Andrew C. Stelzer

Visualizing spatially correlated dynamics that directs RNA conformational transitions.

RNAs fold into three-dimensional (3D) structures that subsequently undergo large, functionally important, conformational transitions in response to a variety of cellular signals. RNA structures are believed to encode spatially tuned flexibility that can direct transitions along specific conformational pathways. However, this hypothesis has proved difficult to examine directly because atomic movements in complex biomolecules cannot be visualized in 3D by using current experimental methods. Here we report the successful implementation of a strategy using NMR that has allowed us to visualize, with complete 3D rotational sensitivity, the dynamics between two RNA helices that are linked by a functionally important trinucleotide bulge over timescales extending up to milliseconds. The key to our approach is to anchor NMR frames of reference onto each helix and thereby directly measure their dynamics, one relative to the other, using ‘relativistic’ sets of residual dipolar couplings (RDCs). Using this approach, we uncovered super-large amplitude helix motions that trace out a surprisingly structured and spatially correlated 3D dynamic trajectory. The two helices twist around their individual axes by approximately 53° and 110° in a highly correlated manner (R = 0.97) while simultaneously (R = 0.81–0.92) bending by about 94°. Remarkably, the 3D dynamic trajectory is dotted at various positions by seven distinct ligand-bound conformations of the RNA. Thus even partly unstructured RNAs can undergo structured dynamics that directs ligand-induced transitions along specific predefined conformational pathways.

Discovery of selective bioactive small molecules by targeting an RNA dynamic ensemble

Current approaches used to identify protein-binding small molecules are not suited for identifying small molecules that can bind emerging RNA drug targets. By docking small molecules onto an RNA dynamic ensemble constructed by combining NMR spectroscopy and computational molecular dynamics, we virtually screened small molecules that target the entire structure landscape of the transactivation response element (TAR) from HIV type 1 (HIV-1). We quantitatively predict binding energies for small molecules that bind different RNA conformations and report the de novo discovery of six compounds that bind TAR with high affinity and inhibit its interaction with a Tat peptide in vitro (K(i) values of 710 nM-169 μM). One compound binds HIV-1 TAR with marked selectivity and inhibits Tat-mediated activation of the HIV-1 long terminal repeat by 81% in T-cell lines and HIV replication in an HIV-1 indicator cell line (IC(50) ∼23.1 μM).

Constructing RNA dynamical ensembles by combining MD and motionally decoupled NMR RDCs: new insights into RNA dynamics and adaptive ligand recognition

We describe a strategy for constructing atomic resolution dynamical ensembles of RNA molecules, spanning up to millisecond timescales, that combines molecular dynamics (MD) simulations with NMR residual dipolar couplings (RDC) measured in elongated RNA. The ensembles are generated via a Monte Carlo procedure by selecting snap-shot from an MD trajectory that reproduce experimentally measured RDCs. Using this approach, we construct ensembles for two variants of the transactivation response element (TAR) containing three (HIV-1) and two (HIV-2) nucleotide bulges. The HIV-1 TAR ensemble reveals significant mobility in bulge residues C24 and U25 and to a lesser extent U23 and neighboring helical residue A22 that give rise to large amplitude spatially correlated twisting and bending helical motions. Omission of bulge residue C24 in HIV-2 TAR leads to a significant reduction in both the local mobility in and around the bulge and amplitude of inter-helical bending motions. In contrast, twisting motions of the helices remain comparable in amplitude to HIV-1 TAR and spatial correlations between them increase significantly. Comparison of the HIV-1 TAR dynamical ensemble and ligand bound TAR conformations reveals that several features of the binding pocket and global conformation are dynamically preformed, providing support for adaptive recognition via a ‘conformational selection’ type mechanism.

