SHV Lactamase Engineering Database: a reconciliation tool for SHV ß-lactamases in public databases.

BACKGROUND: SHV ß-lactamases confer resistance to a broad range of antibiotics by accumulating mutations. The number of SHV variants is steadily increasing. 117 SHV variants have been assigned in the SHV mutation table (http://www.lahey.org/Studies/). Besides, information about SHV ß-lactamases can be found in the rapidly growing NCBI protein database. The SHV ß-Lactamase Engineering Database (SHVED) has been developed to collect the SHV ß-lactamase sequences from the NCBI protein database and the SHV mutation table. It serves as a tool for the detection and reconciliation of inconsistencies, and for the identification of new SHV variants and amino acid substitutions. DESCRIPTION: The SHVED contains 200 protein entries with distinct sequences and 20 crystal structures. 83 protein sequences are included in the both the SHV mutation table and the NCBI protein database, while 35 and 82 protein sequences are only in the SHV mutation table and the NCBI protein database, respectively. Of these 82 sequences, 41 originate from microbial sources, and 22 of them are full-length sequences that harbour a mutation profile which has not been classified yet in the SHV mutation table. 27 protein entries from the NCBI protein database were found to have an inconsistency in SHV name identification. These inconsistencies were reconciled using information from the SHV mutation table and stored in the SHVED.The SHVED is accessible at http://www.LacED.uni-stuttgart.de/classA/SHVED/. It provides sequences, structures, and a multisequence alignment of SHV ß-lactamases with the corrected annotation. Amino acid substitutions at each position are also provided. The SHVED is updated monthly and supplies all data for download. CONCLUSIONS: The SHV ß-Lactamase Engineering Database (SHVED) contains information about SHV variants with reconciled annotation. It serves as a tool for detection of inconsistencies in the NCBI protein database, helps to identify new mutations resulting in new SHV variants, and thus supports the investigation of sequence-function relationships of SHV ß-lactamases.

DWARF--a data warehouse system for analyzing protein families.

BACKGROUND: The emerging field of integrative bioinformatics provides the tools to organize and systematically analyze vast amounts of highly diverse biological data and thus allows to gain a novel understanding of complex biological systems. The data warehouse DWARF applies integrative bioinformatics approaches to the analysis of large protein families. DESCRIPTION: The data warehouse system DWARF integrates data on sequence, structure, and functional annotation for protein fold families. The underlying relational data model consists of three major sections representing entities related to the protein (biochemical function, source organism, classification to homologous families and superfamilies), the protein sequence (position-specific annotation, mutant information), and the protein structure (secondary structure information, superimposed tertiary structure). Tools for extracting, transforming and loading data from public available resources (ExPDB, GenBank, DSSP) are provided to populate the database. The data can be accessed by an interface for searching and browsing, and by analysis tools that operate on annotation, sequence, or structure. We applied DWARF to the family of alpha/beta-hydrolases to host the Lipase Engineering database. Release 2.3 contains 6138 sequences and 167 experimentally determined protein structures, which are assigned to 37 superfamilies 103 homologous families. CONCLUSION: DWARF has been designed for constructing databases of large structurally related protein families and for evaluating their sequence-structure-function relationships by a systematic analysis of sequence, structure and functional annotation. It has been applied to predict biochemical properties from sequence, and serves as a valuable tool for protein engineering.