This research project will use advanced fluorescence fluctuation spectroscopy (FFS) techniques combined with state-of-the-art biophysical theory and modeling to develop an elementary reaction rate model for intramolecular base-pairing and base-stacking in RNA secondary structure formation. The model to be developed will predict all experimentally observable kinetics properties of RNA secondary structure formation for any given sequence, including reaction rates, reaction mechanisms, and the structures and stabilities of the reaction intermediates. Development of the model will be based on experimental-theoretical comparisons of the folding and unfolding kinetics of designed RNA hairpins. Several competing theoretical reaction rate models will be used to predict the temperature dependent folding kinetics of the hairpins. The kinetics of these reactions will then be assessed experimentally using FFS. The experiments will measure reaction rates and identify reaction intermediates occurring over a broad range of time scales, from nanoseconds to hundreds of milliseconds. Different reaction rate models predict qualitatively and quantitatively different folding kinetics, including different Arrhenius plots, reaction intermediates, and reaction time scales. It is not possible to determine which reaction rate model is accurate based on theoretical calculations alone. Experimental comparisons to different model predictions will thus reveal which rate model is most consistent with experimental observations. Once the most likely model has been identified, it will be refined to account for the solvent viscosity, heat capacity, temperature, and counterion dependencies of the kinetic and thermodynamic parameters. The model will be validated by predicting the folding kinetics of RNA hairpins with arbitrary length and sequence and verifying the predictions experimentally. Modeling of more complicated tertiary structure forming RNA will proceed from that point.
The broader impacts of this project include the development of a model that can aid researchers in uncovering the biological function of any given RNA sequence. RNA is one of the fundamental molecular building blocks of living systems and plays a crucial role in a host of biological processes. This research will also contribute to the education and training of a new generation of scientists capable of applying rigorous quantitative experimental and theoretical research tools to important biological problems. Finally, new pedagogical materials based on this research will be developed for an emerging curriculum at the interface of the biological and physical sciences.
DNA and RNA are among the most important biological molecules in the cells of our bodies. These molecules can be thought of as chains where each link in the chain is one of four chemical bases. DNA and RNA molecules come in an almost infinite variety of chain lengths and chemical base sequences, each of which can carry out different functions in our cells. The picture gets even more complicated when we consider that the chemical bases within a chain can form bonded pairs with other bases within the same chain or different chains. This is the bases for the familiar DNA double helix held together by Watson-Crick base pairs in complimentary chains, but it can also give rise to a myriad of different RNA and DNA structures, ranging in size for single RNA or DNA chains, to complimentary pairs of RNA or DNA, to large complexes involving many DNA and RNA chains, as well as proteins and other molecules. Understanding how all of this works is extremely important for basic knowledge of biology, as well as diagnosing and treating diseases that occur when something goes wrong. One approach scientists are using to investigate the structures and behaviors of RNA and DNA is to develop computer models that can predict how an RNA or DNA molecule will behave given its size and sequence. This approach has distinct advantages because it eliminates the need to experiment on every possible DNA or RNA molecule, which would not be possible given their sheer number and complexity. Computer experiments can be carried out much quicker and on a much larger number of molecules than we could ever hope to accomplish in the laboratory. However, computer models require a very accurate knowledge of a few basic parameters, such as the attractive forces between the base pairs. If our knowldedge of these parameters is not accurate enough, the computer experiments will not give us the correct information and will not be useful. The best way to find the parameters needed by the computer models is through a type of feedback loop in which experiments are done to measure some of the necessary parameters, followed by computer models that use the measured parameters to predict the outcome of an experiment, followed by another experiment to test these outcomes, and so on. The NSF funded project described here has the goal of doing just that to predict the kinetics (that is the time dependence) for folding of various RNA and DNA hairpin molecules. The model parameters needed to accurately predict these kinetics are the activation energies for the formation and disruption of a DNA or RNA base-pair stack. What is activation energy and what is a base-pair stack? For any chemical reaction to occur, the reactant molecules need to absorb energy from their surroundings so they can adopt a configuration with the right amount of energy and the right arrangement of atoms for a reaction to proceed. This energy is called the activation energy. When you light a match to start a fire you are providing the activation energy for a combustion reaction to occur. Reactions involving DNA or RNA also require activation energy, and this parameter must be known for accurate computer modeling of DNA and RNA. A base-pair stack is the minimum number of adjacent base-pairs that can stabilize a DNA or RNA structure. During a reaction involving base-pairing of DNA or RNA, new base pair stacks are being formed and existing base-pair stacks are being dissociated. At present, it is believed the minimum size of a base pair stack is two adjacent base pairs. For accurate computer simulation of DNA and RNA, it is necessary to know the activation energy for the formation of a minimum base-pair stack, as well as the activation energy for the dissociation of a minimum base-pair stack. The goal of this project is to carry out the feedback loop described above to determine activation energies for formation and dissociation of a minumum base-pair stack. At Colorado State University, we have designed sophisticated new experimental techniques capable of carrying out this measurement. The actual measurements are not yet complete. They involve detection of millions of individual DNA and RNA molecules, one molecule at a time, in the hopes of observing a small number of these molecules undergoing a formation or dissociation reaction that can lead to a measurement of the activation energy. The design and building of the experimental apparatus has been completed and is now undergoing testing to ensure the measurements are accurate. Stay tuned for the next phase of this project when the measurements will be carried out for a variety of different RNA sequences, and used in computer simulations to predict the outcomes of new experiments.
