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Value of predictive bioinformatics in inherited metabolic diseases

World Journal of Medical Genetics 2015年第3期5卷 46-51页

作者： David J Timson School of Biological Sciences and Institute for Global Food Security Queen’s University Belfast

Typically,inherited metabolic diseases arise from point mutations in genes encoding metabolic enzymes. Although some of these mutations directly affect amino acid residues in the active sites of these enzymes,the majority do not. It is now well accepted that the majority of these disease-associated mutations exert their effects through alteration of protein stability,which causes a reduction in enzymatic activity. This finding suggests a way to predict the severity of newly discovered mutations. In silico prediction of the effects of amino acid sequence alterations on protein stability often correlates with disease severity. However,no stability prediction tool is perfect and,in general,better results are obtained if the predictions from a variety of tools are combined and then interpreted. In addition to predicted alterations to stability,the degree of conservation of a particular residue can also be a factor which needs to be taken into account: alterations to highly conserved residues are more likely to be associated with severe forms of the disease. The approach has been successfully applied in a variety of inherited metabolic diseases,but further improvements are necessary to enable robust translation into clinically useful tools.

关键词： Genetic disease Metabolism In silico method Protein stability disease-associated mutation

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