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

Databases of protein sequences and 3D structures of proteins. Collection of sequences from several sources, including translations from annotated coding regions in GenBank, RefSeq and TPA, as well as records from SwissProt, PIR, PRF, and PDB.

Proper citation: NCBI Protein Database (RRID:SCR_003257) Copy   

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http://cubic.bioc.columbia.edu/db/LOC3d/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 16, 2013. LOC3d is a database of predicted subcellular localization for eukaryotic proteins of known 3-D structure taken from the Protein Databank. Subcellular localization is currently predicted using four different methods: predictNLS (nuclear localization signal), LOChom (using homology), LOCkey (using keywords) and LOC3d (neural network based prediction). The reported localization is based on the method which predicts localization of a given protein with the highest confidence. LOCtree is a novel system of support vector machines (SVMs) that predict the subcellular localization of proteins, and DNA-binding propensity for nuclear proteins, by incorporating a hierarchical ontology of localization classes modeled onto biological processing pathways. Biological similarities are incorporated from the description of cellular components provided by the gene ontology consortium (GO). GO definitions have been simplified and tailored to the problem of protein sorting. Technically the ontology has been implemented using a decision tree with SVMs as the nodes. LOCtree, was extremely successful at learning evolutionary similarities among subcellular localization classes and was significantly more accurate than other traditional networks at predicting subcellular localization. Whenever available, LOCtree also reports predictions based on the following: 1) Nuclear localization signals found by PredictNLS, 2) Localization inferred using Prosite motifs and Pfam domains found in the protein, and 3) SWISS-PROT keywords associated with a protein. Localization is inferred in the last two cases using the entropy-based LOCkey algorithm. Additional information can be found in the LOCtree manuscript and associated PredictNLS and LOCkey publications.

Proper citation: Database oDatabase of Predicted Subcellular Localization for Eukaryotic PDB Chainsf Predicted Subcellular Localization for Eukaryotic PDB Chains (RRID:SCR_002831) Copy   

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http://biocomputer.bio.cuhk.edu.hk/T3DB/

Database aimed to annotate all bacterial Type III Secretion System (T3SS) related structure, effector, regulator, and auxiliary genes.

Proper citation: Type-III-Secretion-System related database (RRID:SCR_002941) Copy   

•   Source: SciCrunch Registry

http://integrativebiology.org/

Database for molecular interaction information integrated with various other bio-entity information, including pathways, diseases, gene ontology (GO) terms, species and molecular types. The information is obtained from several manually curated databases and automatic extraction from literature. There are protein-protein interaction, gene/protein regulation and protein-small molecule interaction information stored in the database. The interaction information is linked with relevant GO terms, pathway, disease and species names. Interactions are also linked to the PubMed IDs of the corresponding abstracts the interactions were obtained from. Manually curated molecular interaction information was obtained from BioGRID, IntAct, NCBI Gene, and STITCH database. Pathway related information was obtained from KEGG database, Pathway Interaction database and Reactome. Disease information was obtained from PharmGKB and KEGG database. Gene ontology terms and related information was obtained from Gene Ontology database and GOA database.

Proper citation: Integrated Molecular Interaction Database (RRID:SCR_003546) Copy   

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http://signalink.org/

An integrated resource to analyze signaling pathway cross-talks, transcription factors, miRNAs and regulatory enzymes. The multi-layered database structure is made up of signaling pathways, their pathway regulators (e.g., scaffold and endocytotic proteins) and modifier enzymes (e.g., phosphatases, ubiquitin ligases), as well as transcriptional and post-transcriptional regulators of all of these components. The website allows the interactive exploration of how each signaling protein is regulated. Features * experimental data not only from humans but from two invertebrate model organisms, C. elegans and D. melanogaster; * combines manual curation with large-scale datasets; * provides confidence scores for each interaction; * operates a customizable download page with multiple file formats (e.g., BioPAX, Cytoscape, SBML).

Proper citation: SignaLink (RRID:SCR_003569) Copy   

•   Source: SciCrunch Registry

http://abc.med.cornell.edu/pdzbase

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022.A manually curated protein-protein interaction database developed specifically for interactions involving PDZ domains. It currently contains 339 experimentally determined protein protein interactions.

