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

Karim R, Aziz MM, Shatabda S, Rahman MS, Mia MA, Zaman F, Rakin S - Sci Rep (2015)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: AlEDA Group, Department of Computer Science and Engineering, Bangladesh University of Engineering and Technology, Bangladesh.

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/.

No MeSH data available.


Representation of α helices of domain d1irqa37 in α carbon distance matrix gray-scale image.
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f2: Representation of α helices of domain d1irqa37 in α carbon distance matrix gray-scale image.

Mentions: We have carefully analyzed the gray-scale images from the α carbon distance matrices and the tertiary structures. We have observed that the α helices and the anti-parallel beta sheets appear as dark lines parallel to the diagonal dark line and parallel beta sheets appear as dark lines normal to the diagonal dark line. Beta sheets of two strips appear as one dark line normal to the diagonal; beta sheets of three strips appear as two dark lines normal to the diagonal and one dark line parallel to the diagonal. In general, for a standard beta sheet, the number of points of co-occurrence of parallel and anti-parallel diagonal lines depends on the number of strips in the beta sheets. Again, the number of single parallel lines depends on the number of standard α helices. Moreover, lengths of those lines near the diagonal region are proportional to the lengths of the α helices. The distance of the parallel lines from the diagonal dark line is proportional to the radius of the α helix. Figure 1 depicts the corresponding α carbon distance matrix of a tertiary structure of a protein with beta sheets as a gray scale image. In the gray scale image, the 7 anti-parallel dark lines near the diagonal dark line correspond to the presence of 8 beta sheets in the corresponding protein structure and the lengths of those dark lines are proportional to the lengths of the beta sheets. Figure 2 represents the gray scale image of the corresponding α carbon distance matrix of a protein tertiary structure with two alpha helices. Here in the image, the two parallel dark lines near the diagonal dark line correspond to the presence of two α helices in the protein structure and the lengths of the dark lines are proportional to the lengths of the α helices.


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

Karim R, Aziz MM, Shatabda S, Rahman MS, Mia MA, Zaman F, Rakin S - Sci Rep (2015)

Representation of α helices of domain d1irqa37 in α carbon distance matrix gray-scale image.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4543952&req=5

f2: Representation of α helices of domain d1irqa37 in α carbon distance matrix gray-scale image.
Mentions: We have carefully analyzed the gray-scale images from the α carbon distance matrices and the tertiary structures. We have observed that the α helices and the anti-parallel beta sheets appear as dark lines parallel to the diagonal dark line and parallel beta sheets appear as dark lines normal to the diagonal dark line. Beta sheets of two strips appear as one dark line normal to the diagonal; beta sheets of three strips appear as two dark lines normal to the diagonal and one dark line parallel to the diagonal. In general, for a standard beta sheet, the number of points of co-occurrence of parallel and anti-parallel diagonal lines depends on the number of strips in the beta sheets. Again, the number of single parallel lines depends on the number of standard α helices. Moreover, lengths of those lines near the diagonal region are proportional to the lengths of the α helices. The distance of the parallel lines from the diagonal dark line is proportional to the radius of the α helix. Figure 1 depicts the corresponding α carbon distance matrix of a tertiary structure of a protein with beta sheets as a gray scale image. In the gray scale image, the 7 anti-parallel dark lines near the diagonal dark line correspond to the presence of 8 beta sheets in the corresponding protein structure and the lengths of those dark lines are proportional to the lengths of the beta sheets. Figure 2 represents the gray scale image of the corresponding α carbon distance matrix of a protein tertiary structure with two alpha helices. Here in the image, the two parallel dark lines near the diagonal dark line correspond to the presence of two α helices in the protein structure and the lengths of the dark lines are proportional to the lengths of the α helices.

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: AlEDA Group, Department of Computer Science and Engineering, Bangladesh University of Engineering and Technology, Bangladesh.

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/.

No MeSH data available.