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Figure 2 | Journal of Cheminformatics

Figure 2

From: Improving protein-ligand binding site prediction accuracy by classification of inner pocket points using local features

Figure 2

Visualization of inner pocket points.(a) Displayed is protein 1AZM from DT198 dataset bound to one ligand (magenta). Fpocket predicted 13 pockets that are depicted as colored areas on the protein surface. To rank these pockets, the protein was first covered with evenly spaced Connolly surface points (probe radius 1.6 Å) and only the points adjacent to one of the pockets were retained. Color of the points reflects their ligandability (green = 0…red = 0.7) predicted by Random Forest classifier. PRANK algorithm rescores pockets according to the cumulative ligandability of their corresponding points. Note that there are two clusters of ligandable points in the picture, one located in the upper dark-blue pocket and the other in the light-blue pocket in the middle. The light-blue pocket, which is in fact the true binding site, contains more ligandable points and therefore will be ranked higher. (b) Detailed view of the binding site with ligand and inner pocket points.

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