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.

Link Function: information

The Molecular Modeling DataBase (MMDB), also known as Entrez Structure, is a database of experimentally determined structures obtained from the RCSB Protein Data Bank (PDB). MMDB is developed by the Structure Group of the NCBI Computational Biology Branch. The data processing procedure at NCBI results in the addition of a number of useful features that facilitate computation on the data and link them to many other data types in the Entrez system. The structure database is considerably smaller than Entrez''s Protein or Nucleotide databases, but a large fraction of all known protein sequences have homologs in this set, and one may often learn more about a protein by examining 3-D structures of its homologs. These are accessible as Related Structures in the Links menu of Entrez Protein sequence records (illustrated example). It is then possible to align the query protein to the structure-based sequence, as shown in the illustration on this page. Additional resources can be used along with MMDB to interactively view the structures, find similar 3D structures, learn about the types of interactions and bound chemicals that have been found to exist among the similar 3D structures, and more.

NCBIfam is a collection of protein families, featuring curated multiple sequence alignments, hidden Markov models (HMMs) and annotation, which provides a tool for identifying functionally related proteins based on sequence homology. NCBIfam is maintained at the National Center for Biotechnology Information (Bethesda, MD). NCBIfam includes models from TIGRFAMs, another database of protein families developed at The Institute for Genomic Research, then at the J. Craig Venter Institute (Rockville, MD, US).

CDD is a protein annotation resource that consists of a collection of annotated multiple sequence alignment models for ancient domains and full-length proteins. These are available as position-specific score matrices (PSSMs) for fast identification of conserved domains in protein sequences via RPS-BLAST. CDD content includes NCBI-curated domain models, which use 3D-structure information to explicitly define domain boundaries and provide insights into sequence/structure/function relationships, as well as domain models imported from a number of external source databases.

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.

The CATH-Gene3D database describes protein families and domain architectures in complete genomes. Protein families are formed using a Markov clustering algorithm, followed by multi-linkage clustering according to sequence identity. Mapping of predicted structure and sequence domains is undertaken using hidden Markov models libraries representing CATH and Pfam domains. CATH-Gene3D is based at University College, London, UK.

SFLD (Structure-Function Linkage Database) is a hierarchical classification of enzymes that relates specific sequence-structure features to specific chemical capabilities.

PROSITE is a database of protein families and domains. It consists of biologically significant sites, patterns and profiles that help to reliably identify to which known protein family a new sequence belongs. PROSITE is based at the Swiss Institute of Bioinformatics (SIB), Geneva, Switzerland.

Link Function: information

Custom Virus database A custom foldseek target database was created, including all protein sequences derived from plant-infecting viruses currently found in the NCBI RefSeq database. In total, 8,191 protein sequences were extracted and used as template for protein structure predictions. Colabfold v1.5.2 (using localcolabfold), which is based upon AlphaFold v2.3.1(40), was used for protein model prediction. Setting: --random-seed 101 --num-seeds 3 --use-dropout --num-models 1 --num-recycle 8 --recycle-early-stop-tolerance 0.5No templates were used during the protein model prediction. The uniref30_2302 and colabfold_envdb_202108 databases were used to generate the multiple sequence alignments (https://colabfold.mmseqs.com/)The predicted structures were filtered based on the pLDDT value, resulting in a set of 7545 protein structures with a pLDDT ≥ 50.## Filesmodelling_stats.txt < Tab seperated file containing the modelling statistics for each structure predictionpdb_files/all < folder containing all pdb files resulting from the structure predictionpdb_files/pLDDT50 < folder containing all pdb files resulting from the structure prediction having a pLDDT score of 50 or higherVIRAL_PROTEIN_PLANT_REFSEQ.fasta < fasta file contain all protein sequences extracted from plant infecting viral genomes uploaded in the NCBI RefSeq database

SMART (a Simple Modular Architecture Research Tool) allows the identification and annotation of genetically mobile domains and the analysis of domain architectures. SMART is based at EMBL, Heidelberg, Germany.

This search engine combs for information from over 30 major databases at NCBI, including PubMed, nucleic acids, amino acid sequences, expression data, PubChem (small molecules with biochemical functions), protein structure, sequenced genomes, and taxonomy. The search engine provides links to the search results, as well as to other related databases.

