Exposing Hidden High-Affinity RNA Conformational States

Abstract

RNA recognition frequently results in conformational changes that optimize intermolecular binding. As a consequence, the overall binding affinity of RNA to its binding partners depends not only on the intermolecular interactions formed in the bound state but also on the energy cost associated with changing the RNA conformational distribution. Measuring these "conformational penalties" is, however, challenging because bound RNA conformations tend to have equilibrium populations in the absence of the binding partner that fall outside detection by conventional biophysical methods. In this study we employ as a model system HIV-1 TAR RNA and its interaction with the ligand argininamide (ARG), a mimic of TAR's cognate protein binding partner, the transactivator Tat. We use NMR chemical shift perturbations and relaxation dispersion in combination with Bayesian inference to develop a detailed thermodynamic model of coupled conformational change and ligand binding. Starting from a comprehensive 12-state model of the equilibrium, we estimate the energies of six distinct detectable thermodynamic states that are not accessible by currently available methods. Our approach identifies a minimum of four RNA intermediates that differ in terms of the TAR conformation and ARG occupancy. The dominant bound TAR conformation features two bound ARG ligands and has an equilibrium population in the absence of ARG that is below detection limit. Consequently, even though ARG binds to TAR with an apparent overall weak affinity (K_d^app ≈ 0.2 mM), it binds the prefolded conformation with a K_d in the nM range. Our results show that conformational penalties can be major determinants of RNA-ligand binding affinity as well as a source of binding cooperativity, with important implications for a predictive understanding of how RNA is recognized and for RNA-targeted drug discovery.

Figure 1.

NMR evidence for multi-site binding coupled with conformational equilibria. (A) Secondary structure of TAR construct used in this work. Red asterisk highlights residues that are particularly sensitive to temperature-dependent conformational equilibria and green asterisk highlights residues that show curved CSP trajectories indicating multiple binding sites. (B) Chemical structure of argininamide (ARG). (C) Chemical shifts as a function of ARG concentration at varying temperatures (blue, 1 °C to red, 25 °C) for representative resonances. Examples are shown for residues sensitive to multiple binding sites (A27-C8 and G28-C8) evidenced by curved CSP trajectories, and residues sensitive to conformational equilibria (U23-C1′ and G28-C8) evidenced by CSPs that vary significantly with temperature. Note that G28-C8 is sensitive to the BL₂ ⇌ CL₂ equilibria in addition to multi-site binding, while U23-C1′ reports on A ⇌ B but is almost entirely insensitive to BL₂ ⇌ CL₂. Shown are the aromatic C6/C8-H6/H8 (left) and sugar C1′-H1′ (right) spectra at 25 °C as a function of increasing ARG concentration showing that the peaks shift in accordance with fast exchange. Spectra of all raw data can be found in Figure S2. (D) Minimal six-state model consistent with the observed CSP trends. In lighter gray are the equilibria that complete the statistical thermodynamic description for a system with three conformations and two independent binding sites per conformation, giving a total of 12 possible RNA species. (E) Cartoon depictions of the three TAR conformational states discussed in the text.

Figure 2.

Evidence for bulge-dependent secondary binding site in the TAR upper helix. (A) Comparison of secondary structures of the TAR and the bulgeless mutant in the absence of ligand. Resonances colored in yellow correspond to the putative secondary binding site. (B) CSPs as a function of ARG concentration and temperature for residues that are sensitive to the bulge-dependent secondary binding site on TAR that is abolished in the bulgeless mutant. Color coding of temperatures follows that of Figure 1C. The data supports that the secondary binding site is localized to the upper helix region between residues A27 and G36. The curved trajectories seen for A27-C8 and G28-C8 in TAR indicate they are sensitive to both the α and β sites. This is consistent with previous results that the α site ARG is stacked above A22 and contacts G26 just below A27. Note that the chemical shifts for G36-C1′ and G36-C8 in TAR are only sensitive to the β site ligand.

Figure 3.

Bayesian global fitting of CSPs. (A) Representative fits to 10 resonances out of a global fitting set containing 54 resonances. Shown are the 95% confidence interval regions at each temperature. Fits for all 54 resonances included in the global fit are shown in Figure S8. The points and curves are colored from 1 °C (blue) to 25 °C (red). (B) Joint posterior distributions of thermodynamic parameters with marginal posterior distributions down the diagonal. (C) Marginal posterior distributions of ΔG values for the A ⇌ B and BL₂ ⇌ CL₂ reactions at each temperature. They are colored using the same color scheme used in panel A.

Figure 4.

Populations vs [ARG] for all species in the six-state model calculated using fitted parameter confidence intervals at 25 °C. The dotted line refers to the ~5% population cutoff for detection of species by the CSP titration method.

Figure 5.

Bayesian-fitted chemical shifts of intermediate species. (A) Comparison of chemical shift changes Δδ obtained for species B by Bayesian global fitting (green) with chemical shifts measured for ΔbulgeTAR in 25 mM NaCl (orange) and TAR in 25 mM NaCl plus 3 mM free MgCl₂ (buffer exchanged) (gray) for representative resonances. (B) Comparison of Δδ between species BL₂ (blue) and CL₂ (red) by Bayesian global fitting. The reference state is the unliganded A state and all Δδ are shown relative to the Bayesian-fitted δ_A values. Error bars represent the standard deviation determined by Bayesian fitting. (C) Schematic of the structural changes between the three different conformational states.

Figure 6.

Testing the model by NMR RD. (A) The predicted distribution of RNA states at the conditions under which the RD measurements were run (0.2 mM ARG, 1.5 mM RNA) at 5 and 25 °C. (B) Off-resonance RD data for the resonances with detectable chemical exchange at 5 °C. Lines represent global fit to BM equations. (C) Comparison of fitted chemical shifts obtained by RD with the chemical shifts obtained by Bayesian fitting to CSP data. Closest agreement is with chemical shifts for state BL_α, consistent with RD reporting on the binding to the α site in the B conformation.

Figure 7.

Energetic distributions of the six detectable RNA species showing the effect of ligand concentration on the RNA energy landscape. The violin plots show the ΔG posterior distributions calculated at 25 °C relative to the A state.