Searching for disease causing SNPs is an ambitious task due to the complex nature of many phenotypes of interest and the enormous number of SNPs to be analyzed. We have developed computational models to investigate the effects of SNPs on the function and intrinsic properties of proteins, with a focus on protein structure. he prediction model investigates the (i) sequence-conservation in related proteins, (ii) structural alteration in the secondary and tertiary conformation, (iii) effect on stability, (iv) alteration in critical contact sites with other proteins, (v) effect on post-translational modification, and (vi) alterations in the physicochemical characteristics of amino acids. The output of these computational prediction tools will be evaluated to rank the SNPs according to their likelihood of being deleterious. The current proposal will allow the development of a model to establish a prioritized resource of functional SNPs.

Molecular approaches, to further characterize the effect of genetic variation on the gene function, are being investigated in collaboration with investigators interested in cancer related pathways.