  Protein tertiary structure defines its functions, classification and binding
sites. Similar structural characteristics between two proteins often lead to
the similar characteristics thereof. Determining structural similarity
accurately in real time is a crucial research issue. In this paper, we present
a novel and effective scoring scheme that is dependent on novel features
extracted from protein alpha carbon distance matrices. Our scoring scheme is
inspired from pattern recognition and computer vision. Our method is
significantly better than the current state of the art methods in terms of
family match of pairs of protein structures and other statistical measurements.
The effectiveness of our method is tested on standard benchmark structures. A
web service is available at http://research.buet.ac.bd:8080/Comograd/score.html
where you can get the similarity measurement score between two protein
structures based on our method.
