AltLocEnumerator was developed to model structural ambiguities appropriately. It handles alternate locations (AltLocs) in experimentally solved protein structures automatically. Thus, users can explore and evaluate the experimentally verified conformational space of their structure of interest. AltLocEnumerator uses a graph-based algorithm to enumerate all valid conformations that do not introduce steric clashes or chain breaks. It generates all structural variants and writes them to separate PDB files.

Publikationen

1. Gutermuth, T.; Sieg, J.; Stohn, T.; Rarey, M. (2023) Modeling with Alternate Locations in X-Ray Protein Structures . Journal of Chemical Information and Modeling, 63(8):2573-2585.

ASCONA is a fully automated command line tool for generating sequence alignments and superpositions of protein binding sites. Itisgeared to the alignment of alternative protein conformations and especially addresses the tasks of dealing with highly flexible backbone regions, detecting multiple occurrences of a binding site in oligomeric structures, and coping with arbitrary annotation inconsistencies and structural artifacts.

Publikationen

1. Bietz, S.; Rarey, M. (2015) ASCONA: Rapid Detection and Alignment of Protein Binding Site
   Conformations . Journal of Chemical Information and Modeling, 55(8):1747–1756.

Conformator is a novel conformer ensemble generator that stands out by handling macrocycles. Furthermore, it is highly accurate and robust regarding input formats and molecular geometries. With an extended set of rules for sampling torsion angles, a novel algorithm for macrocycle conformer generation, and a new clustering algorithm for assembling conformer ensembles, Conformator generates high-quality conformation ensembles.

Publikationen

1. Friedrich, N.-O.; Flachsenberg, F.; Meyder, A.; Sommer, K.; Kirchmair, J.; Rarey, M. (2019) Conformator: A Novel Method for the Generation of Conformer Ensembles . Journal of Chemical Information and Modeling, 59(2):731-742.

The Connected Subgraph Fingerprint (CSFP) is a novel fingerprint method that, unlike other methods, captures all connected subgraphs as structural features of a compound. Therefore, the CSFP captures a complete feature space and has a highly adaptive potential. Apart from surpassing common methods in standard similarity-driven virtual screening settings, the CSFP has substantial structural advantages when applied to combinatorial fragment spaces or for machine learning.

Publikationen

1. Bellmann, L.; Penner, P.; Rarey, M. (2019) Connected Subgraph Fingerprints: Representing Molecules Using Exhaustive Subgraph Enumeration . Journal of Chemical Information and Modeling, 59 (11):4625-4635.

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.

Publikationen

1. Graef, J.; Ehrt, C.; Rarey, M. (2023) Binding Site Detection Remastered: Enabling Fast, Robust, and Reliable Binding Site Detection and Descriptor Calculation with DoGSite3 . Journal of Chemical Information and Modeling, 63(10):3128-3137.

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.

Publikationen

1. Volkamer, A., Kuhn, D., Rippmann, F., Rarey, M. (2012) DoGSiteScorer: A web-server for automatic binding site prediction, analysis, and druggability assessment . Bioinformatics, 28(15):2074–2075.
2. Volkamer, A., Kuhn, D., Grombacher, T., Rippmann, F., Rarey, M. (2012) Combining Global and Local Measures for Structure-Based Druggability Predictions . Journal of Chemical Information and Modeling, 52(2):360-372.
3. Volkamer, A., Griewel, A., Grombacher, T., Rarey, M. (2010) Analyzing the Topology of Active Sites: On the Prediction of Pockets and Sub-pockets . Journal of Chemical Information and Modeling, 50(11):2041-2052.

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 EDIA_m, 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.

Publikationen

1. Meyder, A.; Nittinger, E.; Lange, G.; Klein, R.; Rarey, M. (2017) Estimating Electron Density Support for Individual Atoms and Molecular Fragments in X-ray Structures . Journal of Chemical Information and Modeling, 57(10):2437-2447.
2. Nittinger, E.; Schneider, N.; Lange, G.; Rarey, M. (2015) Evidence of Water Molecules - A Statistical Evaluation of Water Molecules Based on Electron Density . Journal of Chemical Information and Modeling, 55(4):771-783.

