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J Comput Biol. 2007 Apr;14(3):285-99.

Discovery of similar regions on protein surfaces.

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Department of Statistics, Purdue University, West Lafayette, Indiana, USA.


Discovery of a similar region on two protein surfaces can lead to important inference about the functional role or molecular interaction of this region for one of the proteins if such information is available for the other. We propose a new characterization of protein surfaces based on a spin-image representation of the surfaces that facilitates the simultaneous search of the entire surface of each of two proteins for a matching region. For a surface point, we introduce spin-image profiles that are related to the degree of exposure of the point to identify structurally equivalent surface regions in two proteins. Unlike some related methods, we do not assume that a known fixed region of one of the protein surfaces is to be matched on the other protein surface. Rather, we search for the largest similar regions on each of the two surfaces. In spite of the fact that this approach is entirely geometric and no use is made of physicochemical properties of the protein surfaces or fold information, it is effective in identifying similar regions on both surfaces even when the region corresponds to a binding site on one of the proteins. The discovery of similar regions on two or more proteins also has implications for drug design and pharmacophore identification. We present experimental results from datasets of more than 50 protein surfaces.

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