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{ "count": 30662, "next": "?page=2", "previous": null, "list": [ { "name": "FlashDeconv", "description": "Ultra-fast spatial transcriptomics deconvolution using structure-preserving randomized sketching. 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(CDK) v2.0: atom typing, depiction, molecular formulas, and substructure searching", "abstract": "", "date": "2017-06-06T00:00:00Z", "citationCount": 381, "authors": [], "journal": "Journal of Cheminformatics" } }, { "doi": "10.1021/ci025584y", "pmid": "12653513", "pmcid": "PMC4901983", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "The Chemistry Development Kit (CDK): An open-source Java library for chemo- and bioinformatics", "abstract": "", "date": "2003-01-01T00:00:00Z", "citationCount": 935, "authors": [], "journal": "Journal of Chemical Information and Computer Sciences" } }, { "doi": "10.2174/138161206777585274", "pmid": "16796559", "pmcid": null, "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "Recent developments of the Chemistry Development Kit (CDK) - An open-source Java library for chemo- and bioinformatics", "abstract": "", "date": "2006-06-01T00:00:00Z", "citationCount": 445, "authors": [], "journal": "Current Pharmaceutical Design" } } ], "credit": [ { "name": "Christoph Steinbeck", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Rajarshi Guha", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "John May", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Egon Willighagen", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "maastrichtuniversity.nl", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": null, "email": null, "url": "https://sourceforge.net/p/cdk/mailman/?source=navbar", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "egonw", "additionDate": "2015-12-01T14:33:26Z", "lastUpdate": "2025-12-29T19:08:00.918429Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Annotation Seg Converter", "description": "This repository provides tools for segmentation files conversion in DicomSEG, with a primary focus on: DICOM RTSTRUCT to DICOM SEG: A Python script (rtstruct/rtstruct2dcmseg.py) converts DICOM Radiotherapy Structure Set (RTSTRUCT) files, along with their referenced DICOM image series, into DICOM Segmentation (SEG) objects. It can also optionally convert the individual Regions of Interest (ROIs) defined in the RTSTRUCT into separate NIfTI (.nii.gz) files. Nifti Conversions via dcmqi and Custom Scripts: The Docker image built from this repository also includes command-line tools from dcmqi (DICOM Quantitative Imaging Toolkit) and custom Python scripts for various conversions, such as: ITK image formats (NIfTI, NRRD) to/from DICOM SEG. DICOM series to NIfTI. DICOM SEG to NIfTI (custom alternative).", "homepage": "https://github.com/marver17/DICOMSEG_Converter", "biotoolsID": "dicomseg_converter", "biotoolsCURIE": "biotools:dicomseg_converter", "version": [ "1.4.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3553", "term": "Image annotation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2968", "term": "Image" }, "format": [ { "uri": "http://edamontology.org/format_3548", "term": "DICOM format" } ] }, { "data": { "uri": "http://edamontology.org/data_2968", "term": "Image" }, "format": [ { "uri": "http://edamontology.org/format_3549", "term": "nii" } ] }, { "data": { "uri": "http://edamontology.org/data_2048", "term": "Report" }, "format": [] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2968", "term": "Image" }, "format": [ { "uri": "http://edamontology.org/format_3548", "term": "DICOM format" } ] } ], "note": null, "cmd": "docker run --rm \\\n -v $(pwd)/DATA:/data \\\n -v $(pwd)/demo_output:/output \\\n harbor.eucaim.cancerimage.eu/ingestion-tools/dicomseg_converter:1.4.0 \\\n dicomseg \\\n --inputImageList /output/demo2_source/1.nii.gz,/output/demo2_source/2.nii.gz \\\n --inputMetadata /output/demo2_source/meta.json \\\n --inputDICOMDirectory /data/dicom_series \\\n --outputDICOM /output/demo2_nifti_to_dicomseg/output.dcm" }, { "operation": [ { "uri": "http://edamontology.org/operation_3553", "term": "Image annotation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2968", "term": "Image" }, "format": [ { "uri": "http://edamontology.org/format_3548", "term": "DICOM format" } ] }, { "data": { "uri": "http://edamontology.org/data_2968", "term": "Image" }, "format": [ { "uri": "http://edamontology.org/format_3548", "term": "DICOM format" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2968", "term": "Image" }, "format": [ { "uri": "http://edamontology.org/format_3549", "term": "nii" } ] } ], "note": null, "cmd": "docker run --rm \\\n -v $(pwd)/DATA:/data \\\n -v $(pwd)/demo_output:/output \\\n harbor.eucaim.cancerimage.eu/ingestion-tools/dicomseg_converter:1.4.0 \\\n itkimage \\\n --inputDICOM /data/dicomseg_input.dcm \\\n --outputDirectory /output/nifti_output \\\n -t nifti" }, { "operation": [ { "uri": "http://edamontology.org/operation_0226", "term": "Annotation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2968", "term": "Image" }, "format": [ { "uri": "http://edamontology.org/format_3548", "term": "DICOM format" } ] }, { "data": { "uri": "http://edamontology.org/data_2968", "term": "Image" }, "format": [ { "uri": "http://edamontology.org/format_3548", "term": "DICOM format" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2968", "term": "Image" }, "format": [ { "uri": "http://edamontology.org/format_3548", "term": "DICOM format" } ] } ], "note": null, "cmd": "docker run --rm \\\n -v $(pwd)/DATA:/data \\\n -v $(pwd)/demo_output:/output \\\n harbor.eucaim.cancerimage.eu/ingestion-tools/dicomseg_converter:1.4.0 \\\n rtstruct2seg \\\n /data/dicom_ct_series \\\n /data/rtstruct_file.dcm \\\n /output/seg_from_rtstruct.dcm" } ], "toolType": [], "topic": [ { "uri": "http://edamontology.org/topic_3063", "term": "Medical informatics" }, { "uri": "http://edamontology.org/topic_0219", "term": "Data curation and archival" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [], "license": "Apache-2.0", "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/marver17/DICOMSEG_Converter", "type": [ "Repository" ], "note": null }, { "url": "https://harbor.eucaim.cancerimage.eu/harbor/projects/3/repositories/dicomseg_converter/artifacts-tab", "type": [ "Repository" ], "note": "Harbor Repository" } ], "download": [], "documentation": [ { "url": "https://github.com/marver17/DICOMSEG_Converter", "type": [ "Command-line options" ], "note": null } ], "publication": [ { "doi": "10.1186/s13244-021-01081-8", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "How does DICOM support big data management? Investigating its use in medical imaging community", "abstract": "", "date": "2021-12-01T00:00:00Z", "citationCount": 34, "authors": [], "journal": "Insights into Imaging" } } ], "credit": [ { "name": "Mario Verdicchio", "email": "mario.verdicchio@synlab.it", "url": null, "orcidid": "https://orcid.org/0000-0002-3762-3100", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null }, { "name": "Marco Aiello", "email": "marco.aiello@synlab.it", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "owner": "marioverd", "additionDate": "2025-05-29T09:54:35.422273Z", "lastUpdate": "2025-12-29T16:29:13.934923Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "DICOM File Integrity Checker (EUCAIM-SW-002_T-01-01-002)", "description": "The tool performs a DICOM quality check in terms of correct number of files per sequence, corrupted files, precise directory hierarchy, separated dynamic series merging them, interest series filtering/selection by specific series description lists and diffusion sequence identification by b-values. 