DoGSite3

WarPP predicts the position and orientation of water molecules in small-molecule binding sites. It places and scores water molecules in binding sites of crystallographic structures based on EDIAscorer results and interaction geometries as known from experimentally solved protein structures. WarPP was validated on a high-quality set of 1,500 protein-ligand complexes, containing 20,000 crystallographically observed water molecules. It is sufficiently fast for high-throughput analyses. It correctly places water molecules in approx. 80% of the cases. Users can export the predictions as PDB files for, e.g., molecular docking with JAMDA.

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.

JAMDA enables the preparation of individual protein structures and the docking of small molecules in preprocessed binding sites of choice. JAMDA simplifies the process of protein-ligand docking by automatic preprocessing protocols for the protein and binding sites of interest. The JAMDAscore scoring function retrieved 75% of the native poses in the three highest-ranked solutions for high-quality protein-ligand complexes with default settings. Individual configurations for protein preparation are available, e.g., considering protein ensembles, relevant binding site water molecules, or cofactors. A user-defined number of input conformations for the ligands of interest can be generated fully automated using Conformator. Alternatively, users can also provide externally prepared ligand conformers.

LifeSoaks was designed to find solvent channels in macromolecular structures solved by X-ray crystallography. It predicts their accessibility by molecules through an automated annotation of so-called bottleneck radii. It simplifies the process of manually checking a crystal structure for solvent channels. Bottleneck radii can be calculated for solvent channels and small molecule binding sites. The tool is ideally suited for channel analyses before the actual soaking experiments to select the most promising experimental conditions and crystal forms. LifeSoaks runs fully automated and will finish within seconds to minutes for moderately sized crystals.

Three-dimensional protein structures play a vital role in drug design. Structure-based design necessitates an in-depth examination of the available quality data before using the structure in computational experiments and for method evaluation. StructureProfiler assists in automatically profiling sets of protein-ligand complex structures based on multiple quality indicators, ranging from model characteristics, e.g., the R factor, and active site features, e.g., bond length deviations, to ligand properties such as electron density support and the validity of torsion angles.

The electron density score for individual atoms (EDIA) quantifies the electron density fit of each atom in a crystallographically resolved structure. Multiple EDIA values can be combined using the power mean to compute the EDIAm, i.e., the electron density score for a group of several atoms. It enables users to score a set of atoms, such as a ligand, a residue, or an active site.