MutDB services: interactive structural analysis of mutation data

Dantzer, Jessica; Moad, Charles W.; Heiland, Randy; Mooney, Sean D.

doi:10.1093/nar/gki404

Cited by 47 publications

(28 citation statements)

References 20 publications

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“…The UniProtKB/Swissprot database contains manually annotated protein entries that feature partial lists for known sequence variants [Yip et al, 2008]. There are also databases available that aim at annotating human variation data with phenotype variations and protein structural and functional information, such as MS2PH-db (http://ms2phdb-pbil.ibcp.fr/ cgi-bin/home), MutDB [Dantzer et al, 2005], SAAPdb [Cavallo and Martin, 2005], and KMDB/MutationView [Minoshima et al, 2001]. Locus-specific databases (LSDBs) list variants in specific genes and are typically manually annotated.…”

Section: Methods For the Analysis Of Mutations Databasesmentioning

confidence: 99%

Pathogenic or not? And if so, then how? Studying the effects of missense mutations using bioinformatics methods

2009

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Many gene defects are relatively easy to identify experimentally, but obtaining information about the effects of sequence variations and elucidation of the detailed molecular mechanisms of genetic diseases will be among the next major efforts in mutation research. Amino acid substitutions may have diverse effects on protein structure and function; thus, a detailed analysis of the mutations is essential. Experimental study of the molecular effects of mutations is laborious, whereas useful and reliable information about the effects of amino acid substitutions can readily be obtained by theoretical methods. Experimentally defined structures and molecular modeling can be used as a basis for interpretation of the mutations. The effects of missense mutations can be analyzed even when the 3D structure of the protein has not been determined, although structure-based analyses are more reliable. Structural analyses include studies of the contacts between residues, their implication for the stability of the protein, and the effects of the introduced residues. Investigations of steric and stereochemical consequences of substitutions provide insights on the molecular fit of the introduced residue. Mutations that change the electrostatic surface potential of a protein have wide-ranging effects. Analyses of the effects of mutations on interactions with ligands and partners have been performed for elucidation of functional mutations. We have employed numerous methods for predicting the effects of amino acid substitutions. We discuss the applicability of these methods in the analysis of genes, proteins, and diseases to reveal protein structure-function relationships, which is essential to gain insights into disease genotype-phenotype correlations.

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Section: Methods For the Analysis Of Mutations Databasesmentioning

confidence: 99%

Pathogenic or not? And if so, then how? Studying the effects of missense mutations using bioinformatics methods

2009

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“…MutDB (http://www.mutdb.org) annotates SAAPs from dbSNP and UniProtKB/SwissProt [Boeckmann et al, 2003] with structural information [Dantzer et al, 2005]. PolyPhen (http:// www.bork.embl-heidelberg.de/PolyPhen) allows the user to analyse their own SAAPs, in addition to those in dbSNP [Ramensky et al, 2002].…”

Section: Introductionmentioning

confidence: 99%

The SAAPdb web resource: A large-scale structural analysis of mutant proteins

et al. 2009

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The Single Amino Acid Polymorphism database (SAAPdb) is a new resource for the analysis and visualization of the structural effects of mutations. Our analytical approach is to map single nucleotide polymorphisms (SNPs) and pathogenic deviations (PDs) to protein structural data held within the Protein Data Bank. By mapping mutations onto protein structures, we can hypothesize whether the mutant residues will have any local structural effect that may "explain" a deleterious phenotype. Our prior work used a similar approach to analyze mutations within a single protein. An analysis of the contents of SAAPdb indicates that there are clear differences in the sequence and structural characteristics of SNPs and PDs, and that PDs are more often explained by our structural analysis. This mapping and analysis is a useful resource for the mutation community and is publicly available at http://www.bioinf.org.uk/saap/db/.

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“…The topoSNP tool focuses on nonsynonymous SNPs (nsSNPs) and places these SNPs in the context of the protein structure, although the number of proteins and nsSNPs included is limited (Stitziel et al, 2004).The nsSNPAnalyzer (Bao and Cui, 2005) and SNPs3D also look at nsSNPs and use multiple sequence alignments and protein structure information to predict those nsSNPs that will result in a phenotype. Similarly, the MutDB database (Dantzer et al, 2005) places SNPs, as well as mutations, in the context of protein structure and SNPs3D uses information on alterations to protein stability and sequence comparisons to identify deleterious changes. SNPeffect (Reumers et al, 2005) evaluates nsSNPs for effects on protein stability, folding, active sites, phosphorylation, glycosylation, subcellular localization, turnover rate, aggregation, amyloidosis, and chaperone interaction.…”

Section: Appendix 1 Tools To Aid In Snp Selectionmentioning

confidence: 99%