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a catalog of worldwide biological databases

The computational detection of similarities between protein 3D structures has become an indispensable tool for the detection of homologous relationships, the classification of protein families and functional inference. Consequently, numerous algorithms have been developed that facilitate structure comparison, including rapid searches against a steadily growing collection of protein structures. To this end, NCBI's Molecular Modeling Database (MMDB), which is based on the Protein Data Bank (PDB), maintains a comprehensive and up-to-date archive of protein structure similarities computed with the Vector Alignment Search Tool (VAST). These similarities have been recorded on the level of single proteins and protein domains, comprising in excess of 1.5 billion pairwise alignments. Here we present VAST+, an extension to the existing VAST service, which summarizes and presents structural similarity on the level of biological assemblies or macromolecular complexes. VAST+ simplifies structure neighboring results and shows, for macromolecular complexes tracked in MMDB, lists of similar complexes ranked by the extent of similarity. VAST+ replaces the previous VAST service as the default presentation of structure neighboring data in NCBI's Entrez query and retrieval system. MMDB and VAST+ can be accessed via http://www.ncbi.nlm.nih.gov/Structure.

Three-dimensional (3D) structure is now known for a large fraction of all protein families. Thus, it has become rather likely that one will find a homolog with known 3D structure when searching a sequence database with an arbitrary query sequence. Depending on the extent of similarity, such neighbor relationships may allow one to infer biological function and to identify functional sites such as binding motifs or catalytic centers. Entrez's 3D-structure database, the Molecular Modeling Database (MMDB), provides easy access to the richness of 3D structure data and its large potential for functional annotation. Entrez's search engine offers several tools to assist biologist users: (i) links between databases, such as between protein sequences and structures, (ii) pre-computed sequence and structure neighbors, (iii) visualization of structure and sequence/structure alignment. Here, we describe an annotation service that combines some of these tools automatically, Entrez's 'Related Structure' links. For all proteins in Entrez, similar sequences with known 3D structure are detected by BLAST and alignments are recorded. The 'Related Structure' service summarizes this information and presents 3D views mapping sequence residues onto all 3D structures available in MMDB (http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=structure).

Three-dimensional structures are now known within many protein families and it is quite likely, in searching a sequence database, that one will encounter a homolog with known structure. The goal of Entrez's 3D-structure database is to make this information, and the functional annotation it can provide, easily accessible to molecular biologists. To this end Entrez's search engine provides three powerful features. (i) Sequence and structure neighbors; one may select all sequences similar to one of interest, for example, and link to any known 3D structures. (ii) Links between databases; one may search by term matching in MEDLINE, for example, and link to 3D structures reported in these articles. (iii) Sequence and structure visualization; identifying a homolog with known structure, one may view molecular-graphic and alignment displays, to infer approximate 3D structure. In this article we focus on two features of Entrez's Molecular Modeling Database (MMDB) not described previously: links from individual biopolymer chains within 3D structures to a systematic taxonomy of organisms represented in molecular databases, and links from individual chains (and compact 3D domains within them) to structure neighbors, other chains (and 3D domains) with similar 3D structure. MMDB may be accessed at http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=Structure.

The three dimensional structures for representatives of nearly half of all protein families are now available in public databases. Thus, no matter which protein one investigates, it is increasingly likely that the 3D structure of a homolog will be known and may reveal unsuspected structure-function relationships. The goal of Entrez's 3D-structure database is to make this information accessible and usable by molecular biologists (http://www.ncbi.nlm.nih.gov/Entrez). To this end Entrez provides two major analysis tools, a search engine based on sequence and structure 'neighboring' and an integrated visualization system for sequence and structure alignments. From a protein's sequence 'neighbors' one may rapidly identify other members of a protein family, including those where 3D structure is known. By comparing aligned sequences and/or structures in detail, using the visualization system, one may identify conserved features and perhaps infer functional properties. Here we describe how these analysis tools may be used to investigate the structure and function of newly discovered proteins, using the PTEN gene product as an example.