Proper citation: PDZBase (RRID:SCR_003568) Copy   

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http://www.ebi.ac.uk/goldman-srv/pandit

PANDIT is a collection of multiple sequence alignments and phylogenetic trees covering many common protein domains. It contains: * the seed protein sequence alignments from the Pfam-A (curated families) database (version 17.0) * nucleotide sequence alignments derived from sequences available for the above and using the protein alignments as "templates"; * protein sequence alignments restricted to the family members for which nucleotide sequences are available * inferred phylogenetic trees for each alignment The data in PANDIT and the dataset's development have been frozen owing to a lack of funding support. The existing data, version 17.0 corresponding to Pfam 17.0, remain stable and, we hope, useful. The entire database is also available for download as a flatfile from this website.

Proper citation: PANDIT : Protein and Associated Nucleotide Domains with Inferred Trees (RRID:SCR_003321) Copy   

•   Source: SciCrunch Registry

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

Database of three-dimensional structures of macromolecules that allows the user to retrieve structures for specific molecule types as well as structures for genes and proteins of interest. Three main databases comprise Structure-The Molecular Modeling Database; Conserved Domains and Protein Classification; and the BioSystems Database. Structure also links to the PubChem databases to connect biological activity data to the macromolecular structures. Users can locate structural templates for proteins and interactively view structures and sequence data to closely examine sequence-structure relationships. * Macromolecular structures: The three-dimensional structures of biomolecules provide a wealth of information on their biological function and evolutionary relationships. The Molecular Modeling Database (MMDB), as part of the Entrez system, facilitates access to structure data by connecting them with associated literature, protein and nucleic acid sequences, chemicals, biomolecular interactions, and more. It is possible, for example, to find 3D structures for homologs of a protein of interest by following the Related Structure link in an Entrez Protein sequence record. * Conserved domains and protein classification: Conserved domains are functional units within a protein that act as building blocks in molecular evolution and recombine in various arrangements to make proteins with different functions. The Conserved Domain Database (CDD) brings together several collections of multiple sequence alignments representing conserved domains, in addition to NCBI-curated domains that use 3D-structure information explicitly to define domain boundaries and provide insights into sequence/structure/function relationships. * Small molecules and their biological activity: The PubChem project provides information on the biological activities of small molecules and is a component of NIH''''s Molecular Libraries Roadmap Initiative. PubChem includes three databases: PCSubstance, PCBioAssay, and PCCompound. The PubChem data are linked to other data types (illustrated example) in the Entrez system, making it possible, for example, to retrieve information about a compound and then Link to its biological activity data, retrieve 3D protein structures bound to the compound and interactively view their active sites, and find biosystems that include the compound as a component. * Biological Systems: A biosystem, or biological system, is a group of molecules that interact directly or indirectly, where the grouping is relevant to the characterization of living matter. The NCBI BioSystems Database provides centralized access to biological pathways from several source databases and connects the biosystem records with associated literature, molecular, and chemical data throughout the Entrez system. BioSystem records list and categorize components (illustrated example), such as the genes, proteins, and small molecules involved in a biological system. The companion FLink icon FLink tool, in turn, allows you to input a list of proteins, genes, or small molecules and retrieve a ranked list of biosystems.

Proper citation: NCBI Structure (RRID:SCR_004218) Copy   

•   Source: SciCrunch Registry

http://www.ibbl.lu/

An independent, not-for-profit biobanking and biotechnology foundation designed to facilitate new, high quality medical research. The IBBL collects, stores, and analyzes biological samples and associated data, which are then made available to research organizations investigating new treatments for diseases. It houses a biospecimen collection and biorepository that contains high quality tissues and maintains quality control of the specimens and the clinical data associated with the tissue samples, while maintaining biobanking ethical standards. It also provides biorefinery analyses and research services that can make analytes from tissues (e.g. DNA, RNA and protein), maintains technology for high throughput gene sequencing and gene expression, and conducts biospecimen research. An informatics platform maintains the clinical and biospecimens data in a secure fashion for additional analysis. Samples are collected by IBBL personnel from hospitals in a targeted manner. The IBBL collaborates with research and health organizations in North America, Europe and the Middle East, and with the major international biobanking societies.