FTrees (Feature Trees) is a molecular descriptor based on the idea of reduced graphs. Here, the covalent structure of the essential building blocks of a molecule represents this molecule. The comparison of molecules with FTrees enables scaffold hopping because the chemical structure of the individual building blocks is of minor importance.
FTrees can be used to screen fragment spaces (FTrees-FS). The necessary double dynamic programming is a deterministic and precise method to search for similar molecules in fragment spaces. FTrees and FTrees-FS are licensable by BioSolveIT GmbH. More details can be found at https://www.biosolveit.de/wp-content/uploads/2022/03/FTrees.pdf.

Publikationen

1. Fischer, J. R., Lessel, U., Rarey, M. (2011) Improving Similarity-Driven Library Design: Customized Matching an Regio-Selective Feature Trees . Journal of Chemical Information and Modeling, 51(9):2156–2163.
2. Fischer, J.R., Lessel, U., Rarey, M. (2010) LoFT: Similarity-Driven Multi-Objective Focused Library Design . Journal of Chemical Information and Modeling, 50(1):1-21.
3. Fischer, J. R., Rarey, M. (2007) SwiFT: an index structure for reduced graph descriptors in virtual screening and clustering . Journal of Chemical Information and Modeling, 47(4):1341-53.
4. Rarey, M., Stahl, M. (2001) Similarity Searching in Large Combinatorial Chemistry Spaces . Journal of Computer-Aided Molecular Design, 15:497-520.
5. Rarey, M., Dixon, J.S. (1998) Feature Trees: A new molecular similarity measure based on tree matching . Journal of Computer-Aided Molecular Design, 12:471-490.

With Galileo, users can search for molecules in chemical fragment spaces using user-defined scoring functions. The underlying genetic algorithm directly operates in fragment spaces (so each created molecule is from the space). An external scoring function can be integrated via a system call. The tool supports pharmacophore searches based on Phariety. It is the first 3D search engine for fragment spaces.

Publikationen

1. Meyenburg, C.; Dolfus, U.; Briem, H.; Rarey, M. (2022) Galileo: Three‑dimensional searching in large combinatorial fragment spaces on the example of pharmacophores . Journal of Computer-Aided Molecular Design, 37:1-16.

GeoMine enables the automated mining of protein-ligand binding sites. Based on individually designed queries, users can search for spatial interaction patterns in huge collections of protein-ligand complexes and binding pockets. The regularly updated GeoMine database relies on the free database systems SQLite and PostgreSQL. It supports radius-based pockets (based on ligands and predicted pockets (based on DoGSite3) for query generation. The query management is based on XML (for the REST service) or JSON in the GUI mode. Its output consists of the query-based superpositions of the matched binding sites and statistics on matching points, distances, and angles.

Publikationen

1. Diedrich, K.; Ehrt, C.; Graef, J.; Poppinga, M.; Ritter, N.; Rarey, M. (2024) User-Centric Design of a 3D Search Interface for Protein-Ligand Complexes . Journal of Computer-Aided Molecular Design, 38(1):23.
2. Graef, J.; Ehrt, C.; Diedrich, K.; Poppinga, M.; Ritter, N.; Rarey, M. (2021) Searching Geometric Patterns in Protein Binding Sites and Their Application to Data Mining in Protein Kinase Structures . Journal of Medicinal Chemistry, 65(2):1384-1395.
3. Diedrich, K.; Graef, J.; Schöning-Stierand, K.; Rarey, M. (2020) GeoMine: interactive pattern mining of protein–ligand interfaces in the Protein Data Bank . Bioinformatics, 37(3):424-425.

HYDE was designed to offer an integrated description of desolvation, hydrophobic effect, and hydrogen bonding. It assesses protein-ligand complexes energetically. The HYDE function was parameterized based on experimentally determined water-octanol partition coefficients (logP values). It estimates the strength of hydrogen bonds, desolvation, and hydrophobic effects in a consistent manner. The patented HYDE technology was developed in cooperation with Bayer CropScience and BioSolveIT GmbH. More details can be found at https://www.biosolveit.de/wp-content/uploads/2025/01/HYDE_2025.pdf.

Publikationen

1. Schneider, N., Klein, R., Lange, G., Rarey, M. (2012) Nearly no Scoring Function without a Hansch-Analysis . Molecular Informatics, 31(6-7):503–507.
2. Schneider, N., Hindle, S., Lange, G., Klein, R., Albrecht, J., Briem, H., Beyer, K., Claußen, H., Gastreich, M., Lemmen, C., Rarey, M. (2011) Substantial improvements in large-scale redocking and screening using the novel HYDE scoring function . Journal of Computer-Aided Molecular Design, 26(6):701-723.
3. Reulecke, I., Lange, G., Albrecht, J., Klein, R., Rarey, M. (2008) Towards an integrated description of hydrogen bonding and dehydration: II. Reducing false positives in virtual screening using the HYDE scoring function . ChemMedChem, 3(6):885-897.

