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 LINUX clusters thus permitting its use on less expensive parallel architectures. The algorithm scales extremely well and is capable of running with hundreds of thousands of population elements 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 can 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. In general, STRUCTURELAB and other new tools we have developed, contain several features which when used together, act as set of data mining tools to aid in the discovery of patterns in databases of RNA secondary structures including RNA folding pathways. 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, IL2, and rotavirus. 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 molecules are being studied using molecular mechanics and molecular dynamics simulations. The structural motifs currently being studied, in addition to thymidylate synthase (mentioned above), include RNA tetraloops, bulge loops and three-way junctions that appear in structures such as the central domain of the 30S ribosomal subunit from Thermus thermophilus and structural motifs associated with telomerase. In the case of the ribosomal subunit, it has been experimentally determined that the intermolecular interactions between the three-way junction and the S15 ribosomal protein initiate the process of the assembly of the 30S ribosomal subunit. It remains however, to reveal the dynamic picture of the details of the three-way junction including its interaction with the S15 ribosomal protein and the conformational changes that take place at the atomic level associated with this protein interaction. By using molecular dynamics simulations we have obtained significant insights into the conformational transitions of the junction associated with the binding of S15. In addition, the molecular dynamics trajectories associated with temperature dependent denaturation of a tetra-loop and the subsequent refolding to the original crystal structure have been examined. The stablizing influence of the S15 ribosomal protein on the tetra-loop has been analyzed. In both of these cases, besides revealing new atomic level details, the structural transitions in these regions correspond to results derived from thermodynamic and biochemical experiments. We also modeled and applied molecular dynamics techniques to the HIV kissing loop structure and a portion of the HCV. These have lead to the understanding of subtle atomic level interactions that may ultimately be quite significant to the viral life cycles. In regard to telomerase, we have been studying the structural characteristics of the pseudoknot in telomerase which appears to have important relavence not only to cancer but for other genetic diseases. We have recently applied a somewhat different technique to generate feasible transition pathways between two different 3D conformations of RNA molecules. This utiltizes a methodology known as elastic network interpolation (ENI) which is also coupled with normal mode analysis. This methodology has been applied to the core central domain of the 16S ribosomal RNA. The pathways generated were quite accurate and were done much more quicky than with conventional molecular dynamics methods. This methodology is now being applied to other RNA molecules to understand the dynamic characteristics of RNA and how conformational changes in the RNA affect functionality.
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