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http://www.rcsb.org/#Category-welcome

Collection of structural data of biological macromolecules. Database of information about 3D structures of large biological molecules, including proteins and nucleic acids. Users can perform queries on data and analyze and visualize results.

Proper citation: Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) (RRID:SCR_012820) Copy   

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http://sw-tools.pdb.org/index.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. Information Portal to Biological Macromolecular Structures provides variety of software tools made available through the RCSB. These tools include: data extraction and deposition preparation tools, data format conversion and validation tools, data parsing tools, dictionary and data management tools, visualization tools that support PDBx/mmCIF, and other PDBx/mmCIF software library tools.

Proper citation: RCSB PDB Software Tools (RRID:SCR_000035) Copy   

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http://pdbml.pdb.org/

Markup Language that provides a representation of PDB data in XML format. The description of this format is provided in XML schema of the PDB Exchange Data Dictionary. This schema is produced by direct translation of the mmCIF format PDB Exchange Data Dictionary Other data dictionaries used by the PDB have been electronically translated into XML/XSD schemas and these are also presented in the list below. * PDBML data files are provided in three forms: ** fully marked-up files, ** files without atom records ** files with a more space efficient encoding of atom records * Data files in PDBML format can be downloaded from the RCSB PDB website or by ftp. * Software tools for manipulating PDB data in XML format are available.

Proper citation: Protein Data Bank Markup Language (RRID:SCR_005085) Copy   

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http://ligand-expo.rutgers.edu/

An integrated data resource for finding chemical and structural information about small molecules bound to proteins and nucleic acids within the structure entries of the Protein Data Bank. Tools are provided to search the PDB dictionary for chemical components, to identify structure entries containing particular small molecules, and to download the 3D structures of the small molecule components in the PDB entry. A sketch tool is also provided for building new chemical definitions from reported PDB chemical components.

Proper citation: Ligand Expo (RRID:SCR_006636) Copy   

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http://www.nlm.nih.gov/

NLM collects, organizes, and makes available biomedical science information to scientists, health professionals, and the public. The Library's Web-based databases, including PubMed/Medline and MedlinePlus, are used extensively around the world. NLM conducts and supports research in biomedical communications; creates information resources for molecular biology, biotechnology, toxicology, and environmental health; and provides grant and contract support for training, medical library resources, and biomedical informatics and communications research. Celebrating its 175th anniversary in 2011, the National Library of Medicine (NLM), in Bethesda, Maryland, is a part of the National Institutes of Health, U.S. Department of Health and Human Services (HHS). Since its founding in 1836 as the library of the U.S. Army Surgeon General, NLM has played a pivotal role in translating biomedical research into practice. It is the world's largest biomedical library and the developer of electronic information services that deliver trillions of bytes of data to millions of users every day. Scientists, health professionals, and the public in the United States and around the globe search the Library's online information resources more than 1 billion times each year. The Library is open to all and has many services and resources for scientists, health professionals, historians, and the general public. NLM has over 17 million books, journals, manuscripts, audiovisuals, and other forms of medical information on its shelves, making it the largest health-science library in the world. In today's increasingly digital world, NLM carries out its mission of enabling biomedical research, supporting health care and public health, and promoting healthy behavior by: * Acquiring, organizing, and preserving the world's scholarly biomedical literature; * Providing access to biomedical and health information across the country in partnership with the 5,800-member National Network of Libraries of Medicine (NN/LM); * Serving as a leading global resource for building, curating and providing sophisticated access to molecular biology and genomic information, including those from the Human Genome Project and NIH Common Fund; * Creating high-quality information services relevant to toxicology and environmental health, health services research, and public health; * Conducting research and development on biomedical communications systems, methods, technologies, and networks and information dissemination and utilization among health professionals, patients, and the general public; * Funding advanced biomedical informatics research and serving as the primary supporter of pre- and post-doctoral research training in biomedical informatics at 18 U.S. universities.

Proper citation: National Library of Medicine (RRID:SCR_011446) Copy   

•   Source: SciCrunch Registry

http://www.glycosciences.de/modeling/pdb2mgif/

A web tool that takes a 3D structure (a PDB input file) and generates an animated image which can be displayed using any browser without the need for any additional molecular visualization software.

