Structure and Dynamics Based Methods Targeting RNA

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As non-coding RNAs are increasingly implicated in cellular regulatory functions and disease states, there is a need to deepen our understanding of RNA structure-function relationships as well as to develop methods targeting RNA with small molecules. The transactivation response element (TAR) RNA from human immunodeficiency virus type 1 (HIV-1) is an established drug target for the development of anti-HIV therapeutics and has served as a model system for understanding RNA dynamics and RNA:ligand interactions. Like many RNAs, HIV-1 TAR is a highly flexible molecule that experiences dynamics ranging from local fluctuations in base orientation and interhelical angles to higher-order dynamics that transiently alter base pairing away from the ground state (GS) secondary structure. The work presented in this thesis is aimed at developing approaches targeting TAR with small molecules that integrate its broad range of structural dynamics.

First, nuclear magnetic resonance (NMR) chemical shift mapping is applied in concert with fluorescence binding assays and computational docking to efficiently characterize the TAR-binding modes of a focused library of amiloride derivatives. Through this work, amiloride is established as a novel RNA binding scaffold with interesting structure-activity relationships. Ultimately, this approach yielded ten novel TAR binders with demonstrated selectivity for TAR over tRNA and with up to a 100-fold increase in activity over the parent dimethyl amiloride compound.

Next, we demonstrate that ensemble-based virtual screening (EBVS) is a powerful approach to predict ligand binding for flexible RNA targets. Here, we generate a library to evaluate EBVS enrichment by subjecting HIV-1 TAR to experimental high-throughput screening against ~100,000 drug-like small molecules. EBVS against a dynamic ensemble of the TAR GS determined previously by combining NMR spectroscopy data and molecular dynamics (MD) simulations scores hits and non-hits with an area under the receiver operator characteristic curve of ~0.85-0.94 and with ~40-75% of all hits falling within the top 2% of scored molecules. Importantly, the enrichment was shown to depend on the accuracy of the ensemble.

Finally, we explore the novel strategy of specifically targeting non-native RNA excited state conformations inspired by the fact that their altered secondary structures are likely functionally inactive and highly unique. We use a mutational stabilize-and-rescue approach to demonstrate that TAR ES2 dramatically inhibits TAR activity in cells, suggesting that stabilizing the ES conformation with small molecules would similarly inhibit activity. To pursue TAR ES2 as a potential target, we have determined the first-ever dynamic ensemble of an RNA ES using a combination of MD and NMR residual dipolar couplings (RDCs) measured on a highly accurate ES2-stabilizing mutant. This dynamic ensemble was subjected to our validated EBVS approach to identify small molecules that bind and stabilize TAR ES2. Using NMR chemical shift fingerprinting, we have identified molecules that bind the TAR ES2 structure, including two that induce significant broadening in wtTAR consistent with chemical exchange and two that show a preference for TAR ES2 over the GS.

Together, this work explores multiple novel strategies for structure-specific RNA targeting.






Ganser, Laura R (2019). Structure and Dynamics Based Methods Targeting RNA. Dissertation, Duke University. Retrieved from


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