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Based on interaction geometries previously derived from protein crystal structures potential water positions are generated for free interaction directions (lone pairs of acceptors or hydrogen atoms of donors). Every small molecule present in the PDB structure is used to generate an active site of 6.5 Å radius around each atom. Within these active sites water molecules are placed.\nIn the corresponding publication we showed that WarPP is able to place 80% of water molecules within 1.0 Å distance to a crystallographically observed one.", "homepage": "http://proteinsplus.zbh.uni-hamburg.de/#warpp", "biotoolsID": "warpp", "biotoolsCURIE": "biotools:warpp", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2406", "term": "Protein structure analysis" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1460", "term": "Protein structure" }, "format": [ { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1460", "term": "Protein structure" }, "format": [ { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] }, { "data": { "uri": "http://edamontology.org/data_1772", "term": "Score" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_0123", "term": "Protein properties" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [], "license": null, "collectionID": [ "de.NBI" ], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [ "Germany" ], "elixirCommunity": [ "3D-BioInfo" ], "link": [], "download": [], "documentation": [ { "url": "http://proteinsplus.zbh.uni-hamburg.de/help/index", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1021/acs.jcim.8b00271", "pmid": "30036062", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Placement of Water Molecules in Protein Structures: From Large-Scale Evaluations to Single-Case Examples", "abstract": "Water molecules are of great importance for the correct representation of ligand binding interactions. Throughout the last years, water molecules and their integration into drug design strategies have received increasing attention. Nowadays a variety of tools are available to place and score water molecules. However, the most frequently applied software solutions require substantial computational resources. In addition, none of the existing methods has been rigorously evaluated on the basis of a large number of diverse protein complexes. Therefore, we present a novel method for placing water molecules, called WarPP, based on interaction geometries previously derived from protein crystal structures. Using a large, previously compiled, high-quality validation set of almost 1500 protein-ligand complexes containing almost 20000 crystallographically observed water molecules in their active sites, we validated our placement strategy. We correctly placed 80% of the water molecules within 1.0 Å of a crystallographically observed one.", "date": "2018-08-27T00:00:00Z", "citationCount": 33, "authors": [ { "name": "Nittinger E." }, { "name": "Flachsenberg F." }, { "name": "Bietz S." }, { "name": "Lange G." }, { "name": "Klein R." }, { "name": "Rarey M." } ], "journal": "Journal of Chemical Information and Modeling" } } ], "credit": [ { "name": "University of Hamburg - Center for Bioinformatics", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "owner": "ehrt", "additionDate": "2020-06-08T16:17:43Z", "lastUpdate": "2025-12-23T14:50:38.010415Z", "editPermission": { "type": "group", "authors": [ "ehrt" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "StructureProfiler", "description": "Tool for 3D protein structure profiling.", "homepage": "https://www.zbh.uni-hamburg.de/forschung/amd/software/structureprofiler.html", "biotoolsID": "StructureProfiler", "biotoolsCURIE": "biotools:StructureProfiler", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0249", "term": "Protein geometry calculation" }, { "uri": "http://edamontology.org/operation_0321", "term": "Protein structure validation" }, { "uri": "http://edamontology.org/operation_0482", "term": "Protein-ligand docking" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0196", "term": "Sequence assembly" }, { "uri": "http://edamontology.org/topic_0166", "term": "Protein structural motifs and surfaces" }, { "uri": "http://edamontology.org/topic_0082", "term": "Structure prediction" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [], "license": "Other", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [ { "url": "https://software.zbh.uni-hamburg.de/pages/getPackage", "type": "Downloads page", "note": "NAOMI ChemBio Suite including the package", "version": null } ], "documentation": [], "publication": [ { "doi": "10.1093/bioinformatics/bty692", "pmid": "30124779", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "StructureProfiler: An all-in-one tool for 3D protein structure profiling", "abstract": "Motivation Three-dimensional protein structures are important starting points for elucidating protein function and applications like drug design. Computational methods in this area rely on high quality validation datasets which are usually manually assembled. Due to the increase in published structures as well as the increasing demand for specially tailored validation datasets, automatic procedures should be adopted. Results StructureProfiler is a new tool for automatic, objective and customizable profiling of X-ray protein structures based on the most frequently applied selection criteria currently in use to assemble benchmark datasets. As examples, four dataset configurations (Astex, Iridium, Platinum, combined), all results of the combined tests and the list of all PDB Ids passing the combined criteria set are attached in theSupplementary Material.", "date": "2019-03-01T00:00:00Z", "citationCount": 4, "authors": [ { "name": "Meyder A." }, { "name": "Kampen S." }, { "name": "Sieg J." }, { "name": "Fahrrolfes R." }, { "name": "Friedrich N.-O." }, { "name": "Flachsenberg F." }, { "name": "Rarey M." