02231nas a2200325   4500008004100000022001400041245010200055210006900157260001300226300001100239490000700250520119100257653002301448653001101471653001301482653002701495653001401522653003601536653002501572653001301597100002001610700002101630700001801651700002801669700001801697700002001715700002301735700002301758856012401781       2012                        eng d  a1362-496200aSNPeffect 4.0: on-line prediction of molecular and structural effects of protein-coding variants.0 aSNPeffect 40 online prediction of molecular and structural effec  c2012 Jan  aD935-90 v403 a<p>Single nucleotide variants (SNVs) are, together with copy number variation, the primary source of variation in the human genome and are associated with phenotypic variation such as altered response to drug treatment and susceptibility to disease. Linking structural effects of non-synonymous SNVs to functional outcomes is a major issue in structural bioinformatics. The SNPeffect database (http://snpeffect.switchlab.org) uses sequence- and structure-based bioinformatics tools to predict the effect of protein-coding SNVs on the structural phenotype of proteins. It integrates aggregation prediction (TANGO), amyloid prediction (WALTZ), chaperone-binding prediction (LIMBO) and protein stability analysis (FoldX) for structural phenotyping. Additionally, SNPeffect holds information on affected catalytic sites and a number of post-translational modifications. The database contains all known human protein variants from UniProt, but users can now also submit custom protein variants for a SNPeffect analysis, including automated structure modeling. The new meta-analysis application allows plotting correlations between phenotypic features for a user-selected set of variants.</p>10aDatabases, Protein10aHumans10aInternet10aMeta-Analysis as Topic10aPhenotype10aPolymorphism, Single Nucleotide10aProtein Conformation10aProteins1 aDe Baets, Greet1 aVan Durme, Joost1 aReumers, Joke1 aMaurer-Stroh, Sebastian1 aVanhee, Peter1 aDopazo, Joaquin1 aSchymkowitz, Joost1 aRousseau, Frederic  uhttp://clinbioinfosspa.es/content/snpeffect-40-line-prediction-molecular-and-structural-effects-protein-coding-variants01789nas a2200193   4500008004100000245015100041210006900192260001300261300001300274490000600287520104500293100002001338700001801358700002801376700002001404700002301424700002301447856012501470       2011                        eng d00aAn evolutionary trade-off between protein turnover rate and protein aggregation favors a higher aggregation propensity in fast degrading proteins.0 aevolutionary tradeoff between protein turnover rate and protein   c2011 Jun  ae10020900 v73 a<p>We previously showed the existence of selective pressure against protein aggregation by the enrichment of aggregation-opposing ’gatekeeper’ residues at strategic places along the sequence of proteins. Here we analyzed the relationship between protein lifetime and protein aggregation by combining experimentally determined turnover rates, expression data, structural data and chaperone interaction data on a set of more than 500 proteins. We find that selective pressure on protein sequences against aggregation is not homogeneous but that short-living proteins on average have a higher aggregation propensity and fewer chaperone interactions than long-living proteins. We also find that short-living proteins are more often associated to deposition diseases. These findings suggest that the efficient degradation of high-turnover proteins is sufficient to preclude aggregation, but also that factors that inhibit proteasomal activity, such as physiological ageing, will primarily affect the aggregation of short-living proteins.</p>1 aDe Baets, Greet1 aReumers, Joke1 aBlanco, Javier, Delgado1 aDopazo, Joaquin1 aSchymkowitz, Joost1 aRousseau, Frederic  uhttp://clinbioinfosspa.es/content/evolutionary-trade-between-protein-turnover-rate-and-protein-aggregation-favors-higher