| Summary: | Mutations of protein kinases and cytokines are common and can cause cancer and other diseases. However, our understanding of the mutability in these genes remains rudimentary. Therefore, given previously known factors which are associated with high mutation rates, we analyzed how many genes encoding druggable kinases match (i) proximity to telomeres or (ii) high A+T content. We extracted this genomic information using the National Institute of Health Genome Data Viewer. First, among 129 druggable human kinase genes studied, 106 genes satisfied either factors (i) or (ii), resulting in an 82% match. Moreover, a similar 85% match rate was found in 73 genes encoding pro-inflammatory cytokines of multisystem inflammatory syndrome in children. Based on these promising matching rates, we further compared these two factors utilizing 20 de novo mutations of mice exposed to space-like ionizing radiation, in order to determine if these seemingly random mutations were similarly predictable with this strategy. However, only 10 of these 20 murine genetic loci met (i) or (ii), leading to only a 50% match. When compared with the mechanisms of top-selling FDA approved drugs, this data suggests that matching rate analysis on druggable targets is feasible to systematically prioritize the relative mutability—and therefore therapeutic potential—of the novel candidates.
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