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "Matthias Rarey", "email": "rarey@zbh.uni-hamburg.de", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "ehrt", "additionDate": "2019-07-06T06:35:25Z", "lastUpdate": "2025-12-23T14:50:37.487104Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "StructureProfiler", "description": "StructureProfiler was developed as an all-in-one tool to screen structures based on selection criteria typically used upon dataset assembly for structure-based design methods. Test configurations based on either the Astex, the Iridium HT, the Platinum, or the combination of all three criteria catalogs. (Note that RSCC as an electron density validation criteria was replaced by EDIAm scoring).", "homepage": "http://proteinsplus.zbh.uni-hamburg.de/#structureprofiler", "biotoolsID": "structurechecker", "biotoolsCURIE": "biotools:structurechecker", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3695", "term": "Filtering" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1461", "term": "Protein-ligand complex" }, "format": [ { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2087", "term": "Molecular property" }, "format": [ { "uri": "http://edamontology.org/format_3752", "term": "CSV" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Web service" ], "topic": [ { "uri": "http://edamontology.org/topic_3332", "term": "Computational chemistry" }, { "uri": "http://edamontology.org/topic_0154", "term": "Small molecules" }, { "uri": "http://edamontology.org/topic_3534", "term": "Protein binding sites" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [], "license": null, "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [ "Germany" ], "elixirCommunity": [ "3D-BioInfo" ], "link": [], "download": [], "documentation": [ { "url": "http://proteinsplus.zbh.uni-hamburg.de/help/index", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/bty692", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "StructureProfiler: An all-in-one tool for 3D protein structure profiling", "abstract": "© The Author(s) 2018.Motivation Three-dimensional protein structures are important starting points for elucidating protein function and applications like drug design. Computational methods in this area rely on high quality validation datasets which are usually manually assembled. Due to the increase in published structures as well as the increasing demand for specially tailored validation datasets, automatic procedures should be adopted. Results StructureProfiler is a new tool for automatic, objective and customizable profiling of X-ray protein structures based on the most frequently applied selection criteria currently in use to assemble benchmark datasets. As examples, four dataset configurations (Astex, Iridium, Platinum, combined), all results of the combined tests and the list of all PDB Ids passing the combined criteria set are attached in theSupplementary Material.", "date": "2019-03-01T00:00:00Z", "citationCount": 2, "authors": [ { "name": "Meyder A." }, { "name": "Kampen S." }, { "name": "Sieg J." }, { "name": "Fahrrolfes R." }, { "name": "Friedrich N.-O." }, { "name": "Flachsenberg F." }, { "name": "Rarey M." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "University of Hamburg - Center for Bioinformatics", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "owner": "ehrt", "additionDate": "2020-06-08T18:35:57Z", "lastUpdate": "2025-12-23T14:50:36.983259Z", "editPermission": { "type": "private", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Protoss", "description": "Fully automated hydrogen prediction tool for protein-ligand complexes. It adds missing hydrogen atoms to protein structures and detects reasonable protonation states, tautomers, and hydrogen coordinates of both protein and ligand molecules. It investigates hydrogen bonds, metal interactions and repulsive atom contacts for all possible states and calculates an optimal hydrogen bonding network within these degrees of freedom.", "homepage": "http://proteinsplus.zbh.uni-hamburg.de/#protoss", "biotoolsID": "protoss", "biotoolsCURIE": "biotools:protoss", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0394", "term": "Hydrogen bond calculation" }, { "uri": "http://edamontology.org/operation_2949", "term": "Protein interaction analysis" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1460", "term": "Protein structure" }, "format": [ { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] }, { "data": { "uri": "http://edamontology.org/data_1461", "term": "Protein-ligand complex" }, "format": [ { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1460", "term": "Protein structure" }, "format": [ { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] }, { "data": { "uri": "http://edamontology.org/data_1461", "term": "Protein-ligand complex" }, "format": [ { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_0128", "term": "Protein interactions" }, { "uri": "http://edamontology.org/topic_0602", "term": "Molecular interactions, pathways and networks" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [], "license": null, "collectionID": [ "de.NBI", "COVID-19" ], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [ "Germany" ], "elixirCommunity": [ "3D-BioInfo" ], "link": [], "download": [], "documentation": [ { "url": "http://proteinsplus.zbh.uni-hamburg.de/help/index", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1186/1758-2946-6-12", "pmid": "24694216", "pmcid": "PMC4019353", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Protoss: A holistic approach to predict tautomers and protonation states in protein-ligand complexes", "abstract": "The calculation of hydrogen positions is a common preprocessing step when working with crystal structures of protein-ligand complexes. An explicit description of hydrogen atoms is generally needed in order to analyze the binding mode of particular ligands or to calculate the associated binding energies. Due to the large number of degrees of freedom resulting from different chemical moieties and the high degree of mutual dependence this problem is anything but trivial. In addition to an efficient algorithm to take care of the complexity resulting from complicated hydrogen bonding networks, a robust chemical model is needed to describe effects such as tautomerism and ionization consistently. We present a novel method for the placement of hydrogen coordinates in protein-ligand complexes which takes tautomers and protonation states of both protein and ligand into account. Our method generates the most probable hydrogen positions on the basis of an optimal hydrogen bonding network using an empirical scoring function. The high quality of our results could be verified by comparison to the manually adjusted Astex diverse set and a remarkably low rate of undesirable hydrogen contacts compared to other tools. © 2014 Bietz et al.; licensee Chemistry Central Ltd.", "date": "2014-04-03T00:00:00Z", "citationCount": 153, "authors": [ { "name": "Bietz S." }, { "name": "Urbaczek S." }, { "name": "Schulz B." }, { "name": "Rarey M." } ], "journal": "Journal of Cheminformatics" } }, { "doi": "10.1186/1758-2946-1-13", "pmid": "20298519", "pmcid": "PMC3225823", "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "Fast automated placement of polar hydrogen atoms in protein-ligand complexes", "abstract": "Background. Hydrogen bonds play a major role in the stabilization of protein-ligand complexes. The ability of a functional group to form them depends on the position of its hydrogen atoms. An accurate knowledge of the positions of hydrogen atoms in proteins is therefore important to correctly identify hydrogen bonds and their properties. The high mobility