Druggability analysis and prediction based on geometric distances between amino acid residues and protein surface pockets

Protein is the major component of the organism. A concave (pocket) on a protein surface is known to be thebest target for a drug to react. We previously presented astudy on distance analysis between pockets and amino acidresidue. We firstly identified pockets on the protein surfaceand then calculated distances between atoms of an amino acidresidue and the deepest points or the outer loops of the pockets. We extracted proteins which at least one of the pockets areclose to arbitrary pairs of amino acid residues, calculated theratios of druggable proteins, and visualized the distributionof the ratios as a colored matrix. We suggested from thevisualization results that particular pairs of amino acid residuesmay affect the druggability of the proteins in our previousstudy. This paper presents an extension of our study to explorethe relevance between druggability of proteins and distancesbetween a set of amino acid residues and protein surfacepockets. Our technique treats the pockets as 20-dimensionalvectors consisting of distances to each of amino acid residues, and applies GeodesicSOM with the set of the vectors. Sphericalmaps generated by GeodesicSOM are used to visualizationof distribution of the pockets in the 20-dimensional vectorspace, and estimation of druggability of proteins with the 20-dimensional vectors of the pockets.