  Cavities on the structures of proteins are formed due to interaction between
proteins and some small molecules, known as ligands. These are basically the
locations where ligands bind with proteins. Actual detection of such locations
is all-important to succeed in the entire drug design process. This study
proposes a Voronoi Tessellation based novel cavity detection model that is used
to detect cavities on the structure of proteins. As the atom space of protein
structure is dense and of large volumes and the DBSCAN (Density Based Spatial
Clustering of Applications with Noise) algorithm can handle such type of data
very well as well as it is not mandatory to have knowledge about the numbers of
clusters (cavities) in data as priori in this algorithm, this study proposes to
implement the proposed algorithm with the DBSCAN algorithm.
