4.8 Article

SNPeffect 4.0: on-line prediction of molecular and structural effects of protein-coding variants

Journal

NUCLEIC ACIDS RESEARCH
Volume 40, Issue D1, Pages D935-D939

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/nar/gkr996

Keywords

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Funding

  1. Interuniversity Attraction Poles (IAP Network) of the Belgian Federal Science Policy Office (BelSPo) (VIB Switch laboratory) [6/43]
  2. Flanders Institute for Science and Technology (IWT)
  3. Fund for Scientific Research (FWO), Flanders
  4. MICINN (RTICC, ISCIII) (Dopazo lab) [BIO2008-04212, RD06/0020/1019]
  5. GVA-FEDER [PROMETEO/2010/001]
  6. VIB

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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.

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