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.

Publikationen

1. Flachsenberg, F.; Ehrt, C.; Gutermuth, T.; Rarey, M. (2023) Redocking the PDB . Journal of Chemical Information and Modeling, 64(2):219-237.
2. Flachsenberg, F.; Rarey, M. (2021) LSLOpt: An open‐source implementation of the step‐length controlled LSL‐BFGS algorithm . Journal of Computational Chemistry, 42(15):1095-1100.
3. Flachsenberg, F.; Meyder, A.; Sommer, K.; Penner, P.; Rarey, M. (2020) A Consistent Scheme for Gradient-Based Optimization of Protein–Ligand Poses . Journal of Chemical Information and Modeling, 60(12):6502–6522.

JAMDAscorer post-optimizes protein-ligand complexes into precise local energy minima with the new JAMDA scoring function. This new empirical scoring function can be used with gradient-based optimizers. By combining it with the optimizer LSL-BFGS, fast convergence, locality, and the precise detection of local minima are guaranteed. JAMDAscorer considers hydrogen bond geometries, hydrophobic contacts, clashes, and torsion angles. Therefore, it balances the most relevant terms in protein-ligand scoring functions.

Publikationen

1. Flachsenberg, F.; Rarey, M. (2021) LSLOpt: An open‐source implementation of the step‐length controlled LSL‐BFGS algorithm . Journal of Computational Chemistry, 42(15):1095-1100.
2. Flachsenberg, F.; Meyder, A.; Sommer, K.; Penner, P.; Rarey, M. (2020) A Consistent Scheme for Gradient-Based Optimization of Protein–Ligand Poses . Journal of Chemical Information and Modeling, 60(12):6502–6522.

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.

Publikationen

1. Pletzer-Zelgert, J.; Ehrt, C.; Fender, I.; Griewel, A.; Flachsenberg, F.; Klebe, G.; Rarey, M. (2023) LifeSoaks: a tool for analyzing solvent channels in protein crystals and obstacles for soaking experiments . Biological Crystallography, 79(9):837-856.

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.

Publikationen

1. Schöning-Stierand, K.; Diedrich, K.; Fährrolfes, R.; Flachsenberg, F.; Meyder, A.; Nittinger, E.; Steinegger, R.; Rarey, M. (2020) ProteinsPlus: interactive analysis of protein-ligand binding interfaces . Nucleic Acids Research, 48(W1):W48-W53.

MicroMiner assists in identifying single-residue substitutions in protein structure databases. It searches protein residue environments with local sequence and structural similarity based on the SIENA methodology. Users can search for structural mutation in the entire PDB, their in-house structure collection, or (subsets of) the AlphaFold Database. They can use the method to explore the mutation landscape of proteins with experimental or predicted structures. MicroMiner can be applied to single domains or even protein-protein or protein-ligand interfaces. Several filter options to simplify downstream analysis are available.

Publikationen

1. Sieg, J.; Rarey, M. (2023) Searching similar local 3D micro-environments in protein structure databases with MicroMiner . Briefings in Bioinformatics, 24(6):bbad357.

MONA is an interactive tool to prepare and visualize large small-molecule datasets. A set-centric workflow allows intuitively handling hundreds of thousands of molecules. The method builds upon the robust framework NAOMI. Users can perform basic cheminformatics tasks such as analyzing, filtering, and converting molecular files with high efficiency. 

Publikationen

1. Matthias Hilbig;
   Matthias Rarey (2015) MONA 2: A Light Cheminformatics Platform for Interactive
   Compound Library Processing . Journal of Chemical Information and Modeling, 55(10):2071–2078.
2. Hilbig, M.; Urbaczek, S.; Groth, I.; Heuser, S.; Rarey, M. (2013) MONA - Interactive manipulation of molecule collections . Journal of Cheminformatics, 5 (38)

Phariety is a command-line tool for virtual screening with a pharmacophore model as a query. It returns all molecules mapping to the pharmacophore query and a score based on their compatibility with the query model. The hit molecules are superposed on the query. The output file is empty if the input molecules do not match the query pharmacophore. It also contains the calculated scores of the matching structures. 