of hydrogen atoms introduces several degrees of freedom: Tautomeric states, where a hydrogen atom alters its binding partner, torsional changes where the position of the hydrogen atom is rotated around the last heavy-atom bond in a residue, and protonation states, where the number of hydrogen atoms at a functional group may change. Also, side-chain flips in glutamine and asparagine and histidine residues, which are common crystallographic ambiguities must be identified before structure-based calculations can be conducted. Results. We have implemented a method to determine the most probable hydrogen atom positions in a given protein-ligand complex. Optimality of hydrogen bond geometries is determined by an empirical scoring function which is used in molecular docking. This allows to evaluate protein-ligand interactions with an established model. Also, our method allows to resolve common crystallographic ambiguities such as as flipped amide groups and histidine residues. To ensure high speed, we make use of a dynamic programming approach. Conclusion. Our results were checked against selected high-resolution structures from an external dataset, for which the positions of the hydrogen atoms have been validated manually. The quality of our results is comparable to that of other programs, with the advantage of being fast enough to be applied on-the-fly for interactive usage or during score evaluation. © 2009 Lippert and Rarey; licensee BioMed Central Ltd.", "date": "2009-12-01T00:00:00Z", "citationCount": 58, "authors": [ { "name": "Lippert T." }, { "name": "Rarey M." } ], "journal": "Journal of Cheminformatics" } } ], "credit": [ { "name": "University of Hamburg - Center for Bioinformatics", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": null, "email": "rarey-office@zbh.uni-hambugr.de", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "ehrt", "additionDate": "2016-11-28T10:07:16Z", "lastUpdate": "2025-12-23T14:50:36.482733Z", "editPermission": { "type": "group", "authors": [ "Bietz", "ehrt" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "PoseView", "description": "This tool automatically creates two-dimensional diagrams which depict the protein-ligand interactions and conform to chemical drawing conventions. Directed interactions between protein and ligand are estimated by an integrated scoring scheme and depicted as lines between detailed structure diagrams for both protein residues and the ligand molecule.", "homepage": "http://proteinsplus.zbh.uni-hamburg.de/#poseview", "biotoolsID": "poseview", "biotoolsCURIE": "biotools:poseview", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0570", "term": "Structure visualisation" }, { "uri": "http://edamontology.org/operation_3083", "term": "Pathway or network visualisation" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1460", "term": "Protein structure" }, "format": [ { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2968", "term": "Image" }, "format": [ { "uri": "http://edamontology.org/format_3603", "term": "PNG" }, { "uri": "http://edamontology.org/format_3604", "term": "SVG" }, { "uri": "http://edamontology.org/format_3508", "term": "PDF" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_0092", "term": "Data visualisation" }, { "uri": "http://edamontology.org/topic_0602", "term": "Molecular interactions, pathways and networks" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [], "license": null, "collectionID": [ "de.NBI" ], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [ "Germany" ], "elixirCommunity": [ "3D-BioInfo" ], "link": [], "download": [], "documentation": [ { "url": "http://proteinsplus.zbh.uni-hamburg.de/help/index", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/btl150", "pmid": "16632493", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Molecular complexes at a glance: Automated generation of two-dimensional complex diagrams", "abstract": "Motivation: In this paper a new algorithmic approach is presented, which automatically generates structure diagrams of molecular complexes. A complex diagram contains the ligand, the amino acids of the protein interacting with the ligand and the hydrophilic interactions schematized as dashed lines between the corresponding atoms. The algorithm is based on a combinatorial optimization strategy which solves parts of the layout problem non-heuristically. The depicted molecules are represented as structure diagrams according to the chemical nomenclature. Due to the frequent usage of complex diagrams in the scientific literature as well as in text books dealing with structural biology, biochemistry and medicinal chemistry, the new algorithm is a key element for computer applications in these areas. Results: The method was implemented in the new software tool PoseView. It was tested on a representative dataset containing 305 protein - ligand complexes in total from the Brookhaven Protein Data Bank. PoseView was able to find collision-free layouts for more than three quarters of all complexes. In the following the layout generation algorithm is presented and, additional to the statistical results, representative test cases demonstrating the challenges of the layout generation will be discussed. © 2006 Oxford University Press.", "date": "2006-07-15T00:00:00Z", "citationCount": 349, "authors": [ { "name": "Stierand K." }, { "name": "Maass P.C." }, { "name": "Rarey M." } ], "journal": "Bioinformatics" } }, { "doi": "10.1002/cmdc.200700010", "pmid": "17436259", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "From modeling to medicinal chemistry: Automatic generation oft wo-dimensional complex diagrams", "abstract": "As a result of the increasing application of structure-based drug design, the visualization of protein-ligand complexes has become an important feature in medicinal chemistry. The large number of experimentally resolved complex structures and the further development of computer-aided methods like docking or de novo design establishes new possibilities in this field. During lead finding and optimization, a manual investigation of many complexes and their interaction patterns is typically performed. We present an algorithm that automatically generates 2D-protein-ligand diagrams as a possible solution for a transparent visualization of the contact partners in a complex and as a support for scientists in the evaluation of structure-based design results. Running the software on representative test data sets, it generates collision free layouts for ∼76% of the cases in the range of tenths of a second per complex. The success rate for complexes with ligands which have a molecular weight >500 Da is 87 %. © 2007 Wiley-VCH Verlag GmbH & Co. KGaA.", "date": "2007-06-11T00:00:00Z", "citationCount": 84, "authors": [ { "name": "Stierand K." }, { "name": "Rarey M." } ], "journal": "ChemMedChem" } } ], "credit": [ { "name": "University of Hamburg - Center for Bioinformatics", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": null, "email": "rarey-office@zbh.uni-hamburg.de", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "ehrt", "additionDate": "2016-11-21T10:33:07Z", "lastUpdate": "2025-12-23T14:50:36.016352Z", "editPermission": { "type": "group", "authors": [ "Bietz", "ehrt" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "GeoMine", "description": "Interactive Pattern Mining of Protein-Ligand Interfaces in the Protein Data Bank.