DoGSiteScorer

Overview

DoGSiteScorer is a grid-based automated pocket detection and analysis tool. It applies a Difference of Gaussian filter to detect potential binding pockets and splits them into sub-pockets. The method solely uses the 3D structure of the protein. Global properties, describing the size, shape, and chemical features of the predicted (sub-)pockets, are calculated. Per default, a simple druggability score based on a linear combination of the three descriptors describing volume, hydrophobicity, and enclosure is provided for each (sub-)pocket. Furthermore, a subset of meaningful descriptors is incorporated in a support vector machine (libsvm) to predict the (sub-)pocket druggability score (values are between zero and one). The higher the score, the more druggable the pocket is estimated to be.

Software Availability

We are offering DoGSiteScorer as part of our ProteinsPlus web service. Please visit https://proteins.plus, upload your protein, and choose DoGSiteScorer.
A standalone version of DoGSiteScorer can be licensed at https://www.biosolveit.de/academic-drug-discovery/#DoGSiteScorer

References

Volkamer, A.; Kuhn, D.; Grombacher, T.; Rippmann, F.; Rarey, M. Combining Global and Local Measures for Structure-Based Druggability Predictions. J Chem Inf Model 2012, 52 (2), 360-372. DOI: https://doi.org/10.1021/ci200454v