Proper citation: PDB2MultiGif (RRID:SCR_001489) Copy   

•   Source: SciCrunch Registry

http://dockground.bioinformatics.ku.edu/

Data sets, tools and computational techniques for modeling of protein interactions, including docking benchmarks, docking decoys and docking templates. Adequate computational techniques for modeling of protein interactions are important because of the growing number of known protein 3D structures, particularly in the context of structural genomics. The first release of the DOCKGROUND resource (Douguet et al., Bioinformatics 2006; 22:2612-2618) implemented a comprehensive database of cocrystallized (bound) protein-protein complexes in a relational database of annotated structures. Additional releases added features to the set of bound structures, such as regularly updated downloadable datasets: automatically generated nonredundant set, built according to most common criteria, and a manually curated set that includes only biological nonobligate complexes along with a number of additional useful characteristics. Also included are unbound (experimental and simulated) protein-protein complexes. Complexes from the bound dataset are used to identify crystallized unbound analogs. If such analogs do not exist, the unbound structures are simulated by rotamer library optimization. Thus, the database contains comprehensive sets of complexes suitable for large scale benchmarking of docking algorithms. Advanced methodologies for simulating unbound conformations are being explored for the next release. The Dockground project is developed by the Vakser lab at the Center for Bioinformatics at the University of Kansas. Parts of Dockground were co-developed by Dominique Douguet from the Center of Structural Biochemistry (INSERM U554 - CNRS UMR5048), Montpellier, France.

Proper citation: Dockground: Benchmarks, Docoys, Templates, and other knowledge resources for DOCKING (RRID:SCR_007412) Copy   

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http://www.glycosciences.de/database/start.php?action=form_pdb_data

Search for carbohydrate containing PDB entries by criteria like species or the compound / classification terms. You can choose predefined, frequent terms from the pull-down-menus or enter your own queries manually.

Proper citation: pdb-data (RRID:SCR_000386) Copy   

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http://consurfdb.tau.ac.il/

Provides pre-calculated evolutionary conservation profiles for proteins of known structure in the PDB. Enables flexibility in setting the parameters of the calculation, and accepts optional uploads of atomic coordinates, multiple sequence alignments, and phylogenetic trees for use in the calculation of conservation profiles.

Proper citation: ConSurf Database (RRID:SCR_002320) Copy   

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http://www.glycosciences.de/

Portal of glycoinformatics resources including databases and bioinformatics tools for glycobiology and glycomics research. Databases include a bibliography, structure, nuclear magnetic resonance (NMR), mass spectroscopy (ms) and a PDB search.

Proper citation: glycosciences.de (RRID:SCR_002324) Copy   

•   Source: SciCrunch Registry

http://restraintsgrid.bmrb.wisc.edu/NRG/MRGridServlet

Original NMR (nuclear magnetic resonance) data as collected for over 2500 protein and nucleic acid structures with corresponding PDB entries. In addition to the original restraints, most of the distance, dihedral angle and RDC restraint data (>85%) were parsed, and those in over 500 entries were converted and filtered. The converted and filtered data sets constitute the Database Of Converted Restraints (DOCR) and the Filtered Restraints Database (FRED) respectively as described in the references. There are 9,672,968 parsed constraints in 7159 entries. (Mar. 2013)

Proper citation: NMR Restraints Grid (RRID:SCR_006127) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/thornton-srv/databases/enzymes/

Database of known enzyme structures that have been deposited in the Protein Data Bank (PDB). The enzyme structures are classified by their E.C. number of the ENZYME Data Bank. Browse the classification hierarchy or enter an EC number or search-string. There are currently 45,638 PDB-enzyme entries in the PDB (as at 23 February, 2013) involving 38,109 separate PDB files - some files having more than one E.C. number associated with them.

Proper citation: Enzyme Structures Database (RRID:SCR_007125) Copy   

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http://www.ncbi.nlm.nih.gov/nucleotide

Database of nucleotide sequences from several sources, including GenBank, RefSeq, TPA and PDB. Genome, gene and transcript sequence data provide the foundation for biomedical research and discovery.

Proper citation: NCBI Nucleotide (RRID:SCR_004860) Copy   

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http://pcidb.russelllab.org/

The database of protein-chemical structural interactions includes all existing 3D structures of complexes of proteins with low molecular weight ligands. When one considers the proteins and chemical vertices of a graph, all these interactions form a network. Biological networks are powerful tools for predicting undocumented relationships between molecules. The underlying principle is that existing interactions between molecules can be used to predict new interactions. For pairs of proteins sharing a common ligand, we use protein and chemical superimpositions combined with fast structural compatibility screens to predict whether additional compounds bound by one protein would bind the other. The current version includes data from the Protein Data Bank as of August 2011. The database is updated monthly.

