DoGSite3
DoGSite3 was developed for predicting robust and reliable small molecule binding sites and computing their geometrical and chemical descriptors. It is based on the grid-based DoGSite algorithm for predicting pockets and their sub-pockets. The new tool is largely rotation- and translation-invariant due to a normalization procedure before binding site prediction. Known ligands in the structure can be used to bias the grid by sufficiently buried ligand fragments. The output encompasses novel chemical binding site descriptors considering solvent accessibility. Compared to its predecessor, it shows increased robustness through comprehensive parameter optimization. DoGSite3 runs finish within seconds.
Key benefits
Fully automated detection of binding pockets and sub-pockets
Requires only the three-dimensional protein structure
Calculates geometric and physicochemical pocket descriptors
Robust due to largely rotation- and translation-invariant prediction
Much faster than its predecessor DoGSiteScorer
Applications
Identification of potential small-molecule binding sites
Selection of binding sites for docking and virtual screening
Support for target assessment in early-stage drug discovery
Structural characterization of protein cavities
Intended use
DoGSite3 is intended for structural biologists, medicinal chemists,
computational chemists, and researchers in structure-based drug discovery
who need to identify and prioritize potential ligand-binding pockets.
It is particularly suited for users who want an automated, structure-based
assessment of pocket geometry and physicochemical properties.
Contact:
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