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International Journal of Biomedical Imaging
Volume 2011, Article ID 918978, 15 pages
Research Article

Protein Surface Characterization Using an Invariant Descriptor

1Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV 26506, USA
2Department of Pathology, Anatomy and Cell Biology Jefferson Medical College, Thomas Jefferson University, Philadelphia, PA 19107, USA

Received 6 July 2011; Accepted 14 August 2011

Academic Editor: Guowei Wei

Copyright © 2011 Zainab Abu Deeb et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Aim. To develop a new invariant descriptor for the characterization of protein surfaces, suitable for various analysis tasks, such as protein functional classification, and search and retrieval of protein surfaces over a large database. Methods. We start with a local descriptor of selected circular patches on the protein surface. The descriptor records the distance distribution between the central residue and the residues within the patch, keeping track of the number of particular pairwise residue cooccurrences in the patch. A global descriptor for the entire protein surface is then constructed by combining information from the local descriptors. Our method is novel in its focus on residue-specific distance distributions, and the use of residue-distance co-occurrences as the basis for the proposed protein surface descriptors. Results. Results are presented for protein classification and for retrieval for three protein families. For the three families, we obtained an area under the curve for precision and recall ranging from 0.6494 (without residue co-occurrences) to 0.6683 (with residue co-occurrences). Large-scale screening using two other protein families placed related family members at the top of the rank, with a number of uncharacterized proteins also retrieved. Comparative results with other proposed methods are included.