Proper citation: Integrated Biobank of Luxembourg (RRID:SCR_004211) Copy   

•   Source: SciCrunch Registry

http://as-alps.nagahama-i-bio.ac.jp

This database, AS-ALPS (Alternative Splicing-induced ALteration of Protein Structure), is aimed at providing useful information to analyze effect of AS on protein interaction and network through alteration of protein structure. In AS-ALPS, regions of amino acid sequences changed by AS (AS regions) which are detected in human and mouse transcript sequences in H-InvDB, FANTOM and RefSeq, are linked to information extracted from PDB about residues forming hydrophobic cores and inter-molecular interaction sites. This makes it possible to directly infer whether protein structure and/or interaction are affected by each AS event. In addition, AS-ALPS provides links to a protein network database KEGG, making it easy to know which network and which node in the network can be influenced by AS. :Sponsors: This database was supported by a grant of the Genome Network Project from Ministry of Education, Culture, Sports, Science and Technology of Japan. :

Proper citation: Alternate Splicing - induced ALteration of Protein Structure (RRID:SCR_007554) Copy   

•   Source: SciCrunch Registry

http://blocks.fhcrc.org

Blocks is a database of highly conserved regions of proteins, or Blocks. THe database is no longer maintained or updated and some of its tools are no longer functional. However, Blocks does provide Block Searcher, Get Blocks and Block Maker, aids to detection and verification of protein sequence homology. They compare a protein or DNA sequence to a database of protein blocks (current version), retrieve blocks, and create new blocks, respectively. Users can further view blocks by (keyword or number), search a sequence against the database of blocks, search blocks against each other, or make blocks of their own.

Proper citation: Blocks (RRID:SCR_007567) Copy   

•   Source: SciCrunch Registry

http://pir.georgetown.edu/iprolink/biothesaurus

BioThesaurus is a web-based system designed to map a comprehensive collection of protein and gene names to UniProt Knowledgebase protein entries. It covers all UniProtKB protein entries, and consists of several millions of names extracted from multiple resources based on database cross-references in iProClass. The web site allows the retrieval of synonymous names of given protein entries and the identification of ambiguous names shared by multiple proteins. Searches can be done on protein/gene name, organism, or unique identifier.

Proper citation: BioThesaurus (RRID:SCR_007566) Copy   

•   Source: SciCrunch Registry

http://cmckb.cellmigration.org

It is a database of keys facts about proteins, families, and complexes involved in cell migration. This ongoing project provides a large amount of automated and curated data, collected from numerous online resources that are updated monthly. These data include names, synonyms, sequence information, summaries, CMC research data, reagents, structures, as well as protein family and complex details. CMKB''s ultimate goal is to create a database that will enable the cell migration community to conveniently access significant information about molecules of interest. This will also serve as a stepping stone to pathway analysis and demonstrate how these molecules coordinate with one another during cell adhesion and movement. Sponsors: This resource is supported by the Cell Migration Consortium.

Proper citation: CMKB (RRID:SCR_007229) Copy   

•   Source: SciCrunch Registry

http://posa.sanfordburnham.org/fatcat-cgi/cgi/FSN/fsn.pl

Flexible Structural Neighborhood is a database of structural neighbors of proteins as seen by FATCAT - a flexible protein structure alignment program. The server accepts either a protein (PDB ID) or a domain (SCOP ID) as a query. For the former case, the server first displays the information of chains and domains of a given protein. Afterwards, users can retrieve similar structures for a domain (if domain information is available, i.e., the protein is collected by SCOP), or for a chain otherwise. The protein structure database we collected for similar structure search includes a representative set at 90% sequence identity of SCOP domains, and of up-to-date PDB entries that are not included in the latest release of SCOP.

