Folding kinetics for the conformational switch between alternative RNA structures

Protein dynamics and function from solution state NMR spectroscopy

It is well-established that dynamics are central to protein function; their importance is implicitly acknowledged in the principles of the Monod, Wyman and Changeux model of binding cooperativity, which was originally proposed in 1965. Nowadays the concept of protein dynamics is formulated in terms of the energy landscape theory, which can be used to understand protein folding and conformational changes in proteins. Because protein dynamics are so important, a key to understanding protein function at the molecular level is to design experiments that allow their quantitative analysis. Nuclear magnetic resonance (NMR) spectroscopy is uniquely suited for this purpose because major advances in theory, hardware, and experimental methods have made it possible to characterize protein dynamics at an unprecedented level of detail. Unique features of NMR include the ability to quantify dynamics (i) under equilibrium conditions without external perturbations, (ii) using many probes simultaneously, and (iii) over large time intervals. Here we review NMR techniques for quantifying protein dynamics on fast (ps-ns), slow (μs-ms), and very slow (s-min) time scales. These techniques are discussed with reference to some major discoveries in protein science that have been made possible by NMR spectroscopy.

Kinetic mechanism of conformational switch between bistable RNA hairpins

Transitions between the different conformational states play a critical role in many RNA catalytic and regulatory functions. In this study, we use the Kinetic Monte Carlo method to investigate the kinetic mechanism for the conformational switches between bistable RNA hairpins. We find three types of conformational switch pathways for RNA hairpins: refolding after complete unfolding, folding through basepair-exchange pathways and through pseudoknot-assisted pathways, respectively. The result of the competition between the three types of pathways depends mainly on the location of the rate-limiting base stacks (such as the GC base stacks) in the structures. Depending on the structural relationships between the two bistable hairpins, the conformational switch can follow single or multiple dominant pathways. The predicted folding pathways are supported by the activation energy results derived from the Arrhenius plot as well as the NMR spectroscopy data.

Squaring theory with practice in RNA design

Ribonucleic acid (RNA) design offers unique opportunities for engineering genetic networks and nanostructures that self-assemble within living cells. Recent years have seen the creation of increasingly complex RNA devices, including proof-of-concept applications for in vivo three-dimensional scaffolding, imaging, computing, and control of biological behaviors. Expert intuition and simple design rules--the stability of double helices, the modularity of noncanonical RNA motifs, and geometric closure--have enabled these successful applications. Going beyond heuristics, emerging algorithms may enable automated design of RNAs with nucleotide-level accuracy but, as illustrated on a recent RNA square design, are not yet fully predictive. Looking ahead, technological advances in RNA synthesis and interrogation are poised to radically accelerate the discovery and stringent testing of design methods.

Rational truncation of an RNA aptamer to prostate-specific membrane antigen using computational structural modeling

RNA aptamers represent an emerging class of pharmaceuticals with great potential for targeted cancer diagnostics and therapy. Several RNA aptamers that bind cancer cell-surface antigens with high affinity and specificity have been described. However, their clinical potential has yet to be realized. A significant obstacle to the clinical adoption of RNA aptamers is the high cost of manufacturing long RNA sequences through chemical synthesis. Therapeutic aptamers are often truncated postselection by using a trial-and-error process, which is time consuming and inefficient. Here, we used a "rational truncation" approach guided by RNA structural prediction and protein/RNA docking algorithms that enabled us to substantially truncateA9, an RNA aptamer to prostate-specific membrane antigen (PSMA),with great potential for targeted therapeutics. This truncated PSMA aptamer (A9L; 41mer) retains binding activity, functionality, and is amenable to large-scale chemical synthesis for future clinical applications. In addition, the modeled RNA tertiary structure and protein/RNA docking predictions revealed key nucleotides within the aptamer critical for binding to PSMA and inhibiting its enzymatic activity. Finally, this work highlights the utility of existing RNA structural prediction and protein docking techniques that may be generally applicable to developing RNA aptamers optimized for therapeutic use.

Identifying complete RNA structural ensembles including pseudoknots

The close relationship between RNA structure and function underlines the significance of accurately predicting RNA structures from sequence information. Structural topologies such as pseudoknots are of particular interest due to their ubiquity and direct involvement in RNA function, but identifying pseudoknots is a computationally challenging problem and existing heuristic approaches usually perform poorly for RNA sequences of even a few hundred bases. We survey the performance of pseudoknot prediction methods on a data set of full-length RNA sequences representing varied sequence lengths, and biological RNA classes such as RNase P RNA, Group I Intron, tmRNA and tRNA. Pseudoknot prediction methods are compared with minimum free energy and suboptimal secondary structure prediction methods in terms of correct base-pairs, stems and pseudoknots and we find that the ensemble of suboptimal structure predictions succeeds in identifying correct structural elements in RNA that are usually missed in MFE and pseudoknot predictions. We propose a strategy to identify a comprehensive set of non-redundant stems in the suboptimal structure space of a RNA molecule by applying heuristics that reduce the structural redundancy of the predicted suboptimal structures by merging slightly varying stems that are predicted to form in local sequence regions. This reduced-redundancy set of structural elements consistently outperforms more specialized approaches.in data sets. Thus, the suboptimal folding space can be used to represent the structural diversity of an RNA molecule more comprehensively than optimal structure prediction approaches alone.

Mapping the landscape of RNA dynamics with NMR spectroscopy

Among the three major classes of biomacromolecules (DNA, RNA, and proteins) RNA's pronounced dynamics are the most explicitly linked to its wide variety of functions, which include catalysis and the regulation of transcription, translation, and splicing. These functions are mediated by a range of RNA biomachinery, including such varied examples as macromolecular noncoding RNAs, microRNAs, small interfering RNAs, riboswitch RNAs, and RNA thermometers. In each case, the functional dynamics of an interconversion is characterized by an associated rate constant. In this Account, we provide an introduction to NMR spectroscopic characterization of the landscape of RNA dynamics. We introduce strategies for measuring NMR parameters at various time scales as well as the underlying models for describing the corresponding rate constants. RNA exhibits significant dynamic motion, which can be modulated by (i) intermolecular interactions, including specific and nonspecific binding of ions (such as Mg(2+) and tertiary amines), (ii) metabolites in riboswitches or RNA aptamers, and (iii) macromolecular interactions within ribonucleic protein particles, including the ribosome and the spliceosome. Our understanding of the nature of these dynamic changes in RNA targets is now being incorporated into RNA-specific approaches in the design of RNA inhibitors. Interactions of RNA with proteins, other RNAs, or small molecules often occur through binding mechanisms that follow an induced fit mechanism or a conformational selection mechanism, in which one of several populated RNA conformations is selected through ligand binding. The extent of functional dynamics, including the kinetic formation of a specific RNA tertiary fold, is dependent on the messenger RNA (mRNA) chain length. Thus, during de novo synthesis of mRNA, both in prokaryotes and eukaryotes, nascent mRNA of various lengths will adopt different secondary and tertiary structures. The speed of transcription has a critical influence on the functional dynamics of the RNA being synthesized. In addition to modulating the local dynamics of a conformational RNA ensemble, a given RNA sequence may adopt more than one global, three-dimensional structure. RNA modification is one way to select among these alternative structures, which are often characterized by nearly equal stability, but with high energy barriers for conformational interconversion. The refolding of different secondary and tertiary structures has been found to be a major regulatory mechanism for transcription and translation. These conformational transitions can be characterized with NMR spectroscopy, for any given RNA sequence, in response to external stimuli.