Knowledge-based selection of targets for structural genomics.
The problem of rational target selection for protein structure determination in structural genomics projects on microbes is addressed. A flexible computational procedure is described that directly incorporates the whole body of annotation available in the PEDANT genome database into the sequence clustering and selection process in order to identify proteins that are likely to possess currently unknown structural domains. Filtering out gene products based on predicted structural features, such as known three-dimensional structures and transmembrane regions, allows one to reduce the complexity of neighbor relationships between sequences and all but eliminates the need for further partitioning of single-linkage clusters into disjoint protein groups corresponding to homologous families. The results of a large-scale computation experiment in which exemplary target selection for 32 prokaryotic genomes was conducted are presented.
Frishman
Dmitrij
D
Institute for Bioinformatics, GSF-National Research Center for Environment and Health, Ingolstädter Landstrasse 1, 85764 Neuherberg, Germany. d.frishman@gsf.de
D000465:Algorithms; D001105:Archaea / Q000737:chemistry / Q000235:genetics; D001426:Bacterial Proteins / Q000737:chemistry / Q000235:genetics; D016000:Cluster Analysis; D030561:Databases, Nucleic Acid; D015195:Drug Design; D005051:Eubacterium / Q000737:chemistry / Q000235:genetics; D016680:Genome, Bacterial; D017434:Protein Structure, Tertiary
D001426:Bacterial Proteins