Gemoetrical verification of protein structure for single nucleotide polymorphism (SNP)

Among non-synonymous SNPs that cause amino acid change in the protein product, the selection of disease-causing SNPs has been of great interest. We present the comparison between the evolutionary (SIFT score) and structural information (binding pocket) to show that the incorporation between them provides an advantage of sorting disease-causing SNPs from normal SNPs. To set up the procedure, we apply the machine learning method to the test data set from the laboratory experiments.