  Due to the advancements in technology number of entries in the structural
database of proteins are increasing day by day. Methods for retrieving protein
tertiary structures from this large database is the key to comparative analysis
of structures which plays an important role to understand proteins and their
function. In this paper, we present fast and accurate methods for the retrieval
of proteins from a large database with tertiary structures similar to a query
protein. Our proposed methods borrow ideas from the field of computer vision.
The speed and accuracy of our methods comes from the two newly introduced
features, the co-occurrence matrix of the oriented gradient and pyramid
histogram of oriented gradient and from the use of Euclidean distance as the
distance measure. Experimental results clearly indicate the superiority of our
approach in both running time and accuracy. Our method is readily available for
use from this website: http://research.buet.ac.bd:8080/Comograd/.