Publikationen

1. Meyenburg, C.; Dolfus, U.; Briem, H.; Rarey, M. (2022) Galileo: Three‑dimensional searching in large combinatorial fragment spaces on the example of pharmacophores . Journal of Computer-Aided Molecular Design, 37:1-16.

PiMine enables comparisons of protein-protein interfaces. The method screens GeoMine databases generated for known interfaces for similarities based on physicochemical and shape correspondences. It automatically detects the interfaces for a protein complex of interest. Alternatively, users can use a single chain and predicted interface as input. The scoring function can assess single-chain similarities and similarities between both chains of the matched interfaces. The tool’s output consists of a list of similarity scores for all database interfaces, a binned similarity distribution, and (optionally) alignments of the matching interfaces. 

Publikationen

1. Graef, J.; Ehrt, C.; Reim, T.; Rarey, M. (2024) Database-Driven Identification of Structurally Similar Protein-Protein Interfaces . Journal of Chemical Information and Modeling, 64(8):3332-3349.

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.

Publikationen

1. Diedrich, K.; Krause, B.; Berg, O.; Rarey, M. (2023) PoseEdit: enhanced ligand binding mode communication by interactive 2D diagrams . Journal of Computer-Aided Molecular Design, 37:491–503.

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.

Publikationen

1. Stierand, K., Rarey, M. (2010) Drawing the PDB - Protein-Ligand Complexes in two Dimensions . Medicinal Chemistry Letters, 1(9):540-545.
2. Stierand, K., Rarey, M. (2007) From Modeling to Medicinal Chemistry: Automatic generation of two-dimensional complex diagrams . ChemMedChem, 2(6):853-860.
3. Stierand, K., Maaß, P. C., Rarey, M. (2006) Molecular Complexes at a Glance: Automated Generation of two-dimensional Complex Diagrams . Bioinformatics, 22(14):1710-1716.

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.

Publikationen

1. Bietz, S.; Urbaczek, S.; Schulz, B.; Rarey, M. (2014) Protoss: a holistic approach to predict tautomers and protonation states in protein-ligand complexes . Journal of Cheminformatics, 6(12):1-12.
2. Lippert, T., Rarey, M. (2009) Fast automated placement of polar hydrogen atoms in protein-ligand complexes . Journal of Cheminformatics, 1(13)

The tool ReactionViewer visualizes generic reaction patterns. It creates an easily interpretable image for generic reaction patterns based on the SMARTSview technology. ReactiionViewer supports Reaction SMILES, Reaction SMARTS, and SMIRKS. The IUPAC’s Compendium of Chemical Terminology for reaction equations inspired the depiction style. Users can save the reaction depictions in PNG, SVG, and PDF format. This feature enables the single-command conversion of large reaction pattern collections to single PDF documents.

Publikationen

1. Dolfus, U.; Briem, H.; Rarey, M. (2022) Visualizing Generic Reaction Patterns . Journal of Chemical Information and Modeling, 62(19):4680-4689.

ReCore is an index-based software for re-scaffolding. Based on a biologically active molecule, part of the molecule can be interactively marked and replaced by geometrically fitting fragments. ReCore also enables the consideration of pharmacophoric constraints. Through its connection to the Cambridge Structure Database (CSD), low-energy conformers can be generated. The tool can be operated nearly completely interactively due to the indexing.

Publikationen

1. Maaß, P.; Schulz-Gasch, T.; Stahl, M.; Rarey, M. (2007) Recore: A fast and Versatile Method for Scaffold Hopping Based on Small Molecule Crystal Structure Conformations . Journal of Chemical Information and Modeling, 47(2):390-399.

REMUS enables searches for 3D similarity within small and medium-sized compound collections. It calculates molecular similarity based on classical Gaussian (colored by pharmacophoric properties) shape descriptions; Handle molecular. Molecules can be treated as flexible by automatically generated conformers (Conformator). The resulting conformers are finetuned in the alignment step. REMUS employs a brand-new step-limited BFGS numerical optimizer. Users can visually explore molecular alignments and perform them semi-automated by RMSD-fit of user-specified atom pairs.

SIENA is a software pipeline enabling the fully automated construction of protein structure ensembles from the PDB. Starting with a single query structure, all binding sites with high sequence similarity are extracted from the PDB, aligned, and superimposed. SIENA also handles complicated cases, such as comparing binding sites at protein domain interfaces or within multimeric proteins.