RNA Dynamics by Design: Biasing Ensembles Towards the Ligand-Bound State†

A major goal in structural biology and biophysics is to rationally design biomolecules that have specific characteristics at the atomic level. There have been significant advances in the design of proteins that fold into predetermined three-dimensional conformations.[1] However, biomolecular structures also undergo dynamic excursions about their native conformation and transiently access conformational substates that play critical roles in folding, catalysis, recognition, and signal transduction.[1–5] The rational design of such dynamics is a formidable challenge given the broad energy landscape that has to be considered and the complex spatiotemporal dependence of dynamics on sequence and structure, particularly for highly flexible molecules such as RNA.[6,7]

NMR studies of an immunomodulatory benzodiazepine binding to its molecular target on the mitochondrial F1F0-ATPase

Bz-423 is an inhibitor of the mitochondrial F(1)F(0)-ATPase, with therapeutic properties in murine models of immune diseases. Here, we study the binding of a water-soluble Bz-423 analog (5-(3-(aminomethyl)phenyl)-7-chloro- 1-methyl-3-(naphthalen-2-ylmethyl)-1H-benzo][e][1,4]diazepin-2(3H)-one); (1) to its target subunit on the enzyme, the oligomycin sensitivity conferring protein (OSCP), by NMR spectroscopy using chemical shift perturbation and cross-relaxation experiments. Titration experiments with constructs representing residues 1-120 or 1-145 of the OSCP reveals that (a) 1 binds to a region of the protein, at the minimum, comprising residues M51, L56, K65, V66, K75, K77, and N92, and (b) binding of 1 induces conformational changes in the OSCP. Control experiments employing a variant of 1 in which a key binding element on the small molecule was deleted; it had no perturbational effect on the spectra of the OSCP, which indicates that the observed changes with 1 represent specific binding interactions. Collectively, these data suggest that 1 might inhibit the enzyme through an allosteric mechanism where binding results in conformational changes that perturb the OSCP-F(1) interface resulting in disrupted communication between the peripheral stalk and the F(1)-domain of the enzyme.

Ultrahigh resolution characterization of domain motions and correlations by multialignment and multireference residual dipolar coupling NMR.

Nuclear magnetic resonance (NMR) residual dipolar couplings (RDCs) provide a unique opportunity for spatially characterizing complex motions in biomolecules with time scale sensitivity extending up to milliseconds. Up to five motionally averaged Wigner rotation elements, (D(0k)2(alphaalpha)), can be determined experimentally using RDCs measured in five linearly independent alignment conditions and applied to define motions of axially symmetric bond vectors. Here, we show that up to 25 motionally averaged Wigner rotation elements, (D(mk)2(alphabetagamma)), can be determined experimentally from multialignment RDCs and used to characterize rigid-body motions of chiral domains. The 25 (D(mk)2(alphabetagamma)) elements form a basis set that allows one to measure motions of a domain relative to an isotropic distribution of reference frames anchored on a second domain (and vice versa), thus expanding the 3D spatial resolution with which motions can be characterized. The 25 (D(mk)2(alphabetagamma)) elements can also be used to fit an ensemble consisting of up to eight equally or six unequally populated states. For more than two domains, changing the identity of the domain governing alignment allows access to new information regarding the correlated nature of the domain fluctuations. Example simulations are provided that validate the theoretical derivation and illustrate the high spatial resolution with which rigid-body domain motions can be characterized using multialignment and multireference RDCs. Our results further motivate the development of experimental approaches for both modulating alignment and anchoring it on specifically targeted domains.

Constructing Atomic-Resolution RNA Structural Ensembles Using MD and Motionally Decoupled NMR RDCs

A broad structural landscape often needs to be characterized in order to fully understand how regulatory RNAs perform their biological functions at the atomic level. We present a protocol for visualizing thermally accessible RNA conformations at atomic-resolution and with timescales extending up to milliseconds. The protocol combines molecular dynamics (MD) simulations with experimental residual dipolar couplings (RDCs) measured in partially aligned (13)C/(15)N isotopically enriched elongated RNA samples. The structural ensembles generated in this manner provide insights into RNA dynamics and its role in functionally important transitions.

Prediction of RNA 1H and 13C Chemical Shifts: A Structure Based Approach

The use of NMR-derived chemical shifts in protein structure determination and prediction has received much attention, and, as such, many methods have been developed to predict protein chemical shifts from three-dimensional (3D) coordinates. In contrast, little attention has been paid to predicting chemical shifts from RNA coordinates. Using the random forest machine learning approach, we developed RAMSEY, which is capable of predicting both (1)H and protonated (13)C chemical shifts from RNA coordinates. In this report, we introduce RAMSEY, assess its accuracy, and demonstrate the sensitivity of RAMSEY-predicted chemical shifts to RNA 3D structure.