\n\nProteinsPlus structure-based modeling support server. This server is a common web portal for all tools related to structure-based modeling created by the AMD group (Prof. M. Rarey) at ZBH, Hamburg, including DoGSite Scorer, EDIA, PPI, PoseView, SIENA and ProToss.", "homepage": "https://proteins.plus", "biotoolsID": "geomine", "biotoolsCURIE": "biotools:geomine", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2421", "term": "Database search" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_0128", "term": "Protein interactions" }, { "uri": "http://edamontology.org/topic_2830", "term": "Immunoproteins and antigens" }, { "uri": "http://edamontology.org/topic_0091", "term": "Bioinformatics" } ], "operatingSystem": [], "language": [], "license": null, "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [], "download": [], "documentation": [], "publication": [ { "doi": "10.1093/BIOINFORMATICS/BTAA693", "pmid": "32735322", "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "GeoMine: interactive pattern mining of protein-ligand interfaces in the Protein Data Bank", "abstract": "© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.SUMMARY: The searching of user-defined 3D queries in molecular interfaces is a computationally challenging problem that is not satisfactorily solved so far. Most of the few existing tools focused on that purpose are desktop based and not openly available. Besides that, they show a lack of query versatility, search efficiency and user-friendliness. We address this issue with GeoMine, a publicly available web application that provides textual, numerical and geometrical search functionality for protein-ligand binding sites derived from structural data contained in the Protein Data Bank (PDB). The query generation is supported by a 3D representation of a start structure that provides interactively selectable elements like atoms, bonds and interactions. GeoMine gives full control over geometric variability in the query while performing a deterministic, precise search. Reasonably selective queries are processed on the entire set of protein-ligand complexes in the PDB within a few minutes. GeoMine offers an interactive and iterative search process of successive result analyses and query adaptations. From the numerous potential applications, we picked two from the field of side-effect analyze showcasing the usefulness of GeoMine. AVAILABILITY AND IMPLEMENTATION: GeoMine is part of the ProteinsPlus web application suite and freely available at https://proteins.plus. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.", "date": "2021-04-20T00:00:00Z", "citationCount": 1, "authors": [ { "name": "Diedrich K." }, { "name": "Graef J." }, { "name": "Schoning-Stierand K." }, { "name": "Rarey M." } ], "journal": "Bioinformatics (Oxford, England)" } } ], "credit": [ { "name": "Matthias Rarey", "email": "rarey@zbh.uni-hamburg.de", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "owner": "ehrt", "additionDate": "2021-01-18T10:36:05Z", "lastUpdate": "2025-12-23T14:50:35.515139Z", "editPermission": { "type": "group", "authors": [ "ehrt" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "DoGSiteScorer", "description": "Automated pocket detection and analysis tool enabling the identification of potential binding pockets and subpockets in protein structures. Additionally, global properties, describing size, shape and chemical features of the predicted (sub)pockets, are calculated. Per default, a simple druggability score is provided for each (sub)pocket, based on a linear combination of the three descriptors describing volume, hydrophobicity and enclosure.", "homepage": "http://proteinsplus.zbh.uni-hamburg.de/#dogsite", "biotoolsID": "dogsitescorer", "biotoolsCURIE": "biotools:dogsitescorer", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2406", "term": "Protein structure analysis" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1460", "term": "Protein structure" }, "format": [ { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2878", "term": "Protein structural motif" }, "format": [ { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] }, { "data": { "uri": "http://edamontology.org/data_0897", "term": "Protein property" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] } ], "note": "Computational detection of protein binding pockets Protein binding pockets Property statistics of all protein binding pockets", "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_3534", "term": "Protein binding sites" }, { "uri": "http://edamontology.org/topic_3474", "term": "Machine learning" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [], "license": null, "collectionID": [ "de.NBI", "COVID-19" ], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [ "Germany" ], "elixirCommunity": [ "3D-BioInfo" ], "link": [], "download": [], "documentation": [ { "url": "http://proteinsplus.zbh.uni-hamburg.de/help/index", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1021/ci100241y", "pmid": "20945875", "pmcid": null, "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "Analyzing the topology of active sites: On the prediction of pockets and subpockets", "abstract": "Automated prediction of protein active sites is essential for large-scale protein function prediction, classification, and druggability estimates. In this work, we present DoGSite, a new structure-based method to predict active sites in proteins based on a Difference of Gaussian (DoG) approach which originates from image processing. In contrast to existing methods, DoGSite splits predicted pockets into subpockets, revealing a refined description of the topology of active sites. DoGSite correctly predicts binding pockets for over 92% of the PDBBind and the scPDB data set, being in line with the best-performing methods available. In 63% of the PDBBind data set the detected pockets can be subdivided into smaller subpockets. The cocrystallized ligand is contained in exactly one subpocket in 87% of the predictions. Furthermore, we introduce a more precise prediction performance measure by taking the pairwise ligand and pocket coverage into account. In 90% of the cases DoGSite predicts a pocket that contains at least half of the ligand. In 70% of the cases additionally more than a quarter of the respective pocket itself is covered by the cocrystallized ligand. Consideration of subpockets produces an increase in coverage yielding a success rate of 83% for the latter measure. © 2010 American Chemical Society.", "date": "2010-11-22T00:00:00Z", "citationCount": 186, "authors": [ { "name": "Volkamer A." }, { "name": "Griewel A." }, { "name": "Grombacher T." }, { "name": "Rarey M." } ], "journal": "Journal of Chemical Information and Modeling" } }, { "doi": "10.1093/bioinformatics/bts310", "pmid": "22628523", "pmcid": null, "type": [ "Other" ], "version": null, "note": null, "metadata": { "title": "Dogsitescorer: A web server for automatic binding site prediction, analysis and druggability assessment", "abstract": "Motivation: Many drug discovery projects fail because the underlying target is finally found to be undruggable. Progress in structure elucidation of proteins now opens up a route to automatic structure-based target assessment. DoGSiteScorer is a newly developed automatic tool combining pocket prediction, characterization and druggability estimation and is now available through a web server. © The Author 2012. Published by Oxford University Press. All rights reserved.", "date": "2012-08-01T00:00:00Z", "citationCount": 396, "authors": [ { "name": "Volkamer A." }, { "name": "Kuhn D." }, { "name": "Rippmann F." }, { "name": "Rarey M." