Computational analysis and modeling of ribonucleic acid structure, function, and dynamics

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Background RNA plays a central role in cells. It is involved in all cellular processes, revealing a primordial arrival and universal biochemical properties. Its sequential nature makes it a simple device for storing genetic information. Its structure allows both to protect and expose its sequence and to present interaction surfaces facilitating its interaction with other molecules as well as buried binding sites that promote ion capture and catalysis. No other macromolecule allows for such a large structural and functional diversity. My research program has led to computer models and algorithms to predict RNA structure from sequence and structural data. Several research groups from the fields of RNA structure and biology have been using our software for decades. Our approach differs from that of others because we use symbolic calculations that integrate domain knowledge, thus defining a category of intelligent tools well suited to scientists. Our tools run from high-level physical model specifications, and interpret experimental data and formulate results in qualitative terms. Rationale & Aims One of the goals of RNA structure prediction is to identify the native state of a given RNA sequence. Prediction algorithms propose many 2D conformational states defined by different sets of base pairs. An objective function is used to score each state based on free energy derived from either thermodynamics or statistical parameters. The global aim of our research program is to predict RNA structure and function. Our approach is computational, as we implement, benchmark, and validate computational tools to analyse and model RNA structure from sequence data. We account for the physiological conditions by digging structural dynamics to identify functional motifs based on two hypotheses. First, sequence variations found in a family of homologous sequences are leaving evolutionary traces that relate to the physiological conditions in which they evolved. Second, these traces translate into structural elements, or motifs, which although rarely optimal reveal structural and functional determinants. Our specific goals are to: Aim 1: Improve structure prediction?Aim 2: Characterize functional determinants Aim 2: Characterize functional determinants Approach This research involves computational work that includes modeling (developing the model of RNA dynamics and implementing it by computer programming), benchmarking, as well as making predictions, which, along with experimental validation, lead to new discoveries. Significance We are at the beginning of an era where RNA will be at the heart of numerous new fascinating applications in environmental science, biotechnology and medicine. The results of this research program will provide the scientific community with computational tools and data to analyze and model RNA structure, function, and dynamics with unequaled precision.