A complete understanding of the function of RNA molecules requires a knowledge of the higher order structures (2D and 3D) as well as the characteristics of their primary sequence. RNA structure is important for many functions, including regulation of transcription and translation, catalysis, and transport of proteins across membranes. The understanding of these functions are important for basic biology as well as for bioassays and the development of drugs that can intervene in cases where pathological functionality of these molecules occurs. This may include viruses such as HIV or expression pathways in malignant cells. We have developed and continue to improve upon an RNA folding technique that uses concepts from genetic algorithms. The algorithm was originally developed on a massively parallel SIMD (16,384 processors) MasPar and currently runs on parallel MIMD supercomputers. The algorithm can run on a single processor of an SGI OCTANE, a 64 processor SGI ORIGIN 3800 as well as a 512 processor CRAY T3E. Most recently a version has been adapted to run on a LINUX cluster thus permitting its use on less expensive parallel architectures. The algorithm scales extremely well and is capable of running with hundreds of thousands of virtual processors giving significant structural results when analyzed in the context of population variation. We are able to predict RNA pseudoknots and explore folding pathways that contain multiple functional conformations. In addition, the algorithm contains other features such as a Boltzmann relaxation technique, a choice of different energy rules, the ability to simulate sequential folding as well as sequential processing, forced/suggested and inhibited embedding of helical stems and the visualization of folding dynamics in real time. STRUCTURELAB, the heterogeneous bioinformatical RNA analysis workbench, which permits the use of a broad array of approaches for RNA structure analysis, has been continually enhanced. For example, it will generate refined 3D atomic coordinates of RNA structures along with the visualization of these structures. It also contains a novel interactive visualization methodology, STEM TRACE. This methodology enables the comparison and analysis of multiple sequence RNA folds from a phylogenetic point of view, thus allowing improvement of predicted structural results across a family of sequences. In addition, it permits the visualization of folding pathways when used in conjunction with the genetic algorithm (see above). It is also possible to produce motif patterns so that families of RNA sequences can be explored for common structural elements. These systems have been adapted to other environments inside and outside our laboratory and NIH and are available upon request. This system has been employed in studying RNA folding pathways and their functional intermediates as exemplified by the PSTV viroids and the hok/sok plasmid, both of which enter into intermediate states that are important for their life cycle. More recently the folding pathway of the HIV dimerization region has been studied in detail as well as HDV and IL2. We also studied the genetic mechanisms of the viral cardiovirulence phenotype of the coxsackie B viruses which includes mechanisms for transcription attenuation. In addition we studied the correlation of single stranded mutated p53 DNA structure and capillary electrophoresis; and the RNA/protein structural interactions between the enzyme thymidylate synthase (TS) and TS mRNA. In the latter, experiments have indicated that translation of human TS mRNA is controlled by an a negative autoregulatory mechanism with its own synthesized protein. The existence of these RNA/protein complexes have been found in human colon cancer cells. In order to understand RNA structures, folding pathways and the structural effects of RNA-Protein interactions at the atomic level, some structural elements of RNA m
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