Protein structure methods as discussed in the previous sections can be employed in a variety of applications from whole genome analysis to detailed rational drug design projects. In basic research, protein structure prediction and the resulting structural models can help to assign possible functions of proteins and to better understand possible functional mechanisms and specificities, possibly in order to plan expression, mutation and recombination experiments, and understand genetic variation. In pharmaceutical and molecular medicine, research applications range from finding functional proteins in complex networks (probably with the help of new high throughput screening data, such as DNA expression measurements with arrays and chips) through the identification of possible drug target molecules, based on the protein function in metabolic and regulatory net-

gene expression data structure/function prediction

with predicted target protein experimental or modeled structure work contexts, to modeling detailed structures for rationally guiding and designing new drug molecules. Figure 6.6 gives a schematic overview of structure-based methods in a larger functional genomics and target-finding setup.

The following sections briefly discuss some results and trends in using structure prediction for remote homology detection especially in the genomic context, to aid the structural genomics projects, to further whole genome annotation and to exploit the sequence-to-structure-to-function paradigm for functional predictions.

Continue reading here: Remote homology detection

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