Proper citation: FATCAT Flexible Structural Neighborhood (RRID:SCR_007665) Copy   

•   Source: SciCrunch Registry

http://spock.genes.nig.ac.jp/~genome/gtop.html

GTOP is a database consists of data analyses of proteins identified by various genome projects. This database mainly uses sequence homology analyses and features extensive utilization of information on three-dimensional structures. GTOP is built by the Laboratory of Gene-Product Informatics at the National Institute of Genetics. This research is supported by the Japan Science and Technology Corporation and Grants-in-Aid for Scientific Research (Genomes in category C) from the Ministry of Education, Science, Sports and Culture of Japan. We use the following methods: Prediction of 3D structure Sequence homology search of PDB, using REVERSE PSI-BLAST. Functional predictions (family classifications) Sequence homology search of Swiss-Prot, a well-annotated sequence database, with the use of BLAST. Other analytical methods We are also carrying out the following analyses: Motif Analysis(PROSITE) Family classification(Pfam) Prediction of transmembrane helix domains(SOSUI) Prediction of coiled-coil regions(Multicoil) Repetitive sequence analysis(RepAlign)

Proper citation: GTOP - Genomes To Protein structures (RRID:SCR_007698) Copy   

•   Source: SciCrunch Registry

http://nectarmutation.org/main

A database and web application to annotate disease-related and functionally important amino acids in human proteins., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: NECTAR (RRID:SCR_007757) Copy   

•   Source: SciCrunch Registry

http://merops.sanger.ac.uk/

An information resource for peptidases (also termed proteases, proteinases and proteolytic enzymes) and the proteins that inhibit them. The MEROPS database uses an hierarchical, structure-based classification of the peptidases. In this, each peptidase is assigned to a Family on the basis of statistically significant similarities in amino acid sequence, and families that are thought to be homologous are grouped together in a Clan. There is a Summary page for each family and clan, and these have indexes. Each of the Summary pages offers links to supplementary pages. About 3000 individual peptidases and inhibitors are included in the database, and there is a Summary page describing each one. You can navigate to this by any of several routes. There are indexes of Name, MEROPS Identifier and source Organism on the menu bar. Each Summary page describes the classification and nomenclature of the peptidase or inhibitor, and provides links to supplementary pages showing sequence identifiers, the structure if known, literature references and more.

Proper citation: MEROPS (RRID:SCR_007777) Copy   

•   Source: SciCrunch Registry

http://www.mapuproteome.com

Database containing several body fluid proteomes, including plasma, urine, and cerebrospinal fluid. Cell lines have been mapped to a depth of several thousand proteins and the red blood cell proteome has also been analyzed in depth. The liver proteome is represented with 3200 proteins. By employing high resolution MS and stringent validation criteria, false positive identification rates in MAPU are lower than 1:1000. Thus MAPU datasets can serve as reference proteomes in biomarker discovery. MAPU contains the peptides identifying each protein, measured masses, scores and intensities using a clickable interface of cell or body parts. Proteome data can be queried across proteomes by protein name, accession number, sequence similarity, peptide sequence and annotation information. More than 4500 mouse and 2500 human proteins have already been identified in at least one proteome. Basic annotation information and links to other public databases are provided in MAPU and we plan to add further analysis tools.

Proper citation: Max Planck Unified Proteome Database (RRID:SCR_007771) Copy   

•   Source: SciCrunch Registry

https://leger2.helmholtz-hzi.de/cgi-bin/expLeger.pl

Knowledge database and visualization tool for comparative genomics of pathogenic and non-pathogenic Listeria species.Provides information on gene functions (as annotated or supposed by literature from homologous organisms) , protein expression levels under defined experimental conditions ,subcellular localization of proteins (expected and/or experimentally validated) , biological meaning of genes and proteins based on KEGG, InterPro and Gene Ontology.

Proper citation: LEGER: the post-genome Database for Listeria Research (RRID:SCR_007760) Copy   

•   Source: SciCrunch Registry

http://cbm.bio.uniroma2.it/surface

A database containing the results of a large-scale protein annotation and local structural comparison project. A non-redundant set of protein chains is used to build a database of protein surface patches, defined as putative surface functional sites. Each patch is annotated with sequence and structure-derived information about function or interaction abilities. Users can search the annotations and the results of the surface patches comparisons stored in the DB based on PDB code, PROSITE pattern, or ligand. A new procedure for structure comparison is used to exert an all-versus-all patches comparison. Selection of the results obtained with stringent parameters offers a similarity score that can be used to associate different patches and may allow reliable annotation by similarity. protein, protein structure, structural comparison, protein ligand, protein surface, protein morphology

Proper citation: SURFACE: Surface Residues and Functions Annotated, Compared and Evaluated (RRID:SCR_007953) Copy   

•   Source: SciCrunch Registry