A structural bioinformatics approach to the analysis of nonsynonymous single nucleotide polymorphisms (nsSNPs) and their relation to disease

Tools

Item Type:	Article
Title:	A structural bioinformatics approach to the analysis of nonsynonymous single nucleotide polymorphisms (nsSNPs) and their relation to disease
Creators Name:	Worth, C.L., Bickerton, G.R.J., Schreyer, A., Forman, J.R., Cheng, T.M.K., Lee, S., Gong, S., Burke, D.F. and Blundell, T.L.
Abstract:	The prediction of the effects of nonsynonymous single nucleotide polymorphisms (nsSNPs) on function depends critically on exploiting all information available on the three-dimensional structures of proteins. We describe software and databases for the analysis of nsSNPs that allow a user to move from SNP to sequence to structure to function. In both structure prediction and the analysis of the effects of nsSNPs, we exploit information about protein evolution, in particular, that derived from investigations on the relation of sequence to structure gained from the study of amino acid substitutions in divergent evolution. The techniques developed in our laboratory have allowed fast and automated sequence-structure homology recognition to identify templates and to perform comparative modeling; as well as simple, robust, and generally applicable algorithms to assess the likely impact of amino acid substitutions on structure and interactions. We describe our strategy for approaching the relationship between SNPs and disease, and the results of benchmarking our approach - human proteins of known structure and recognized mutation.
Keywords:	Single Nucleotide Polymorphism, Disease Association, Protein Structure, Comparative Modeling
Source:	Journal of Bioinformatics and Computational Biology
ISSN:	0219-7200
Publisher:	Imperial College Press
Volume:	5
Number:	6
Page Range:	1297-1318
Date:	December 2007
Official Publication:	https://doi.org/10.1142/S0219720007003120
PubMed:	View item in PubMed

Repository Staff Only: item control page