On the complexity measures of mutation hotspots in human TP53 protein

Abstract

The role of sequence complexity in 23 051 somatic missense mutations including 73 well-known mutation hotspots across 22 major cancers was studied in human TP53 proteins. A role for sequence complexity in TP53 protein mutations is suggested since (i) the mutation rate significantly increases in low amino acid pair bias complexity; (ii) probability distribution complexity increases following single point substitution mutations and strikingly increases after mutation at the mutation hotspots including six detectable hotspot mutations (R175, G245, R248, R249, R273, and R282); and (iii) the degree of increase in distribution complexity is significantly correlated with the frequency of missense mutations (r = -0.5758, P < 0.0001) across 20 major types of solid tumors. These results are consistent with the hypothesis that amino acid pair bias and distribution probability may be used as novel measures for protein sequence complexity, and the degree of complexity is related to its susceptibility to mutation, as such, it may be used as a predictor for modeling protein mutations in human cancers.