenic viruses - and so it is likely that many cancers are exploiting similar molecular mimicry mechanisms of protein interaction motifs during tumour development and progression.
We are combining publicly available datasets of host-host and host-pathogen PPI with recently developed tools from the SLiMSuite package to (1) identify novel candidates for viral mimicry of known host SLiMs, and (2) predict entirely new SLiM classes. In each case, signals of convergent evolution are identified using statistical over-representation of motifs in unrelated proteins. We are also using SLiM analysis tools to identify putative gain- and loss-of-function mutations from public cancer mutation databases. SLiM predictions and mutations will be placed in context using the human protein-protein interaction network and cross-referenced to known viral molecular mimicry and proteins/pathways affected in cancer. Simulated mutation data will be used to test for possible enrichment of mutations that create or destroy SLiMs.
Keywords: molecular mimicry, cancer, viruses, protein-protein interactions, short linear motifs, SLiMs