SNP2Structure: A public database for mapping and modeling nsSNPs on human protein structures

ABSTRACT

With the development of deep DNA sequencing techniques, the cost for detecting mutations in the human genome falls significantly. Numerous non-synonymous single nucleotide polymorphisms (nsSNPs) have been identified and many of them are associated with human disease. One of the long-standing challenges is to understand how nsSNPs change protein structure and further affect their function. While it is impractical to solve all the mutated protein structures experimentally, it is quite feasible to model the mutated structures in silico. Toward this goal, we are building a publicly available structure database (SNP2Structure) to facilitate our research endeavors. Compared with the existing web portals with a similar aim, ours has three major advantages. First, we corrected the existing sequence mapping discrepancies presented in others. Although the percentage of erroneously mapped structures is small, it is critical to correct such errors. Second, our portal offers comparison of two structures simultaneously. Third, the mutated structures are available to download locally for further investigations. We believe SNP2Structure will be a valuable tool to the research community to understand the functional impact of disease-causing nsSNPs.

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Index Terms

• Applied computing

  • Life and medical sciences