PROSITE: a documented database using patterns and profiles as motif descriptors

Among the various databases dedicated to the identification of protein families and domains, PROSITE is the first one created and has continuously evolved since. PROSITE currently consists of a large collection of biologically meaningful motifs that are described as patterns or profiles, and linked to documentation briefly describing the protein family or domain they are designed to detect. The close relationship of PROSITE with the SWISS-PROT protein database allows the evaluation of the sensitivity and specificity of the PROSITE motifs and their periodic reviewing. In return, PROSITE is used to help annotate SWISS-PROT entries. The main characteristics and the techniques of family and domain identification used by PROSITE are reviewed in this paper.     

ProDom: automated clustering of homologous domains

The ProDom database is a comprehensive set of protein domain families automatically generated from the SWISS-PROT and TrEMBL sequence databases. An associated database, ProDom-CG, has been derived as a restriction of ProDom to completely sequenced genomes. The ProDom construction method is based on iterative PSI-BLAST searches and multiple alignments are generated for each domain family. The ProDom web server provides the user with a set of tools to visualise multiple alignments, phylogenetic trees and domain architectures of proteins, as well as a BLAST-based server to analyse new sequences for homologous domains. The comprehensive nature of ProDom makes it particularly useful to help sustain the growth of InterPro.     

An anatomofunctional brain database

This study proposes a closer look at the neuropsychological method defined as the study of the neural bases of the behavioural and cognitive functions using an organisation-representation model for current data and knowledge of the brain, and the application of an anatomofunctional database. A Centre of Cognitive Anatomy (CAC) was set up for the collection and processing of neuronatomical, neuropsychological, and psycho-behavioural data for patients presenting sequels of focal brain damage. Such a system would allow concurrent treatment of anatomical and functional data. We would expect the results from such a model to produce stable 'anatomofunctional laws' that would be independent of all inter-individual variations in the functioning of the brain and could be checked against the entire database of information. A direct application would be the improvement of cognitive and/or behavioural rehabilitation of patients with brain damage.     

Identification of protein functions from a molecular surface database,eF-site

A bioinformatics method was developed to identify the protein surface around the functional site and to estimate the biochemical function, using a newly constructed molecular surface database named the eF-site (electrostatic surface of Functional site. Molecular surfaces of protein molecules were computed based on the atom coordinates, and the eF-site database was prepared by adding the physical properties on the constructed molecular surfaces. The electrostatic potential on each molecular surface was individually calculated solving the Poisson–Boltzmann equation numerically for the precise continuum model, and the hydrophobicity information of each residue was also included. The eF-site database is accessed by the internet (http://pi.protein.osaka-u.ac.jp/eF-site/). We have prepared four different databases, eF-site/antibody, eF-site/prosite, eF-site/P-site, and eF-site/ActiveSite, corresponding to the antigen binding sites of antibodies with the same orientations, the molecular surfaces for the individual motifs in PROSITE database, the phosphate binding sites, and the active site surfaces for the representatives of the individual protein family, respectively. An algorithm using the clique detection method as an applied graph theory was developed to search of the eF-site database, so as to recognize and discriminate the characteristic molecular surfaces of the proteins. The method identifies the active site having the similar function to those of the known proteins.     

A phylogenetic supertree of the bats (Mammalia: Chiroptera)

We present the first estimate of the phylogenetic relationships among all 916 extant and nine recently extinct species of bats Mammalia: Chiroptera), a group that accounts for almost one-quarter of extant mammalian diversity. This phylogeny was derived by combining 105 estimates of bat phylogenetic relationships published since 1970 using the supertree construction technique of Matrix Representation with Parsimony (MRP). Despite the explosive growth in the number of phylogenetic studies of bats since 1990, phylogenetic relationships in the order have been studied non-randomly. For example, over one-third of all bat systematic studies to date have locused on relationships within Phyllostomidae, whereas relationships within clades such as Kerivoulinae and Murinae have never been studied using cladistic methods. Resolution in the supertree similarly differs among clades: overall resolution is poor (46.4%, of a fully bifurcating solution) but reaches 100% in some groups (e.g. relationships within Mormoopidae). The supertree analysis does not support a recent proposal that Microchiroptera is paraphyletic with respect to Megachiroptera, as the majority of source topologies support microbat monophyly. Although it is not a substitute for comprehensive phylogenetic analyses of primary molecular and morphological data, the bat supertree provides a useful tool for future phylogenetic comparative and macroevolutionary studies. Additionally, it identifies clades that have been little studied, highlights groups within which relationships are controversial, and like all phylogenetic studies, provides preliminary hypotheses that can form starting points for future phylogenetic studies of bats.     