SUPERFAMILY is a library of profile hidden Markov models that represent all proteins of known structure. The library is based on the SCOP classification of proteins: each model corresponds to a SCOP domain and aims to represent the entire SCOP superfamily that the domain belongs to. SUPERFAMILY is based at the University of Bristol, UK.

PIRSF protein classification system is a network with multiple levels of sequence diversity from superfamilies to subfamilies that reflects the evolutionary relationship of full-length proteins and domains. PIRSF is based at the Protein Information Resource, Georgetown University Medical Centre, Washington DC, US.

This is a database of comparative protein structure models of MIP (Major Intrinsic Protein) family of proteins. The nearly completed sets of MIPs have been identified from the completed genome sequence of organisms available at NCBI. The structural models of MIP proteins were created by defined protocol. The database aims to provide key information of MIPs in particular based on sequence as well as structures. This will further help to decipher the function of uncharacterized MIPs. For each MIP entry, this database contains information about the source, gene structure, sequence features, substitutions in the conserved NPA motifs, structural model, the residues forming the selectivity filter and channel radius profile. For selected set of MIPs, it is possible to derive structure-based sequence alignment and evolutionary relationship. Sequences and structures of selected MIPs can be downloaded from MIPModDB database.

The gene database provides information on gene sequence, structure, location, and function for annotated genes from the NCBI database. Users can search by accession ID or keyword, compare and identify sequences using BLAST, or submit references into function (RIFs) based on experimental results. Bulk download and an update mailing list are available.

We describe a Bayesian Markov chain Monte Carlo (MCMC) sampler for protein multiple sequence alignment (MSA) that, as implemented in the program GISMO and applied to large numbers of diverse sequences, is more accurate than the popular MSA programs MUSCLE, MAFFT, Clustal-Ω and Kalign. Features of GISMO central to its performance are: (i) It employs a “top-down” strategy with a favorable asymptotic time complexity that first identifies regions generally shared by all the input sequences, and then realigns closely related subgroups in tandem. (ii) It infers position-specific gap penalties that favor insertions or deletions (indels) within each sequence at alignment positions in which indels are invoked in other sequences. This favors the placement of insertions between conserved blocks, which can be understood as making up the proteins’ structural core. (iii) It uses a Bayesian statistical measure of alignment quality based on the minimum description length principle and on Dirichlet mixture priors. Consequently, GISMO aligns sequence regions only when statistically justified. This is unlike methods based on the ad hoc, but widely used, sum-of-the-pairs scoring system, which will align random sequences. (iv) It defines a system for exploring alignment space that provides natural avenues for further experimentation through the development of new sampling strategies for more efficiently escaping from suboptimal traps. GISMO’s superior performance is illustrated using 408 protein sets containing, on average, 235 sequences. These sets correspond to NCBI Conserved Domain Database alignments, which have been manually curated in the light of available crystal structures, and thus provide a means to assess alignment accuracy. GISMO fills a different niche than other MSA programs, namely identifying and aligning a conserved domain present within a large, diverse set of full length sequences. The GISMO program is available at http://gismo.igs.umaryland.edu/.

A database of allergenic proteins. It contains various computational tools that can assist structural biology studies related to allergens. SDAP is an important tool in the investigation of the cross-reactivity between known allergens, in testing the FAO/WHO allergenicity rules for new proteins, and in predicting the IgE-binding potential of genetically modified food proteins. Using this Internet service through a browser, it is possible to retrieve information related to an allergen from the most common protein sequence and structure databases (SwissProt, PIR, NCBI, PDB), to find sequence and structural neighbors for an allergen, and to search for the presence of an epitope other the whole collection of allergens.

Links are provided to published protein structures for the apoenzyme DmdA from Pelagibacter ubique, as well as for DmdA co-crystals soaked with substrate DMSP or the cofactor tetrahydrofolate (THF) accessible via NCBI's Molecular Modeling Database (MMDB).

Experimental design, methods, and results are further described in:
D. J. Schuller, C. R. Reisch, M. A. Moran, W. B. Whitman, and W. N. Lanzilotta (2012). Structures of dimethylsulfoniopropionate-dependent demethylase from the marine organism Pelegabacter ubique. Protein Science, vol. 21, p. 289. doi: 10.1002/pro.2015