WarPP

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.

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.

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.

METALizer predicts the coordination geometry of metal ions in metalloproteins. Users can compare potential coordination geometries to those found in the examined structure. The predicted coordination geometries and the observed metal interaction distances can be interactively compared to statistics calculated based on the PDB.

PoseView automatically generates 2D diagrams of protein-ligand complexes, focusing on the interactions between protein and ligand. Interactions between molecules are estimated by an underlying interaction mode that relies on atom types and simple geometric criteria. It adheres to the conventions of chemical structure diagram generation. The quality of the resulting diagrams is comparable to manually drawn examples from books and scientific publications.

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.