Publikationen

1. Bietz, S.; Rarey, M. (2016) SIENA: Efficient Compilation of Selective Protein Binding Site Ensembles . Journal of Chemical Information and Modeling, 56(1):248-259.

SiteMine was developed to compare small molecule binding sites in large databases and calculate their physicochemical and shape similarity. Users can screen large GeoMine databases of ligand-based and/or predicted binding sites for similar sites to a fully automatically modeled query site. Users can create databases of individual experimental or predicted structures. A prefiltering cascade based on several pocket properties and subsets of structure identifiers reduces the number of relevant pockets before screening. Similarity calculations include two scoring functions that account for the physicochemical and shape similarities of the respective binding sites. SiteMine runs take approx. three minutes on a database of 10,000 pockets.

Publikationen

1. Reim, T.; Ehrt, C.; Graef, J.; Günther, S.; Meents; Rarey, M. (2024) SiteMine: Large-scale binding site similarity searching in protein structure databases . Archiv der Pharmazie, 357(5)

With SMARTScompare, we provide a tool to calculate the relationship between SMARTS patterns. SMARTS is the quasi-standard for describing filter collections used, for example, to exclude unwanted compounds from screening collections.SMARTScompare automatically detects relationships between two patterns. In this way, patterns can be distinguished by generality and similarity. 

Publikationen

1. Ehmki, E.S.R.; Schmidt, R.; Ohm, F.; Rarey, M. (2019) Comparing Molecular Patterns Using the Example of SMARTS: Applications and Filter Collection Analysis . Journal of Chemical Information and Modeling, 59(6):2572-2586.
2. Schmidt, R.; Ehmki, E.S.R.; Ohm, F.; Ehrlich, H.-C.; Mashychev, A.; Rarey, M. (2019) Comparing Molecular Patterns Using the Example of SMARTS: Theory and Algorithms . Journal of Chemical Information and Modeling, 59(6):2560-2571.

SMARTScompareViewer and the accompanying SMARTScompare command-line tool are the first algorithmic solutions for chemical pattern analysis and comparisons, especially designed for the SMARTS language. SMARTScompare determines similarity and subset relationships between SMARTS patterns

Publikationen

1. Ehmki, E.S.R.; Schmidt, R.; Ohm, F.; Rarey, M. (2019) Comparing Molecular Patterns Using the Example of SMARTS: Applications and Filter Collection Analysis . Journal of Chemical Information and Modeling, 59(6):2572-2586.
2. Schmidt, R.; Ehmki, E.S.R.; Ohm, F.; Ehrlich, H.-C.; Mashychev, A.; Rarey, M. (2019) Comparing Molecular Patterns Using the Example of SMARTS: Theory and Algorithms . Journal of Chemical Information and Modeling, 59(6):2560-2571.
3. Schomburg, K.; Ehrlich, H.-C.; Stierand, K.; Rarey, M. (2010) From Structure Diagrams to Visual Chemical Patterns . Journal of Chemical Information and Modeling, 50(9):1529-1535.

SMARTSeditor is a graphical editing tool for generic chemical patterns. Based on the SMARTS language, chemical patterns can be created and edited interactively, similar to molecule editing in a chemical structure editor. The visualization of patterns builds on the visualization concept of SMARTSviewer. SMARTSeditor supports editing of given SMARTS patterns or editing of chemical patterns without knowledge of the SMARTS language from scratch. It supports logic combinations as well as atom environment definitions. The generated pattern is converted into a SMARTS string for any application requiring a SMARTS pattern, e.g., for filtering molecular databases.
The tool SMARTSminer, which automatically generates discriminating patterns for two given sets of molecules, is also integrated into SMARTSeditor. With this feature, a user can load molecule sets as positive (molecules to be matched) and negative (molecules not to be matched) sets and immediately see the matching results highlighted in the positive structures.

Publikationen

1. Bietz, S.; Schomburg, K. T.; Hilbig, M.; Rarey, M. (2015) Discriminative Chemical Patterns: Automatic and Interactive Design . Journal of Chemical Information and Modeling, 55(8):1535–1546.
2. Schomburg, K., Wetzer, L., Rarey, M. (2013) Interactive design of generic chemical patterns . Drug Discovery Today, 13:1-8.

