<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Arbiza, L.</style></author><author><style face="normal" font="default" size="100%">Duchi, S.</style></author><author><style face="normal" font="default" size="100%">Montaner, D.</style></author><author><style face="normal" font="default" size="100%">Burguet, J.</style></author><author><style face="normal" font="default" size="100%">Pantoja-Uceda, D.</style></author><author><style face="normal" font="default" size="100%">Pineda-Lucena, A.</style></author><author><style face="normal" font="default" size="100%">Dopazo, J.</style></author><author><style face="normal" font="default" size="100%">H. Dopazo</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Selective pressures at a codon-level predict deleterious mutations in human disease genes</style></title><secondary-title><style face="normal" font="default" size="100%">J Mol Biol</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Amino Acid Sequence Amino Acid Substitution Codon/*genetics Databases</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Evolution</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Models</style></keyword><keyword><style  face="normal" font="default" size="100%">Human Humans Models</style></keyword><keyword><style  face="normal" font="default" size="100%">Inborn/*genetics Genome</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular Genes</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular Molecular Sequence Data *Mutation Neoplasms/genetics Proteins/genetics *Selection (Genetics) Tumor Suppressor Protein p53/chemistry/genetics</style></keyword><keyword><style  face="normal" font="default" size="100%">p53 Genetic Diseases</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=16584746</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">5</style></number><volume><style face="normal" font="default" size="100%">358</style></volume><pages><style face="normal" font="default" size="100%">1390-404</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Deleterious mutations affecting biological function of proteins are constantly being rejected by purifying selection from the gene pool. The non-synonymous/synonymous substitution rate ratio (omega) is a measure of selective pressure on amino acid replacement mutations for protein-coding genes. Different methods have been developed in order to predict non-synonymous changes affecting gene function. However, none has considered the estimation of selective constraints acting on protein residues. Here, we have used codon-based maximum likelihood models in order to estimate the selective pressures on the individual amino acid residues of a well-known model protein: p53. We demonstrate that the number of residues under strong purifying selection in p53 is much higher than those that are strictly conserved during the evolution of the species. In agreement with theoretical expectations, residues that have been noted to be of structural relevance, or in direct association with DNA, were among those showing the highest signals of purifying selection. Conversely, those changing according to a neutral, or nearly neutral mode of evolution, were observed to be irrelevant for protein function. Finally, using more than 40 human disease genes, we demonstrate that residues evolving under strong selective pressures (omega&lt;0.1) are significantly associated (p&lt;0.01) with human disease. We hypothesize that non-synonymous change on amino acids showing omega&lt;0.1 will most likely affect protein function. The application of this evolutionary prediction at a genomic scale will provide an a priori hypothesis of the phenotypic effect of non-synonymous coding single nucleotide polymorphisms (SNPs) in the human genome.</style></abstract><notes><style face="normal" font="default" size="100%">Arbiza, Leonardo Duchi, Serena Montaner, David Burguet, Jordi Pantoja-Uceda, David Pineda-Lucena, Antonio Dopazo, Joaquin Dopazo, Hernan Research Support, Non-U.S. Gov’t England Journal of molecular biology J Mol Biol. 2006 May 19;358(5):1390-404. Epub 2006 Mar 15.</style></notes></record></records></xml>