EDIAscorer

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.

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.

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.

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.

Protoss is a fully automated hydrogen atom placement tool for protein-ligand complexes. It adds missing hydrogen atoms to protein structures and detects reasonable protonation states, tautomeric states, and hydrogen coordinates of both protein and ligand molecules by optimizing the hydrogen bond network.

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.