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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.

PoseEdit 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 model that relies on atom types and simple geometric criteria. The structure mining tool GeoMine also uses this model to describe binding sites. In addition, users can manipulate the diagrams by translating, rotating, mirroring parts of the structure, adding additional interactions, or removing them. Furthermore, users can add individual labels or adjust available labels. Users can download the final 2D diagrams for a binding site of interest in JSON or SVG format.

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.

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.

HyPPI classifies a protein-protein complex based on its interaction type into permanent, transient, or crystal artifact. Permanent protein-protein complexes are only stable in their complexed state. Their subunits would denature upon dissociation of the protein-protein complex. Transient protein-protein complexes are stable in the complexed as well as in the monomeric form, depending on the necessary function of the complex. Crystal artifacts have no biological function and are artificially formed during the crystallization process. The discrimination is performed using two characteristics of the protein-protein complex, the hydrophobicity of the interface (ΔGhydrophobic) and the quotient of interface area ratios (IF-quotient). The IF-quotient considers whether the protein-protein interface is symmetric.