title: Dipeptide analysis of p53 mutations and evolution of p53 family proteins.
abstract: p53 gain-of-function mutations are similar to driver mutations in cancer genes, with both promoting tumorigenesis. Most previous studies focused on residues lost by mutations, providing information related to a dominantly-negative effect. However, to understand gain-of-function mutations, it is also important to investigate what are the distributions of residues gained by mutations. We compile available p53/p63/p73 protein sequences and construct a non-redundant dataset. We analyze the amino acid and dipeptide composition of p53/p63/p73 proteins across evolution and compare them with the gain/loss of amino acids and dipeptides in human p53 following cancer-related somatic mutations. We find that the ratios of amino acids gained via somatic mutations during evolution to those lost through p53 cancer mutations correlate with the ratios found in single nucleotide polymorphisms in the human proteome. The dipeptide mutational gain/loss ratios are inversely correlated with those observed over p53 evolution but tend to follow the increasing p63/p73-like dipeptide propensities. We successfully simulated the p53 cancer mutation spectrum using the dipeptide composition across the p53 family accounting for the likelihood of mutations in p53 codons. The results revealed that the p53 mutation spectrum is dominated not only by p53 evolution but also by reversal of evolution to a certain degree. This article is part of a Special Issue entitled: Computational Proteomics, Systems Biology & Clinical Implications. Guest Editor: Yudong Cai.
authors.affiliation: State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai 200433, China.
authors.forename: Qiang
authors.initials: Q
authors.lastname: Huang
authors.forename: Long
authors.initials: L
authors.lastname: Yu
authors.forename: Arnold J
authors.initials: AJ
authors.lastname: Levine
authors.forename: Ruth
authors.initials: R
authors.lastname: Nussinov
authors.forename: Buyong
authors.initials: B
authors.lastname: Ma
mesh_terms: D000595:Amino Acid Sequence; D019295:Computational Biology / Q000379:methods*; D004268:DNA-Binding Proteins / Q000737:chemistry / Q000235:genetics; D004151:Dipeptides / Q000737:chemistry* / Q000235:genetics; D019143:Evolution, Molecular; D006801:Humans; D009154:Mutation; D009369:Neoplasms / Q000235:genetics / Q000473:pathology; D014157:Transcription Factors; D016159:Tumor Suppressor Protein p53 / Q000737:chemistry / Q000235:genetics*
chemical_list: D004268:DNA-Binding Proteins; D004151:Dipeptides; C495901:TP53 protein, human; D014157:Transcription Factors; D016159:Tumor Suppressor Protein p53
keywords: Cancer; Evolution; Gene regulation; Mutation; Phosphorylation; p53/p63/p73