SMARTSminer was developed to generate SMARTS patterns that distinguish molecules from two different sets. It can, for example, create SMARTS patterns that match active molecules of a target of interest but do not match inactive molecules. Besides screening, the SMARTSminer technology can also provide valuable insights into typical patterns of frequent hitters or elucidate differences between sets of molecules binding to different target types.

Publikationen

1. Bietz, S.; Schomburg, K. T.; Hilbig, M.; Rarey, M. (2015) Discriminative Chemical Patterns: Automatic and Interactive Design . Journal of Chemical Information and Modeling, 55(8):1535–1546.

SpaceCompare is a novel tool for comparing and analyzing ultra-large combinatorial chemical spaces. For the first time, users can compare trillion-sized chemical spaces using the combinatorial algorithmic approach of SpaceCompare.

Publikationen

1. Bellmann, L.; Penner, P.; Gastreich, M.; Rarey, M. (2022) Comparison of Combinatorial Fragment Spaces and Its Application to Ultralarge Make-on-Demand Compound Catalogs . Journal of Chemical Information and Modeling, 62(3):553-566.

SpaceLight is a novel search method for similarity-driven virtual screening in large combinatorial fragment spaces with topological fingerprints. It utilizes the well-known ECFP and the Connected Subgraph Fingerprint (CSFP) to describe molecular similarity. In contrast to existing workflows based on fingerprint methods, the SpaceLight approach exploits the combinatorial nature of fragment spaces. Consequently, it can conduct similarity searches considering billions of compounds within seconds on a standard computer. Furthermore, users can retrieve scaffold-forming fragments to identify reaction routes for compounds. Using this feature, they can generate custom fragment 

Publikationen

1. Bellmann, L.; Penner, P.; Rarey, M. (2021) Topological Similarity Search in Large Combinatorial Fragment Spaces . Journal of Chemical Information and Modeling, 61(1):238-251.

SpaceMACS is a novel search method for similarity-driven virtual screening in large combinatorial fragment spaces. SpaceMACS identifies maximum common connected induced substructures between a query and all products of a fragment space, e.g.,  a commercial make-on-demand library. SpaceMACS heavily exploits the fragment structure of those spaces. Therefore, users can screen billions or even trillions of compounds within seconds to minutes on standard computers. Its runtime depends on the number of results and the size of the fragment space representation. The runtime is commonly independent of the number of compounds represented. To explore fragment spaces, the SpaceMACS tool supports interactive command-line sessions and the processing of multiple queries, avoiding the need to load the space for every query separately.

Publikationen

1. Schmidt, R.; Klein, R.; Rarey, M. (2021) Maximum Common Substructure Searching in Combinatorial Make-on-Demand Compound Spaces . Journal of Chemical Information and Modeling, 62(9):2133–2150.

SpaceProp was designed as a telescope for chemical fragment spaces. It calculates exact chemical property distributions for ultra-large chemical spaces (heavy atom count, molecular weight, clogP, number of hydrogen bond donors and acceptors, topological polar surface area, number of rotatable bonds, number of molecules containing user-defined molecular patterns as defined by SMARTS patterns). Users will also get example molecules for every value or pattern.

Publikationen

1. Lübbers, J.; Lessel, U.; Rarey, M. (2024) Enhanced Calculation of Property Distributions in Chemical Fragment Spaces . Journal of Chemical Information and Modeling, 64(6):2008-2020.
2. Bellmann, L.; Klein, R.; Rarey, M. (2022) Calculating and Optimizing Physicochemical Property Distributions of Large Combinatorial Fragment Spaces . Journal of Chemical Information and Modeling, 62(11):2800-2810.

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.

Publikationen

1. Meyder, A.; Kampen, S.; Sieg, J.; Fährrolfes, R.; Friedrich, N.-O.; Flachsenberg, F.; Rarey, M. (2018) StructureProfiler: An All-In-One Tool for 3D Protein Structure Profiling . Bioinformatics, 35(5):874-876.

Synthesia offers full modification control over retrosynthetic routes for optimizing lead structures by generating structural analogues in a synthesis-aware process. It integrates the preservation of the synthesizability of the target structure into the lead structure modification process. It creates structural diversity for a lead structure that matches user-defined molecular properties without losing the applicability of a particular synthetic pathway. Thereby, it maximizes synthetic efficiency and provides an initial estimate of the effort for synthesizing the entire series.

