SNPeffect 4.0: on-line prediction of molecular and structural effects of protein-coding variants
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...
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| Veröffentlicht in: | Nucleic acids research 2012-01, Vol.40 (D1), p.D935-D939 |
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| container_title | Nucleic acids research |
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| creator | De Baets, Greet Van Durme, Joost Reumers, Joke Maurer-Stroh, Sebastian Vanhee, Peter Dopazo, Joaquin Schymkowitz, Joost Rousseau, Frederic |
| description | 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. |
| doi_str_mv | 10.1093/nar/gkr996 |
| format | Article |
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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.</description><identifier>ISSN: 0305-1048</identifier><identifier>EISSN: 1362-4962</identifier><identifier>DOI: 10.1093/nar/gkr996</identifier><identifier>PMID: 22075996</identifier><language>eng</language><publisher>England: Oxford University Press</publisher><subject>Databases, Protein ; Humans ; Internet ; Meta-Analysis as Topic ; Phenotype ; Polymorphism, Single Nucleotide ; Protein Conformation ; Proteins - genetics</subject><ispartof>Nucleic acids research, 2012-01, Vol.40 (D1), p.D935-D939</ispartof><rights>The Author(s) 2011. 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| ispartof | Nucleic acids research, 2012-01, Vol.40 (D1), p.D935-D939 |
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| source | Oxford Journals Open Access Collection; MEDLINE; DOAJ Directory of Open Access Journals; PubMed Central; Free Full-Text Journals in Chemistry |
| subjects | Databases, Protein Humans Internet Meta-Analysis as Topic Phenotype Polymorphism, Single Nucleotide Protein Conformation Proteins - genetics |
| title | SNPeffect 4.0: on-line prediction of molecular and structural effects of protein-coding variants |
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