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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://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   

•   Source: SciCrunch Registry

http://www.ucsd.edu/

The University of California, San Diego, also known as UC San Diego, is public research university located in the La Jolla neighborhood of San Diego, California, in the United States. Established in 1960, UCSD has 6 different campuses.

Proper citation: University of California at San Diego; California; USA (RRID:SCR_011625) Copy   

•   Source: SciCrunch Registry

http://www.emdataresource.org/

Portal for deposition and retrieval of cryo electron microscopy (3DEM) density maps, atomic models, and associated metadata. Global resource for 3 Dimensional Electron Microscopy structure data archiving and retrieval, news, events, software tools, data standards, validation methods.

Proper citation: EMDataResource.org (RRID:SCR_003207) Copy   

•   Source: SciCrunch Registry

https://bmrb.io

Public depository that collects, annotates, archives, and disseminates important spectral and quantitative data derived from nuclear magnetic resonance spectroscopic investigations of biological macromolecules and metabolites. Provides reference information and maintains a collection of NMR pulse sequences and computer software for biomolecular NMR.

Proper citation: Biological Magnetic Resonance Data Bank (BMRB) (RRID:SCR_002296) Copy   

•   Source: SciCrunch Registry

http://source.rcsb.org/jfatcatserver/ceHome.jsp

CE is a databases of alignments for all polypeptide chains. A representative set of proteins is available and kept current with the PDB, a method for calculating pairwise structure alignments. CE aligns two polypeptide chains using characteristics of their local geometry as defined by vectors between C alpha positions. Matches are termed aligned fragment pairs (AFPs). Heuristics are used in defining a set of optimal paths joining AFPs with gaps as needed. The path with the best RMSD is subject to dynamic programming to achieve an optimal alignment. For specific families of proteins additional characteristics are used to weight the alignment. Complete details are described in the paper (PDF format). Databases of alignments for all polypeptide chains and a representative set of proteins is available and kept current with the PDB

Proper citation: Combinatorial Extension (CE) (RRID:SCR_007585) Copy   

•   Source: SciCrunch Registry

https://neuinfo.org/mynif/search.php?list=cover&q=*

Service that partners with the community to expose and simultaneously drill down into individual databases and data sets and return relevant content. This type of content, part of the so called hidden Web, is typically not indexed by existing web search engines. Every record links back to the originating site. In order for NIF to directly query these independently maintained databases and datasets, database providers must register their database or dataset with the NIF Data Federation and specify permissions. Databases are concept mapped for ease of sharing and to allow better understanding of the results. Learn more about registering your resource, http://neuinfo.org/nif_components/disco/interoperation.shtm Search results are displayed under the Data Federation tab and are categorized by data type and nervous system level. In this way, users can easily step through the content of multiple resources, all from the same interface. Each federated resource individually displays their query results with links back to the relevant datasets within the host resource. This allows users to take advantage of additional views on the data and tools that are available through the host database. The NIF site provides tutorials for each resource, indicated by the Professor Icon professor icon showing users how to navigate the results page once directed there through the NIF. Additionally, query results may be exported as an Excel document. Note: NIF is not responsible for the availability or content of these external sites, nor does NIF endorse, warrant or guarantee the products, services or information described or offered at these external sites. Integrated Databases: Theses virtual databases created by NIF and other partners combine related data indexed from multiple databases and combine them into one view for easier browsing. * Integrated Animal View * Integrated Brain Gene Expression View * Integrated Disease View * Integrated Nervous System Connectivity View * Integrated Podcasts View * Integrated Software View * Integrated Video View * Integrated Jobs * Integrated Blogs For a listing of the Federated Databases see, http://neuinfo.org/mynif/databaseList.php or refer to the Resources Listed by NIF Data Federation table below.

Proper citation: NIF Data Federation (RRID:SCR_004834) Copy   

•   Source: SciCrunch Registry

http://www.bindingmoad.org/

Database of protein-ligand crystal structures that is a subset of the Protein Data Bank (PDB), containing every high-quality example of ligand-protein binding. The resolved protein crystal structures with clearly identified biologically relevant ligands are annotated with experimentally determined binding data extracted from literature. A viewer is provided to examine the protein-ligand structures. Ligands have additional chemical data, allowing for cheminformatics mining. The binding-affinity data ranges 13 orders of magnitude. The issue of redundancy in the data has also been addressed. To create a nonredundant dataset, one protein from each of the 1780 protein families was chosen as a representative. Representatives were chosen by tightest binding, best resolution, etc. For the 1780 best complexes that comprise the nonredundant version of Binding MOAD, 475 (27%) have binding data. This collection of protein-ligand complexes will be useful in elucidating the biophysical patterns of molecular recognition and enzymatic regulation. The complexes with binding-affinity data will help in the development of improved scoring functions and structure-based drug discovery techniques.

Proper citation: Binding MOAD (RRID:SCR_002294) Copy   

•   Source: SciCrunch Registry

http://metallo.scripps.edu/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on June 24, 2013. Database and Browser containing quantitative information on all the metal-containing sites available from structures in the PDB distribution. This database contains geometrical and molecular information that allows the classification and search of particular combinations of site characteristics, and answer questions such as: How many mononuclear zinc-containing sites are five coordinate with X-ray resolution better than 1.8 Angstroms?, and then be able to visualize and manipulate the matching sites. The database also includes enough information to answer questions involving type and number of ligands (e.g. "at least 2 His"), and include distance cutoff criteria (e.g. a metal-ligand distance no more than 3.0 Angstroms and no less than 2.2 Angstroms). This database is being developed as part of a project whose ultimate goal is metalloprotein design, allowing the interactive visualization of geometrical and functional information garnered from the MDB. The database is created by automatic recognition and extraction of metal-binding sites from metal-containing proteins. Quantitative information is extracted and organized into a searchable form, by iterating through all the entries in the latest PDB release (at the moment: September 2001). This is a comprehensive quantitative database, which exists in SQL format and contains information on about 5,500 proteins.

Proper citation: Metalloprotein Site Database (RRID:SCR_007780) Copy   

•   Source: SciCrunch Registry