Connecting protein family resourcesusing the proWeb network

We are developing a community website, called HDBase, to support basic scientific research on Huntington's Disease (HD). The core of the site is expert-reviewed scientific content consisting of curated bibliographies on topics of interest to HD researches and datasets extracted from those bibliographies. We are presently working on the following content areas: therapeutic studies in mouse, primarily drug screens; HD mouse models; antibodies used in HD research; large scale gene expression studies; and genes and proteins relevant to HD research. We work closely with other public databases to improve their HD coverage and try not to duplicate their efforts. The net effect is that much of our content actually exists as part of other databases. All of the software developed for this project is open source, and the data are similarly provided at no cost.

In the past few years, yeast and cultured cells have been the model systems of choice for the study of protein sorting and transport. Recently, there has been a surge in research in these areas in Caenorhabditis elegans, with advances in experimental techniques and genomics. New in vivo assays that monitor endocytosis and neuronal transport have been used to delineate roles for several genes in these processes.

In the wake of the numerous now-fruitful genome projects, we have witnessed a ‘tsunami’ of sequence data and with it the birth of the field of bioinformatics. Bioinformatics involves the application of information technology to the management and analysis of biological data. For many of us, this means that databases and their search tools have become an essential part of the research environment. However, the rate of sequence generation and the haphazard proliferation of databases have made it difficult to keep pace with developments, even for the cognoscenti. Moreover, increasing amounts of sequence information do not necessarily equate with an increase in knowledge, and in the panic to automate the route from raw data to biological insight, we may be generating and propagating innumerable errors in our precious databases. In the genome era upon us, researchers want rapid, easy-to-use, reliable tools for functional characterisation of newly determined sequences. For the pharmaceutical industry in particular, the Pandora's box of bioinformatics harbours an information-rich nugget, ripe with potential drug targets and possible new avenues for the development of therapeutic agents. This review outlines the current status of the major pattern databases now used routinely in the analysis of protein sequences. The review is divided into three main sections. In the first, commonly used terms are defined and the methods behind the databases are briefly described; in the second, the structure and content of the principal pattern databases are discussed; and in the final part, several alignment databases, which are frequently confused with pattern databases, are mentioned. For the new-comer, the array of resources, the range of methods behind them and the different tools required to search them can be confusing. The review therefore also briefly mentions a current international endeavour to integrate the diverse databases, which effort should facilitate sequence analysis in the future. This is particularly important for target-discovery programmes, where the challenge is to rationalise the enormous numbers of potential targets generated by sequence database searches. This problem may be addressed, at least in part, by reducing search outputs to the more focused and manageable subsets suggested by searches of integrated groups of family-specific pattern databases.