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. 2015 Aug 21:5:13275.
doi: 10.1038/srep13275.

CoMOGrad and PHOG: From Computer Vision to Fast and Accurate Protein Tertiary Structure Retrieval

Rezaul Karim  1 , Mohd Momin Al Aziz  1 , Swakkhar Shatabda  1   2 , M Sohel Rahman  1 , Md Abul Kashem Mia  1 , Farhana Zaman  1 , Salman Rakin  1
Affiliations

CoMOGrad and PHOG: From Computer Vision to Fast and Accurate Protein Tertiary Structure Retrieval

Rezaul Karim et al. Sci Rep. .

Abstract

The number of entries in a structural database of proteins is increasing day by day. Methods for retrieving protein tertiary structures from such a large database have turn out to be the key to comparative analysis of structures that plays an important role to understand proteins and their functions. In this paper, we present fast and accurate methods for the retrieval of proteins having tertiary structures similar to a query protein from a large database. Our proposed methods borrow ideas from the field of computer vision. The speed and accuracy of our methods come from the two newly introduced features- the co-occurrence matrix of the oriented gradient and pyramid histogram of oriented gradient- and 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/.

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Figures

Figure 1
Figure 1. Representation of β sheets of domain d1n4ja in α carbon distance matrix gray-scale image.
Figure 2
Figure 2. Representation of α helices of domain d1irqa in α carbon distance matrix gray-scale image.
Figure 3
Figure 3. Level 1 quad tree of α carbon distance matrix image.
Figure 4
Figure 4. Percentage of matches of Class, Fold, Superfamily and Family for up to top 50 retrieval results.
Figure 5
Figure 5. MCC values for binary classification.
See this image and copyright information in PMC

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