Publikationen

1. Dolfus, U.; Briem, H.; Rarey, M. (2021) Synthesis-Aware Generation of Structural Analogues . Journal of Chemical Information and Modeling, 62(15):3565-3576.

TorsionAnalyzer enables the analysis and inspection of torsion angles in small molecules. The tool is based on a collection of SMARTS patterns and rules derived from collections of high-quality crystal structures. The rotatable bonds of a molecule are assigned to three categories (frequent, moderately frequent, infrequent) and colored accordingly. Users can evaluate large quantities of molecules with a given torsion library. The result table contains each torsion bond along with its corresponding torsion rule, angle, observed frequency, and quality category. The software displays a molecule in a conformation of interest and highlights bonds that exhibit geometrically unusual torsion angles. The software was developed in collaboration with F. Hoffmann-La Roche Ltd. in Basel and the ZBH - Center for Bioinformatics. 
With TorsionAnalyzer, you can visually inspect the torsion angles of a given molecule and compare the angles to those observed in the Cambridge Structural Database (CSD) or Protein Data Bank (PDB) or recalculate angle frequencies based on your own data set.
TorsionPatternMiner is an all-in-one command-line tool to populate torsion angle statistics for SMARTS torsion patterns for selected libraries of molecular conformations. SMARTScompare enables in-depth SMARTS pattern analysis. Users can apply the resulting torsion rules in many conformer generators such as Conformator, RDKit, or OMEGA.

Publikationen

1. Penner, P.; Guba, W.; Schmidt, R.; Meyder, A.; Stahl, M.; Rarey, M. (2022) The Torsion Library: Semiautomated Improvement of Torsion Rules with SMARTScompare . Journal of Chemical Information and Modeling, 62(7):1644-1653.
2. Guba, W.; Meyder, A.; Rarey, M.; Hert, J. (2016) Torsion Library Reloaded: A New Version of Expert-Derived SMARTS rules
   for Assessing Conformations of Small Molecules . Journal of Chemical Information and Modeling, 56(1):1-5.
3. Schärfer, C.; Schulz-Gasch, T.; Ehrlich, H.-C.; Guba, W.; Rarey, M.; Stahl, M. (2013) Torsion Angle Preferences in Drug-like Chemical Space: A Comprehensive Guide . Journal of Medicinal Chemistry, 56(6):2016-2028.

UNICON is a command-line tool to cope with common cheminformatics tasks. The functionality of UNICON ranges from file conversion between standard formats SDF, MOL2, SMILES, and PDB via the generation of 2D structure coordinates and 3D structures to the enumeration of tautomeric forms, protonation states and conformer ensembles.

Publikationen

1. Sommer, K.; Friedrich, N.-O.; Bietz, S.; Hilbig, M.; Inhester, T.; Rarey, M: (2016) UNICON: A powerful and easy-to-use compound library converter . Journal of Chemical Information and Modeling, 56(6):1105–1111.

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.

Publikationen

1. Nittinger, E.; Flachsenberg, F.; Bietz, S.; Lange, G.; Klein, R.; Rarey, M. (2018) Placement of Water Molecules in Protein Structures: From Large-Scale Evaluations to Single-Case Examples . Journal of Chemical Information and Modeling, 58(8):1625-1637.

The fragment space exhaustive enumeration system (FSees) is an efficient method to enumerate all molecules within a specific molecular subspace. This chemical space is described as a fragment space constrained by user-defined physicochemical properties. The FSees algorithm uses file-based data structures to overcome the limitation of the computer's main memory. Thus, it enables enumerating large chemical spaces. The resulting chemical library can be used as a starting point for computational lead-finding technologies, like similarity searching, pharmacophore mapping, docking, or virtual screening.

Publikationen

1. Lauck, F.; Rarey, M. (2016) FSees: Customized Enumeration of Chemical Subspaces with Limited Main Memory Consumption . Journal of Chemical Information and Modeling, 56(9):1641-1653.

iRAISE is an inverse screening tool based on the RAISE (RApid Index-based Screening Engine) technology. RAISE employs triangle descriptors of ligands and protein binding sites, enabling a highly efficient screening of large datasets. The triangle-descriptor abstraction of proteins and molecules allows fast, non-sequential screening of thousands of target structures. iRAISE enables the search for potential targets for a small molecule binder to, for example, predict off-targets and/or polypharmacology. Scoring measures applied for selectivity considering the reference ligand and coverages of the pocket and the ligand pose support inter-protein ranking.

