? The recent recognition of Bioinformatic approaches to both discovery, and hypothesis-based research, and the advent of multiple organismal sequencing projects demands new innovative directions in basic research. My overall research agenda is the study of the function, structure and evolution of all RNA-based life forms. One of the long-term goals of this proposal is to study the complexity of co-evolution among and between Retroid (i.e., genomes encoding the reverse transcriptase), and Eukaryotic genomes. The ongoing development of the genome parsing suite, GPS, provides the software necessary for these studies. Results of these analyses will be deposited in databases and linked to genome browsers of various organismal sequencing projects, providing a new tool for studying evolutionary processes. Retroid Agents play important roles in the development of Eukaryotes, and are involved in both host gene regulation and reproduction. Endogenous retroviruses have been associated with a variety of diseases such as multiple sclerosis, rheumatoid arthritis and schizophrenia. The second major goal of the proposal is a functional genomics approach to elucidate protein:protein contacts among the three proteins involved in the replication/transcription complex of the order Mononegavirales (e.g., rabies, measles and Ebola viruses) without knowledge of structural information. To date, little known about the distribution of functions within or the actual structure of, the replication/transcription complex of this order. The size of these complexes currently precludes traditional physical determination approaches (e.g., x-ray crystallography or NMR spectroscopy). The correlation of results from an approach that combines prediction of regions of protein disorder, as well as various types of evolutionary dynamic analyses, will allow the inference of amino acid residues that are probable candidates of contact. The use of a combined functional genome methods to elucidate potential protein:protein contacts without structural information is a new and important area of research. We will soon be deluged with higher order protein interaction data from proteomics projects for which there is little structural, but ample sequence data. Bringing the complexity of this problem to the attention of the Bioinformatic research community is necessary to accelerate progress in understanding the lifecycle of these medically important viruses, as well as in applications to proteomics projects. ? ?
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