Expanding the nitrogen regulatory protein superfamily: Homology detection at below random sequence identity

Nitrogen regulatory (PII) proteins are signal transduction molecules involved in controlling nitrogen metabolism in prokaryots. PII proteins integrate the signals of intracellular nitrogen and carbon status into the control of enzymes involved in nitrogen assimilation. Using elaborate sequence similarity detection schemes, we show that five clusters of orthologs (COGs) and several small divergent protein groups belong to the PII superfamily and predict their structure to be a (betaalphabeta)(2) ferredoxin-like fold. Proteins from the newly emerged PII superfamily are present in all major phylogenetic lineages. The PII homologs are quite diverse, with below random (as low as 1%) pairwise sequence identities between some members of distant groups. Despite this sequence diversity, evidence suggests that the different subfamilies retain the PII trimeric structure important for ligand-binding site formation and maintain a conservation of conservations at residue positions important for PII function. Because most of the orthologous groups within the PII superfamily are composed entirely of hypothetical proteins, our remote homology-based structure prediction provides the only information about them. Analogous to structural genomics efforts, such prediction gives clues to the biological roles of these proteins and allows us to hypothesize about locations of functional sites on model structures or rationalize about available experimental information. For instance, conserved residues in one of the families map in close proximity to each other on PII structure, allowing for a possible metal-binding site in the proteins coded by the locus known to affect sensitivity to divalent metal ions. Presented analysis pushes the limits of sequence similarity searches and exemplifies one of the extreme cases of reliable sequence-based structure prediction. In conjunction with structural genomics efforts to shed light on protein function, our strategies make it possible to detect homology between highly diverse sequences and are aimed at understanding the most remote evolutionary connections in the protein world.     

Pharmacophore-based molecular docking to account for ligand flexibility

Rapid computational mining of large 3D molecular databases is central to generating new drug leads. Accurate virtual screening of large 3D molecular databases requires consideration of the conformational flexibility of the ligand molecules. Ligand flexibility can be included without prohibitively increasing the search time by docking ensembles of precomputed conformers from a conformationally expanded database. A pharmacophore-based docking method whereby conformers of the same or different molecules are overlaid by their largest 3D pharmacophore and simultaneously docked by partial matches to that pharmacophore is presented. The method is implemented in DOCK 4.0.     

Mining of assembled expressed sequence tag (EST) data for protein families: application to the G protein-coupled receptor superfamily

The availability of large expressed sequence tag (EST) databases has led to a revolution in the way new genes are identified. Mining of these databases using known protein sequences as queries is a powerful technique for discovering orthologous and paralogous genes. The scientist is often confronted, however, by an enormous amount of search output owing to the inherent redundancy of EST data. In addition, high search sensitivity often cannot be achieved using only a single member of a protein superfamily as a query. In this paper a technique for addressing both of these issues is described. Assembled EST databases are queried with every member of a protein superfamily, the results are integrated and false positives are pruned from the set. The result is a set of assemblies enriched in members of the protein superfamily under consideration. The technique is applied to the G protein-coupled receptor (GPCR) superfamily in the construction of a GPCR Resource. A novel full-length human GPCR identified from the GPCR Resource is presented, illustrating the utility of the method.     

HOMSTRAD: a database of protein structure alignments for homologous families.

We describe a database of protein structure alignments for homologous families. The database HOMSTRAD presently contains 130 protein families and 590 aligned structures, which have been selected on the basis of quality of the X-ray analysis and accuracy of the structure. For each family, the database provides a structure-based alignment derived using COMPARER and annotated with JOY in a special format that represents the local structural environment of each amino acid residue. HOMSTRAD also provides a set of superposed atomic coordinates obtained using MNYFIT, which can be viewed with a graphical user interface or used for comparative modeling studies. The database is freely available on the World Wide Web at: http://www-cryst.bioc.cam. ac.uk/-homstrad/, with search facilities and links to other databases.