Targeting RNA Using Small Molecules

RNA secondary structure can be predicted using folding thermodynamics. Free energy minimization is commonly used to predict structures, but it only predicts about 70% of base pairs on average. Our group develops methods to improve the accuracy of structure prediction, including methods to estimate Boltzmann probabilities of structures, methods to predict conserved structures in multiple homologs, and methods to use experimental mapping data to improve modeling accuracy.

In this talk, I’ll present three new approaches we developed for RNA secondary structure prediction. We recently demonstrated that estimating the probability of loop formation can predict loops with higher fidelity than free energy minimization. We also developed a new method, called Rsample, to use SHAPE mapping data to model the structures of RNAs that fold to multiple structures. We can accurately model the structures, and also their population. Finally, we advanced our TurboFold method to predict conserved structures across multiple sequences. TurboFold now estimates multiple sequence alignments. It can also use SHAPE data for one or more homologs to improve the accuracy of structure prediction.

These methods are freely available in the RNAstructure software package, which can be downloaded at http://rna.urmc.rochester.edu .

RNA has been a long sought-after target for small molecules.  Three-dimensionally folded RNAs such as the bacterial ribosome and riboswitches are well known and validated targets for small molecules.  Human RNAs that contribute to disease, however, have been recalcitrant to small molecule targeting.  Our group has developed multiple approaches to efficiently deliver lead bioactive small molecules targeting RNA over the past dozen years.  Our non-traditional lead identification strategy uses selection-based approaches to assign affinity landscapes for the RNA motifs that are bound by small molecules.  These landscapes are defined by using a novel library-versus-library screening approach named Two-Dimensional Combinatorial Screening (2DCS), which probes libraries of small molecules for binding to libraries of RNA motifs simultaneously.  Although not highly regarded in its infancy, the developments of 2DCS and a computational approach dubbed Inforna that identifies druggable motifs derived from 2DCS in human RNAs, has delivered a myriad of lead small molecules that inhibit many human disease-causing RNAs in cellular and animal disease models.  Targets to which bioactive compounds have been delivered include RNA repeating transcripts that cause genetically-defined rare diseases and non-coding RNAs that cause cancer.  In this talk, I will describe the history of these approaches and also a first-class approach to validate the targets of small molecules, Chemical Cross-Linking and Isolation by Pull Down (Chem-CLIP).  Chem-CLIP has also defined rules for drugging non-coding RNAs, particularly microRNA precursors, that contribute to a myriad of diseases.  These studies have laid a foundation to rationally design small molecules targeting RNA by using non-traditional approaches and have delivered multiple bioactive compounds for diseases to which there are no known cures or that have poor prognoses.

Given the demonstrated importance and therapeutic potential of RNA biology in human health and disease, the dearth of studies aimed at targeting structured RNAs with small molecules is alarming. RNA remains a disproportionately under-explored target for drug discovery owing in part to the limited number of protein-centric assays currently employed for the discovery of new small molecules targeting RNA. Effective RNA-centric assays should instead account for the propensity of RNA to adopt alternative, non-functional conformers. These conformers present distinct binding sites which, when occupied with a small molecule, may preclude formation of the native structure. Yet high-throughput assays designed to explore RNA conformational space are not common.

We hypothesize that targeting the RNA folding process, in lieu of simple RNA binding analysis, will more thoroughly assess the ‘druggability’ of structured RNA targets of interest. We developed an efficient, high-throughput method to simultaneously screen chemical libraries and RNA structural space to discover novel chemical modulators of RNA structure and function. Using Förster resonance energy transfer (FRET), we generate multi-dimensional landscapes characterizing RNA conformations and thermodynamic stability. To demonstrate the utility of this approach we investigated landscapes of the cyclic di-GMP riboswitch in response to Mg2+, small molecule, and temperature. Our landscape analysis uncovers an otherwise hidden RNA-small molecule interaction that inhibits the function of this RNA through stabilization of a non-native conformation. Hence, targeting alternate conformers is a viable approach to discover new RNA-ligand interactions, highlighting how biophysics informs biology and therapeutic design.