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "University of Hamburg - Center for Bioinformatics", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": null, "email": "rarey-office@zbh.uni-hamburg.de", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "ehrt", "additionDate": "2016-11-21T10:33:07Z", "lastUpdate": "2025-12-23T14:50:34.366857Z", "editPermission": { "type": "group", "authors": [ "Bietz", "ehrt" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "METALizer", "description": "METALizer predicts the coordination geometry of metals in metalloproteins. Potential coordination geometries of metals are matched onto the found metal interactions in the examined structure. The predicted coordination geometries and the observed metal interaction distances can be compared interactively to statistics calculated on the PDB.", "homepage": "https://proteins.plus/#metalizer", "biotoolsID": "metalizer", "biotoolsCURIE": "biotools:metalizer", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3898", "term": "Metal-binding site prediction" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1460", "term": "Protein structure" }, "format": [ { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0906", "term": "Protein interaction data" }, "format": [] } ], "note": null, "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_0128", "term": "Protein interactions" }, { "uri": "http://edamontology.org/topic_3534", "term": "Protein binding sites" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [], "license": null, "collectionID": [ "de.NBI" ], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [ "Germany" ], "elixirCommunity": [ "3D-BioInfo" ], "link": [], "download": [], "documentation": [ { "url": "http://proteinsplus.zbh.uni-hamburg.de/help/index", "type": [ "General" ], "note": null } ], "publication": [], "credit": [ { "name": "University of Hamburg - Center for Bioinformatics", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": null, "typeRole": [], "note": null } ], "owner": "ehrt", "additionDate": "2020-06-08T16:00:55Z", "lastUpdate": "2025-12-23T14:50:33.410897Z", "editPermission": { "type": "group", "authors": [ "ehrt" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "SIENA", "description": "Search for homologous protein binding sites structures in the Protein Data Bank. The tool allows an automated assembly and preprocessing of protein structure ensembles supporting protein flexibility and point mutation analyses as well as structure-based virtual screening.", "homepage": "http://proteinsplus.zbh.uni-hamburg.de/#siena", "biotoolsID": "siena", "biotoolsCURIE": "biotools:siena", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3432", "term": "Clustering" }, { "uri": "http://edamontology.org/operation_0339", "term": "Structure database search" }, { "uri": "http://edamontology.org/operation_0310", "term": "Sequence assembly" }, { "uri": "http://edamontology.org/operation_0295", "term": "Structure alignment" }, { "uri": "http://edamontology.org/operation_0244", "term": "Protein flexibility and motion analysis" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1460", "term": "Protein structure" }, "format": [ { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1460", "term": "Protein structure" }, "format": [ { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] }, { "data": { "uri": "http://edamontology.org/data_1384", "term": "Sequence alignment (protein)" }, "format": [] }, { "data": { "uri": "http://edamontology.org/data_1497", "term": "Root-mean-square deviation" }, "format": [] } ], "note": "statistics", "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_3534", "term": "Protein binding sites" }, { "uri": "http://edamontology.org/topic_0081", "term": "Structure analysis" }, { "uri": "http://edamontology.org/topic_3336", "term": "Drug discovery" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [], "license": null, "collectionID": [ "de.NBI", "COVID-19" ], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [ "Germany" ], "elixirCommunity": [ "3D-BioInfo" ], "link": [], "download": [], "documentation": [ { "url": "http://proteinsplus.zbh.uni-hamburg.de/help/index", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1021/acs.jcim.5b00588", "pmid": "26759067", "pmcid": null, "type": [ "Method" ], "version": null, "note": null, "metadata": { "title": "SIENA: Efficient Compilation of Selective Protein Binding Site Ensembles", "abstract": "Structural flexibility of proteins has an important influence on molecular recognition and enzymatic function. In modeling, structure ensembles are therefore often applied as a valuable source of alternative protein conformations. However, their usage is often complicated by structural artifacts and inconsistent data annotation. Here, we present SIENA, a new computational approach for the automated assembly and preprocessing of protein binding site ensembles. Starting with an arbitrarily defined binding site in a single protein structure, SIENA searches for alternative conformations of the same or sequentially closely related binding sites. The method is based on an indexed database for identifying perfect k-mer matches and a recently published algorithm for the alignment of protein binding site conformations. Furthermore, SIENA provides a new algorithm for the interaction-based selection of binding site conformations which aims at covering all known ligand-binding geometries. Various experiments highlight that SIENA is able to generate comprehensive and well selected binding site ensembles improving the compatibility to both known and unconsidered ligand molecules. Starting with the whole PDB as data source, the computation time of the whole ensemble generation takes only a few seconds. SIENA is available via a Web service at www.zbh.uni-hamburg.de/siena.", "date": "2016-01-25T00:00:00Z", "citationCount": 37, "authors": [ { "name": "Bietz S." }, { "name": "Rarey M." } ], "journal": "Journal of Chemical Information and Modeling" } }, { "doi": "10.1021/acs.jcim.5b00210", "pmid": "26098831", "pmcid": null, "type": [ "Method" ], "version": null, "note": null, "metadata": { "title": "ASCONA: Rapid Detection and Alignment of Protein Binding Site Conformations", "abstract": "The usage of conformational ensembles constitutes a