Proper citation: ProtChemSI (RRID:SCR_006115) Copy   

•   Source: SciCrunch Registry

http://dommino.org

DOMMINO is a comprehensive structural database on macromolecular interactions. As of June, 2011, it contains more than 407,000 binary interactions. The distinctive features of DOMMINO are: # Automated updates: DOMMINO is fully automated and is designed to update itself on a weekly basis, one day after a PDB weekly update. Thus, the community will be able to study macromolecular interactions almost immediately after they are released by PDB. # Coverage of non-domain mediated interactions: In addition to domain-domain and domain-peptide interactions the database characterizes the interaction between domains and unstructured protein regions that are not parts of a domain, such as inter-domain linkers and N- and C-termini. The interactions that involve the latter unstructured parts of proteins have been included to the database for the first time providing additional ~186,000 interactions (~45% of the total number of interactions, as of June, 2011). # Coverage of new structural domains: DOMMINO employs one of the most accurate structural classifications of proteins, SCOP. In addition to the existing SCOP-annotated domains, we employ a state-of-the-art machine learning approach to classify newer protein structures into existing SCOP families. With the progress of structural genomics, we do not expect a significant growth of the number of structurally novel folds or protein families and therefore our method allows covering almost all new protein structures. In total, using this predictive approach has allowed us to add more than 261,000 new interactions, almost twice as many as existing SCOP-annotated interactions. # The web-interface is designed to give the user a possibility of a flexible search as well as the capability to study macromolecular interactions in a PDB structure at the interaction network level and at the individual interface level. The web interface of the DOMMINO database includes a comprehensive list of help topics linked to the specific actions. In addition, we have designed a step-by-step tutorial that covers all aspects of working with the data from DOMMINO using the web interface.

Proper citation: DOMMINO - Database Of MacroMolecular INteractiOns (RRID:SCR_005958) Copy   

•   Source: SciCrunch Registry

http://pdbtm.enzim.hu/

Comprehensive and continuously updated transmembrane protein database of the Protein Data Bank (PDB) created by scanning all PDB entries with the TMDET algorithm. Resource for transmembrane proteins and their structures., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: PDBTM (RRID:SCR_011962) Copy   

•   Source: SciCrunch Registry

http://www.minas.uzh.ch/

Database compiling the detailed information on innersphere, outersphere and larger coordination environment of >70,000 metal ions of 36 elements found in >2000 structures of nucleic acids contained today in the PDB and NDB. MINAS is updated monthly with new structures and offers a multitude of search functions, e.g. the kind of metal ion, metal-ligand distance, innersphere and outersphere ligands defined by element or functional group, residue, experimental method, as well as PDB entry-related information. The results of each search can be saved individually for later use with so-called miniPDB files containing the respective metal ion together with the coordination environment within a 15 A radius. MINAS thus offers a unique way to explore the coordination geometries and ligands of metal ions together with the respective binding pockets in nucleic acids.

Proper citation: MINAS - Metal Ions in Nucleic AcidS (RRID:SCR_013145) Copy   

•   Source: SciCrunch Registry

http://www.csardock.org

Experimental datasets of crystal structures and binding affinities for diverse protein-ligand complexes. Some datasets are generated in house while others are collected from the literature or deposited by academic labs, national centers, and the pharmaceutical industry. For the community to improve their approaches, they need exceptional datasets to train scoring functions and develop new docking algorithms. They aim to provide the highest quality data for a diverse collection of proteins and small molecule ligands. They need input from the community in developing target priorities. Ideal targets will have many high-quality crystal structures (apo and 10-20 bound to diverse ligands) and affinity data for 25 compounds that range in size, scaffold, and logP. It is best if the ligand set has several congeneric series that span a broad range of affinity, with low nanomolar to mid-micromolar being most desirable. They prefer Kd data over Ki data over IC50 data (no % activity data). They will determine solubility, pKa, logP/logD data for the ligands whenever possible. They have augmented some donated IC50 data by determining Kon/Koff and ITC data.

Proper citation: Community Structure-Activity Resource (RRID:SCR_002206) Copy   

•   Source: SciCrunch Registry

http://www.pdbbind.org/

A database of binding affinities for the protein-ligand complexes in the Protein Data Bank (PDB). The PDBbind database is a collection of the experimentally measured binding affinities exclusively for the protein-ligand complexes available in the Protein Data Bank (PDB). It thus provides a link between energetic and structural information of those complexes and may be of great value to various molecular recognition studies. This site was last updated in 2007. The updated version of the resource is maintained by the Shanghai Institute of Organic Chemistry (http://www.pdbbind.org.cn).

Proper citation: Protein Data Bank Bind Database (RRID:SCR_008224) Copy   

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http://wwwmgs.bionet.nsc.ru/mgs/gnw/pdbsite/

Protein Data Bank (PDB) contains data on the spatial protein structures and their biologically active sites (i.e., ligand binding regions, enzyme catalytic centers, regions subjected to biochemical modifications, etc.). However, neither of the well known systems searching PDB does not provide the user with possibility to make the queries related with the active sites. A database PDBSITE storing the data on biologically active sites contained in the PDB database has been developed. PDBSITE accumulates amino acid content, structure features calculated by spatial protein structures, and physicochemical properties of sites and their spatial surroundings.

Proper citation: Protein Data Bank Site (RRID:SCR_008227) Copy   

•   Source: SciCrunch Registry