According to World Health Organization, there were approximately 36.7 million people living with HIV at the end of 2015. Despite the success of combination antiretroviral therapy (cART), HIV/AIDS remains one of the world's most significant public health challenges. Ongoing challenges associated with HIV/AIDS include the complex regimen of antiretroviral therapy, cardiovascular and neurological complications associated with cART, and viral ability to require resistance due to high mutation rates. These issues require exploration of new viral targets and development of other therapies. HIV relies on a -1 ribosomal frameshift for the production of several essential viral proteins. This process is regulated by the HIV-1 Frameshifting Stimulatory Signal(FSS), a highly conserved 22 nt stemloop located downstream to a UUUUUUA “slippery sequence” that is also required for -1 ribosomal event to occur. There is a large body of evidence suggesting that targeting the HIV-1 FSS could be of therapeutic value. Since the HIV-1 FSS RNA contains a unique sequence with an extremely stable hairpin structure, we hypothesized that frameshifting can be targeted specifically without affecting normal cell physiology. Here, we synthetized and evaluated triazole-containing analogs of a hit compound determined previously via Dynamic Combinatorial Selection. Compounds demonstrated strong binding selectivity for the HIV-1 FSS, and antiviral activity against HIV in human cells including a highly cytopathic, multi-drug resistant strain.

While small molecules offer a unique opportunity to target structural and regulatory elements in therapeutically relevant RNA, selectivity has been a recurrent challenge in small molecule: RNA recognition. In particular, RNAs tend to be more dynamic and offer less chemical functionality than proteins, and biologically active ligands must compete with the highly abundant and highly structured RNA of the ribosome. Indeed, no small molecule drugs targeting RNAs other than the ribosome are currently available, and our recent survey of the literature revealed little more than one hundred reported chemical probes that target non-ribosomal RNA in biological systems. As part of our efforts to improve small molecule targeting strategies and gain fundamental insights into small molecule:RNA recognition, we are analyzing patterns in both RNA-biased small molecule chemical space and RNA topological space privileged for differentiation. To begin, we identified physicochemical, structural, and spatial properties properties of biologically active RNA ligands that are distinct from those of protein-targeted ligands. Elaboration of four RNA binding scaffolds into a library enriched with these properties has led to improved recognition of medicinally relevant RNA targets. At the same time, we used pattern recognition protocols to identify RNA topologies that can be differentially recognized by small molecules. We are currently expanding these studies with the ultimate goal of applying these insights to the rapid development of ligands with high affinity and specificity for a wide range of RNA targets, particularly those critical to cancer progression.

Riboswitches are non-coding RNA structures located in bacterial messenger RNAs that bind endogenous ligands, such as a specific metabolite or ion, to regulate gene expression. As such, riboswitches serve as a novel, yet largely unexploited, class of emerging drug targets. Demonstrating this potential, however, has proven difficult and is restricted to structurally similar antimetabolites and semi-synthetic analogs of their cognate ligand, thus greatly restricting the chemical space and selectivity sought for such inhibitors. We recently reported the discovery and characterization of ribocil, a highly selective chemical modulator of bacterial riboflavin (RF) riboswitches, which was identified in a phenotypic screen and acts as a structurally distinct synthetic mimic of the natural ligand, flavin mononucleotide (FMN), to repress riboswitch-mediated ribB gene expression and inhibit bacterial cell growth. Our findings indicate non-coding RNA structural elements may be more broadly targeted by synthetic small molecules than previously expected.

MicroRNAs (miRNA) are an emerging class of small RNAs that play critical roles in human development and disease. These micromanagers function at the level of post-transcriptional gene regulation, and alteration of miRNA expression levels have been implicated in cancer, obesity, diabetes, viral infections and autoimmune, neurodegenerative and cardiovascular diseases among others. As such, the targeting of miRNAs is considered attractive as a novel therapeutic strategy. A major bottleneck toward this goal, however, has been the identification of small molecule probes that are specific for select RNAs and methods that will facilitate such discovery efforts. Using pre-microRNAs as proof-of-concept, we have developed an innovative approach for assaying RNA-small molecule interactions that takes advantage of the power of catalytic signal amplification combined with the selectivity and bioorthogonality of click chemistry. Through this platform assay technology, which we term catalytic Enzyme-Linked Click Chemistry Assay or cat-ELCCA, we have designed a method that can be implemented in high-throughput, is virtually free of false read-outs and is general for all nucleic acids. Using cat-ELCCA, we are working toward the discovery of new chemical space for RNA to illuminate the druggability of this under-explored nucleic acid and provide the basis for the development of next-generation, RNA-targeted small molecule therapeutics for the management of human health. Our progress toward this goal will be discussed.