widespread technique for the consideration of protein flexibility in computational biology. When experimental structures are applied for this purpose, alignment techniques are usually required in dealing with structural deviations and annotation inconsistencies. Moreover, many application scenarios focus on protein ligand binding sites. Here, we introduce our new alignment algorithm ASCONA that has been specially geared to the problem of aligning multiple conformations of sequentially similar binding sites. Intense efforts have been directed to an accurate detection of highly flexible backbone deviations, multiple binding site matches within a single structure, and a reliable, but at the same time highly efficient, search algorithm. In contrast, most available alignment methods rather target other issues, e.g., the global alignment of distantly related proteins that share structurally conserved regions. For conformational ensembles, this might not only result in an overhead of computation time but could also affect the achieved accuracy, especially for more complicated cases as highly flexible proteins. ASCONA was evaluated on a test set containing 1107 structures of 65 diverse proteins. In all cases, ASCONA was able to correctly align the binding site at an average alignment computation time of 4 ms per target. Furthermore, no false positive matches were observed when searching the same query sites in the structures of other proteins. ASCONA proved to cope with highly deviating backbone structures and to tolerate structural gaps and moderate mutation rates. ASCONA is available free of charge for academic use at http://www.zbh.uni-hamburg.de/ascona. (Figure Presented).", "date": "2015-08-24T00:00:00Z", "citationCount": 15, "authors": [ { "name": "Bietz S." }, { "name": "Rarey M." } ], "journal": "Journal of Chemical Information and Modeling" } } ], "credit": [ { "name": "University of Hamburg - Center for Bioinformatics", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": null, "email": "rarey-office@zbh.uni-hamburg.de", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "ehrt", "additionDate": "2016-11-28T10:07:17Z", "lastUpdate": "2025-12-23T14:50:32.227556Z", "editPermission": { "type": "group", "authors": [ "Bietz", "ehrt" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "HyPPI", "description": "HyPPI classifies a protein-protein complex concerning its interaction type into permanent, transient or crystal artifact. Permanent protein-protein complexes are only stable in their complexed state and the subunits would denature upon complex dissociation. Transient protein-protein complexes are stable in the complexed form as well as in the monomeric depending of the necessary function of the complex. Crystal artifacts have no biological function and are artifically formed during 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 takes the symmetry of the protein-protein interface into account.", "homepage": "http://proteinsplus.zbh.uni-hamburg.de/#ppi", "biotoolsID": "ppi", "biotoolsCURIE": "biotools:ppi", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2492", "term": "Protein interaction prediction" }, { "uri": "http://edamontology.org/operation_2406", "term": "Protein structure analysis" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1460", "term": "Protein structure" }, "format": [ { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1772", "term": "Score" }, "format": [] } ], "note": "Probability score for interface classification", "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_0128", "term": "Protein interactions" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [], "license": null, "collectionID": [ "de.NBI" ], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [ "Germany" ], "elixirCommunity": [ "3D-BioInfo" ], "link": [], "download": [], "documentation": [ { "url": "http://proteinsplus.zbh.uni-hamburg.de/help/index", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1007/s10822-012-9626-2", "pmid": "23269578", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "A consistent description of HYdrogen bond and DEhydration energies in protein-ligand complexes: Methods behind the HYDE scoring function", "abstract": "The estimation of free energy of binding is a key problem in structure-based design. We developed the scoring function HYDE based on a consistent description of HYdrogen bond and DEhydration energies in protein-ligand complexes. HYDE is applicable to all types of protein targets since it is not calibrated on experimental binding affinity data or protein-ligand complexes. The comprehensible atom-based score of HYDE is visualized by applying a very intuitive coloring scheme, thereby facilitating the analysis of protein-ligand complexes in the lead optimization process. In this paper, we have revised several aspects of the former version of HYDE which was described in detail previously. The revised HYDE version was already validated in large-scale redocking and screening experiments which were performed in the course of the Docking and Scoring Symposium at 241st ACS National Meeting. In this study, we additionally evaluate the ability of the revised HYDE version to predict binding affinities. On the PDBbind 2007 coreset, HYDE achieves a correlation coefficient of 0.62 between the experimental binding constants and the predicted binding energy, performing second best on this dataset compared to 17 other well-established scoring functions. Further, we show that the performance of HYDE in large-scale redocking and virtual screening experiments on the Astex diverse set and the DUD dataset respectively, is comparable to the best methods in this field. © 2012 Springer Science+Business Media Dordrecht.", "date": "2013-01-01T00:00:00Z", "citationCount": 218, "authors": [ { "name": "Schneider N." }, { "name": "Lange G." }, { "name": "Hindle S." }, { "name": "Klein R." }, { "name": "Rarey M." } ], "journal": "Journal of Computer-Aided Molecular Design" } } ], "credit": [ { "name": "University of Hamburg - Center for Bioinformatics", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": null, "email": "rarey-office@zbh.uni-hamburg.de", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "ehrt", "additionDate": "2016-11-28T10:07:16Z", "lastUpdate": "2025-12-23T14:50:31.665805Z", "editPermission": { "type": "group", "authors": [ "ehrt" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "EDIA", "description": "Easily interpretable electron density score for individual atoms. It quantifies the electron density support of each single atom by computing a weighted sum over an oversampled electron density grid in the proximity of the atom. Atomic EDIA values can also be combined with the help of the power mean to compute EDIA_m, an electron density score for small molecules, fragments, or residues.", "homepage": "http://proteinsplus.zbh.uni-hamburg.de/#edia", "biotoolsID": "edia", "biotoolsCURIE": "biotools:edia", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0321", "term": "Protein model validation" }, { "uri": "http://edamontology.org/operation_2406", "term": "Protein