Investigation and prediction of the severity of p53 mutants using parameters from structural calculations.
A method has been developed to predict the effects of mutations in the p53 cancer suppressor gene. The new method uses novel parameters combined with previously established parameters. The most important parameter is the stability measure of the mutated structure calculated using molecular modelling. For each mutant, a severity score is reported, which can be used for classification into deleterious and nondeleterious. Both structural features and sequence properties are taken into account. The method has a prediction accuracy of 77% on all mutants and 88% on breast cancer mutations affecting WAF1 promoter binding. When compared with earlier methods, using the same dataset, our method clearly performs better. As a result of the severity score calculated for every mutant, valuable knowledge can be gained regarding p53, a protein that is believed to be involved in over 50% of all human cancers.
Carlsson
Jonas
J
IFM Bioinformatics, Linköping University, Sweden. jonca@ifm.liu.se
Soussi
Thierry
T
Persson
Bengt
B
D000465:Algorithms; D001943:Breast Neoplasms / Q000235:genetics*; D050759:Cyclin-Dependent Kinase Inhibitor p21 / Q000235:genetics / Q000378:metabolism; D005260:Female; D006801:Humans; D008958:Models, Molecular; D009154:Mutation; D009369:Neoplasms / Q000235:genetics / Q000517:prevention & control; D011401:Promoter Regions, Genetic; D011485:Protein Binding; D011487:Protein Conformation; D012720:Severity of Illness Index; D016159:Tumor Suppressor Protein p53 / Q000737:chemistry / Q000235:genetics*
C493956:CDKN1A protein, human; D050759:Cyclin-Dependent Kinase Inhibitor p21; D016159:Tumor Suppressor Protein p53