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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://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://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://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   

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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://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/tools/glyvicinity/

Service to generate statistics about the amino acids present in the vicinity of carbohydrate residues. Besides the amino acids in sequential neighborhood of glycosylation sites (analysed by GlySeq), those in the spatial vicinity of carbohydrate residues determine the characteristics of glycoproteins. The latter ones are of special interest for the examination of carbohydrate-binding proteins. Since carbohydrate moieties are not covalently bound in these cases, sequence analysis comparable to that for glycosylation sites is not possible there. GlyVicinity performs statistical analyses on the types of amino acids around carbohydrate chains and on the atoms forming the closest contacts between protein and carbohydrate residues. Results are based on weekly updated datasets derived from the Protein Data Bank (PDB).

Proper citation: GlyVicinity (RRID:SCR_001567) Copy   

•   Source: SciCrunch Registry

http://dknet.org/

The NIDDK Information Network (dkNET) is a community-based network to serve needs of basic and clinical investigators that includes large pools of data and research resources relevant to mission of National Institute of Diabetes and Digestive and Kidney Disease.

Proper citation: NIDDK Information Network (dkNET) (RRID:SCR_001606) 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://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   

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http://www.thesgc.org/

Charity registered in United Kingdom whose mission is to accelerate research in new areas of human biology and drug discovery.Not for profit, public-private partnership that carries out basic science of relevance to drug discovery whose core mandate is to determine 3D structures on large scale and cost effectively targeting human proteins of biomedical importance and proteins from human parasites that represent potential drug targets.

Proper citation: Structural Genomics Consortium (RRID:SCR_003890) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/pdbe/

The European resource for the collection, organization and dissemination of data on biological macromolecular structures. In collaboration with the other worldwide Protein Data Bank (wwPDB) partners - the Research Collaboratory for Structural Bioinformatics (RCSB) and BioMagResBank (BMRB) in the USA and the Protein Data Bank of Japan (PDBj) - they work to collate, maintain and provide access to the global repository of macromolecular structure data. The main objectives of the work at PDBe are: * to provide an integrated resource of high-quality macromolecular structures and related data and make it available to the biomedical community via intuitive user interfaces. * to maintain in-house expertise in all the major structure-determination techniques (X-ray, NMR and EM) in order to stay abreast of technical and methodological developments in these fields, and to work with the community on issues of mutual interest (such as data representation, harvesting, formats and standards, or validation of structural data). * to provide high-quality deposition and annotation facilities for structural data as one of the wwPDB deposition sites. Several sophisticated tools are also available for the structural analysis of macromolecules.

Proper citation: PDBe - Protein Data Bank in Europe (RRID:SCR_004312) Copy   

•   Source: SciCrunch Registry

http://polbase.neb.com/

Repository of biochemical, genetic, and structural information about DNA Polymerases. Polbase is designed to compile detailed results of polymerase experimentation, presenting them in a dynamic view to inform further research. After validation, results from references are displayed in context with relevant experimental details and are always traceable to their source publication. Polbase is connected to other resources, including PubMed, UniProt and the RCSB Protein Data Bank, to provide multi-faceted views of polymerase knowledge. In addition to a simple web interface, Polbase data is exposed for custom analysis by external software.

Proper citation: Polbase (RRID:SCR_006107) Copy   

•   Source: SciCrunch Registry

http://biodev.cea.fr/interevol/

InterEvol database is designed for the analysis of co-evolution events at the interface of known structures of hetero- and homo-oligomers. The database can be search and analyzed through 3 interconnected levels of analysis: * From a Keyword or the PDB entry of a complex, you can browse: ** structural homologs for every chain in other complexes ** structural interologs for every interface ** retrieve pre-computed sequence alignments in diverse species * From 1 or 2 sequences of interacting partners: ** build 2 multiple sequence alignments with the same species ordered in each ** query the InterEvol database with alignments using profile-profile comparison method * Visualize structure vs sequence alignment at the complex interface ** A dedicated Pymol plugin is provided ** Alignment views in Pymol are interactively restricted to the residues selected at the interface

Proper citation: InterEvol database (RRID:SCR_006054) 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   

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http://rnafrabase.ibch.poznan.pl/

Engine and database to search the three-dimensional fragments within 3D RNA structures using as an input the sequence(s) and / or secondary structure(s) given in the dot-bracket notation. The database contains RNA sequences and secondary structures, described in the dot-bracket notation, derived from PDB-deposited RNA structures and their complexes. It also contains atom coordinates of the unmodified and modified nucleotide and nucleoside residues extracted from the PDB-deposited RNA structures, as well as torsion and pseudotorsion angle values, sugar pucker parameters and classification of base pair types given for the PBD-deposited RNA structures. Knowledge of the three dimensional RNA structure is crucial for all fields of biomolecular research. In contrast to the protein field, only about 1.300 experimentally derived structures of RNAs are deposited in the Protein Data Bank (PDB). To complement the results of experimental studies, new approaches based on bioinformatics and calculation are pursued in several laboratories to make tertiary RNA structure prediction possible. RNA FRABASE version 2.0 should greatly facilitate various RNA structure modelling approaches, RNA structure analysis and motif searching. If one compares the three dimensional RNA structure to a spatial puzzle, the RNA FRABASE allows to pull out a defined piece of this puzzle - the 3D RNA fragment. The architecture of the web-accessible RNA FRABASE engine and database is based on the following information path: PDB-deposited RNA structures �� RNA sequences and secondary structures described in the dot-bracket notation �� secondary structures of RNA fragments �� 3D RNA fragments. RNA FRABASE 2.0 also stores data and conformational parameters in order to provide on the spot structural filters to explore the three-dimensional RNA structures. An instant visualization of the 3D RNA structures is provided.

Proper citation: RNA FRABASE - RNA FRAgments search engine and dataBASE (RRID:SCR_012808) Copy   

•   Source: SciCrunch Registry

http://hollow.sourceforge.net/

HOLLOW facilitates the production of surface images of proteins. HOLLOW is a portable command-line utility written in Python 2.4-2.7; it does not have any other dependencies (although running under the PyPy JIT interpreter, it runs much faster). The input is a PDB file. The output is a PDB file of dummy water atoms that forms a cast of the voids and channels of a protein. HOLLOW generates a surface from a cast of the protein surface. HOLLOW fills the interior spaces of a protein structure with dummy atoms defined on an overlapping grid. The surface generated by these dummy atoms can be shown to reproduce the surface of the protein at the ideal limit. The use of the surface of the dummy atoms allows us to focus on a specific piece of the interior surface. Simply by deleting dummy atoms, the interior surface can be trimmed to produce a custom portion of the interior space. For advanced coloring of the surface, the B-factor of the dummy atoms can be calculated as the average of the B-factor of the protein atoms surrounding the dummy atoms. This allows various colorings of the surface to be conveyed through the B-factor field of the PDB files. The volume filling representation facilitated by HOLLOW is meant to complement other programs that identify voids, pockets and channels, such as SPHGEN and CASTp, which identify binding sites but cannot produce output that can be rendered in standard molecular graphics software. HOLLOW can be used to help render these binding pockets.

Proper citation: HOLLOW (RRID:SCR_005729) Copy   

•   Source: SciCrunch Registry