structure analysis" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1460", "term": "Protein structure" }, "format": [ { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] }, { "data": { "uri": "http://edamontology.org/data_1461", "term": "Protein-ligand complex" }, "format": [ { "uri": "http://edamontology.org/format_1476", "term": "PDB" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1772", "term": "Score" }, "format": [] } ], "note": "Score for structure quality assessment on a global or atomistic level", "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_0081", "term": "Structure analysis" }, { "uri": "http://edamontology.org/topic_2828", "term": "X-ray diffraction" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [], "license": null, "collectionID": [ "de.NBI", "COVID-19" ], "maturity": null, "cost": "Free of charge", "accessibility": null, "elixirPlatform": [], "elixirNode": [ "Germany" ], "elixirCommunity": [ "3D-BioInfo" ], "link": [], "download": [], "documentation": [ { "url": "http://proteinsplus.zbh.uni-hamburg.de/help/index", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1021/acs.jcim.7b00391", "pmid": "28981269", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Estimating Electron Density Support for Individual Atoms and Molecular Fragments in X-ray Structures", "abstract": "© 2017 American Chemical Society.Macromolecular structures resolved by X-ray crystallography are essential for life science research. While some methods exist to automatically quantify the quality of the electron density fit, none of them is without flaws. Especially the question of how well individual parts like atoms, small fragments, or molecules are supported by electron density is difficult to quantify. While taking experimental uncertainties correctly into account, they do not offer an answer on how reliable an individual atom position is. A rapid quantification of this atomic position reliability would be highly valuable in structure-based molecular design. To overcome this limitation, we introduce the electron density score EDIA for individual atoms and molecular fragments. EDIA assesses rapidly, automatically, and intuitively the fit of individual as well as multiple atoms (EDIAm) into electron density accompanied by an integrated error analysis. The computation is based on the standard 2fo - fc electron density map in combination with the model of the molecular structure. For evaluating partial structures, EDIAm shows significant advantages compared to the real-space R correlation coefficient (RSCC) and the real-space difference density Z score (RSZD) from the molecular modeler's point of view. Thus, EDIA abolishes the time-consuming step of visually inspecting the electron density during structure selection and curation. It supports daily modeling tasks of medicinal and computational chemists and enables a fully automated assembly of large-scale, high-quality structure data sets. Furthermore, EDIA scores can be applied for model validation and method development in computer-aided molecular design. In contrast to measuring the deviation from the structure model by root-mean-squared deviation, EDIA scores allow comparison to the underlying experimental data taking its uncertainty into account.", "date": "2017-10-23T00:00:00Z", "citationCount": 33, "authors": [ { "name": "Meyder A." }, { "name": "Nittinger E." }, { "name": "Lange G." }, { "name": "Klein R." }, { "name": "Rarey M." } ], "journal": "Journal of Chemical Information and Modeling" } } ], "credit": [ { "name": "University of Hamburg - Center for Bioinformatics", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": null, "email": "rarey-office@zbh.uni-hamburg.de", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "owner": "ehrt", "additionDate": "2016-11-28T10:07:17Z", "lastUpdate": "2025-12-23T14:50:31.055029Z", "editPermission": { "type": "group", "authors": [ "Bietz", "ehrt" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Data Integration Quality Check Tool (DIQCT)", "description": "A tool that checks the clinical metadata quality (validity, completeness), the integrity between images and clinical metadata provided as well as their accuracy, the de-identification protocol applied, and existence of annotation together with the consistency between the images and the annotation files and informs the user on corrective actions prior to data upload.", "homepage": "https://www.mdpi.com/2939712", "biotoolsID": "data_integration_quality_check_tool_diqct", "biotoolsCURIE": "biotools:data_integration_quality_check_tool_diqct", "version": [], "otherID": [], "relation": [], "function": [], "toolType": [ "Desktop application", "Suite" ], "topic": [ { "uri": "http://edamontology.org/topic_3572", "term": "Data quality management" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "Python", "R" ], "license": "Proprietary", "collectionID": [ "eucaim" ], "maturity": "Mature", "cost": "Commercial", "accessibility": "Restricted access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://harbor.eucaim.cancerimage.eu/harbor/projects/3/repositories/dicqt/", "type": [ "Repository" ], "note": "Link to the Harbor image" }, { "url": "https://drive.google.com/drive/folders/15HotbC4RnBXe83lzWEnOQZksB0pZa1JY", "type": [ "Other" ], "note": "Link to the temporary license of the tool" } ], "download": [], "documentation": [ { "url": "https://docs.google.com/document/d/1b_5-pf94_QeOZVT2wVdG1YpWkAiTskwa/edit?usp=sharing&ouid=106267739460923945711&rtpof=true&sd=true", "type": [ "Other" ], "note": null }, { "url": "https://docs.google.com/document/d/1EnkkmFOGAo-WhPwx3OQ8vxSb3FKFn4b-/edit?usp=sharing&ouid=106267739460923945711&rtpof=true&sd=true", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.3390/info15090533", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Toward Ensuring Data Quality in Multi-Site Cancer Imaging Repositories", "abstract": "", "date": "2024-09-01T00:00:00Z", "citationCount": 7, "authors": [], "journal": "Information (Switzerland)" } }, { "doi": "10.1109/EMBC48229.2022.9871018", "pmid": null, "pmcid": null, "type": [], "version": null, "note": null, "metadata": { "title": "Data Quality Check in Cancer Imaging Research: Deploying and Evaluating the DIQCT Tool", "abstract": "", "date": "2022-01-01T00:00:00Z", "citationCount": 5, "authors": [], "journal": "Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS" } } ], "credit": [ { "name": "Ioanna Chouvarda", "email": "ioannach@auth.gr", "url": null, "orcidid": "https://orcid.org/0000-0001-8915-6658", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "owner": "authEucaim", "additionDate": "2025-05-16T09:56:39.880752Z", "lastUpdate": "2025-12-23T13:36:06.026155Z", "editPermission": { "type": "group", "authors": [ "dimfilos" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "Image Duplicates Checker", "description": "Detects duplicate or visually similar DICOM series using a tiered approach that combines metadata analysis, hash-based comparison, and pixel-level similarity metrics.\nIdeal for:\n1. 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