Publikationen

1. Schomburg, K.T.; Bietz, S.; Briem, H.; Henzler, A.M.; Urbaczek, S.; Rarey, M. (2014) Facing the Challenges of Structure-Based Target Prediction by Inverse Virtual Screening . Journal of Chemical Information and Modeling, 54(6):1676-1686.

NAOMInext is a software tool supporting medicinal chemists during hit-to-lead optimization. Starting with a co-crystallized small fragment, synthetically feasible lead compounds are generated directly within the protein’s binding site. Thus, the software implicitly performs target-focused library design.

The NAOMInext software package has an easy-to-use graphical user interface providing access to robust organic synthesis steps. The 3D viewer allows for inspecting available extension vectors. Beyond that, users can easily define constraints to guide the growing process into a specific sub-pocket.

Publikationen

1. Sommer, K.; Flachsenberg, F.; Rarey, M. (2018) NAOMInext - Synthetically feasible fragment growing in a structure-based design context . European Journal of Medicinal Chemistry, 163:747-762.

NAOMInova enables the geometrical and chemical analysis of atoms surrounding a user-defined structure of interest. Substructures can be searched based on a user-defined set of protein structures. Users can also visualize the distribution of partner points. Two visualization options are available: the “set” visualization, i.e., the partner points surrounding the substructure, and the “pocket” visualization, i.e., the transformation of all partner points surrounding the substructure into a suitable binding site of interest. Diverse geometric - distance, angles, resolution - and chemical - atom type, location, amino acid - properties are available for more detailed analysis by filtering the results. The original complex is stored for each partner point, enabling an easy evaluation to find whether this point is of interest.

Publikationen

1. Inhester, T.; Nittinger, E.; Sommer, K.; Schmidt, P.; Bietz, S.; Rarey, M. (2017) NAOMInova: Interactive Geometric Analysis of Noncovalent Interactions in Macromolecular Structures . Journal of Chemical Information and Modeling, 57(9):2132–2142.
2. Nittinger, E.; Inhester, T.; Bietz, S.; Meyder, A.; Schomburg, K.T.; Lange, G.; Klein, R.; Rarey, M. (2017) Large-Scale Analysis of Hydrogen Bond Interaction Patterns in Protein-Ligand Interfaces . Journal of Medicinal Chemistry, 60(10):4245-4257.

PELIKAN is a software tool that enables rapidly searching spatial interaction patterns in large collections of protein-ligand complexes. Data from protein-ligand complexes is stored in an SQLite database for different search processes.

The PELIKAN software package comes with a graphical user interface, providing dialogs to build SQLite databases from any set of protein-ligand complexes and allowing for conveniently constructing 3D queries starting from a protein-ligand interface of interest or designing from scratch. The results of a search are shown in a 3D viewer.

Publikationen

1. Inhester, T.; Bietz, S.; Hilbig, M.; Schmidt, R.; Rarey, M. (2017) Index-based Searching of Interaction Patterns in Large Collections of Protein-Ligand Interfaces . Journal of Chemical Information and Modeling, 57(2):148-158.

NAOMI was a command-line tool to consistently convert different commonly used molecule file formats (SDF, SMILES, MOL2, PDB). It is based on a robust chemical model developed to correctly describe organic molecules, which is highly relevant in drug discovery. Furthermore, NAOMI checks for the chemical validity of molecules and calculates coordinates for hydrogen atoms.

In June 2016, NAOMI was replaced by our new, highly performant universal converter UNICON.

Publikationen

1. Urbaczek, S., Kolodzik, A., Rarey, M. (2014) The Valence State Combination Model: A generic framework for handling tautomers and protonation states . Journal of Chemical Information and Modeling, 54(3):756-766.
2. Urbaczek, S., Kolodzik, A., Heuser, S., Groth, I., Rarey, M. (2013) Reading PDB: Perception of Molecules from 3D Atomic Coordinates . Journal of Chemical Information and Modeling, 53(1):76-87.
3. Urbaczek, S., Kolodzik, A., Fischer, J. R., Lippert, T., Heuser, S., Schulz-Gasch, T., Rarey, M. (2011) NAOMI: On the Almost Trivial Task of Reading Molecules
   from Different File formats . Journal of Chemical Information and Modeling, 51(12):3199-3207.