Characterizing RNA Dynamics at Atomic Resolution Using Solution-state NMR Spectroscopy

Many recently discovered non-coding RNAs do not fold into a single native conformation, but rather, sample many different conformations along their free energy landscape to carry out their biological function. Unprecedented insights into the RNA dynamic structure landscape are provided by solution-state NMR techniques that measure the structural, kinetic, and thermodynamic characteristics of motions spanning picosecond to second timescales at atomic resolution. From these studies a basic description of the RNA dynamic structure landscape is emerging, bringing new insights into how RNA structures change to carry out their function as well as applications in RNA-targeted drug discovery and RNA bioengineering

The Complex Energy Landscape of the Protein IscU

AbstractIscU, the scaffold protein for iron-sulfur (Fe-S) cluster biosynthesis in Escherichia coli, traverses a complex energy landscape during Fe-S cluster synthesis and transfer. Our previous studies showed that IscU populates two interconverting conformational states: one structured (S) and one largely disordered (D). Both states appear to be functionally important because proteins involved in the assembly or transfer of Fe-S clusters have been shown to interact preferentially with either the S or D state of IscU. To characterize the complex structure-energy landscape of IscU, we employed NMR spectroscopy, small-angle x-ray scattering (SAXS), and differential scanning calorimetry. Results obtained for IscU at pH 8.0 show that its S state is maximally populated at 25°C and that heating or cooling converts the protein toward the D state. Results from NMR and DSC indicate that both the heat- and cold-induced S→D transitions are cooperative and two-state. Low-resolution structural information from NMR and SAXS suggests that the structures of the cold-induced and heat-induced D states are similar. Both states exhibit similar 1H-15N HSQC spectra and the same pattern of peptidyl-prolyl peptide bond configurations by NMR, and both appear to be similarly expanded compared with the S state based on analysis of SAXS data. Whereas in other proteins the cold-denatured states have been found to be slightly more compact than the heat-denatured states, these two states occupy similar volumes in IscU

Incorporation of CC Steps into Z‑DNA: Interplay between B–Z Junction and Z‑DNA Helical Formation

The left-handed DNA structure, Z-DNA, is believed to play important roles in gene expression and regulation. Z-DNA forms sequence-specifically with a preference for sequences rich in pyrimidine/purine dinucleotide steps. In vivo, Z-DNA is generated in the presence of negative supercoiling or upon binding proteins that absorb the high energetic cost of the B-to-Z transition, including the creation of distorted junctions between B-DNA and Z-DNA. To date, the sequence preferences for the B-to-Z transition have primarily been studied in the context of sequence repeats lacking B–Z junctions. Here, we develop a method for characterizing sequence-specific preferences for Z-DNA formation and B–Z junction localization within heterogeneous DNA duplexes that is based on combining 2-aminopurine fluorescence measurements with a new quantitative application of circular dichroism spectroscopy for determining the fraction of B- versus Z-DNA. Using this approach, we show that at least three consecutive CC dinucleotide steps, traditionally thought to disfavor Z-DNA, can be incorporated within heterogeneous Z-DNA containing B–Z junctions upon binding to the Zα domain of the RNA adenosine deaminase protein. Our results indicate that the incorporation of CC steps into Z-DNA is driven by favorable sequence-specific Z–Z and B–Z stacking interactions as well as by sequence-specific energetics that localize the distorted B–Z junction at flexible sites. Together, our results expose higher-order complexities in the Z-DNA code within heterogeneous sequences and suggest that Z-DNA can in principle propagate into a wider range of genomic sequence elements than previously thought

Role of IscX in Iron–Sulfur Cluster Biogenesis in Escherichia coli

The Escherichia coli <i>isc</i> operon encodes key proteins involved in the biosynthesis of iron–sulfur (Fe–S) clusters. Whereas extensive studies of most ISC proteins have revealed their functional properties, the role of IscX (also dubbed YfhJ), a small acidic protein encoded by the last gene in the operon, has remained in question. Previous studies showed that IscX binds iron ions and interacts with the cysteine desulfurase (IscS) and the scaffold protein for cluster assembly (IscU), and it has been proposed that IscX functions either as an iron supplier or a regulator of Fe–S cluster biogenesis. We have used a combination of NMR spectroscopy, small-angle X-ray scattering (SAXS), chemical cross-linking, and enzymatic assays to enlarge our understanding of the interactions of IscX with iron ions, IscU, and IscS. We used chemical shift perturbation to identify the binding interfaces of IscX and IscU in their complex. NMR studies showed that Fe²⁺ from added ferrous ammonium sulfate binds IscX much more avidly than does Fe³⁺ from added ferric ammonium citrate and that Fe²⁺ strengthens the interaction between IscX and IscU. We found that the addition of IscX to the IscU–IscS binary complex led to the formation of a ternary complex with reduced cysteine desulfurase activity, and we determined a low-resolution model for that complex from a combination of NMR and SAXS data. We postulate that the inhibition of cysteine desulfurase activity by IscX serves to reduce unproductive conversion of cysteine to alanine. By incorporating these new findings with results from prior studies, we propose a detailed mechanism for Fe–S cluster assembly in which IscX serves both as a donor of Fe²⁺ and as a regulator of cysteine desulfurase activity

Development and Application of a High Throughput Protein Unfolding Kinetic Assay.

The kinetics of folding and unfolding underlie protein stability and quantification of these rates provides important insights into the folding process. Here, we present a simple high throughput protein unfolding kinetic assay using a plate reader that is applicable to the studies of the majority of 2-state folding proteins. We validate the assay by measuring kinetic unfolding data for the SH3 (Src Homology 3) domain from Actin Binding Protein 1 (AbpSH3) and its stabilized mutants. The results of our approach are in excellent agreement with published values. We further combine our kinetic assay with a plate reader equilibrium assay, to obtain indirect estimates of folding rates and use these approaches to characterize an AbpSH3-peptide hybrid. Our high throughput protein unfolding kinetic assays allow accurate screening of libraries of mutants by providing both kinetic and equilibrium measurements and provide a means for in-depth ϕ-value analyses

Learning relationships between chemical and physical stability for drug development

Chemical and physical stabilities are two key features considered in pharmaceutical development. Chemical stability is typically reported as a combination of potency and degradation product. For peptide products, it is common to measure physical stability via aggregation or fibrillation using the fluorescent reporter Thioflavin T. Executing stability studies is a lengthy process and requires extensive resources. To reduce the resources and shorten the process for stability studies during the development of a product, we introduce a machine learning based model for predicting the chemical stability over time using both the formulation conditions as well as the aggregation curve. In this work, we explore the relationships between the formulation, stability time point, and the measurements of chemical stability and achieve a coefficient of determination on a random test set of 0.945 and a mean absolute error (MAE) of 0.421 when using a multilayer perceptron (MLP) neural network for total degradation. Similarly, we achieve a coefficient of determination of 0.908 and an MAE of 1.435 when predicting the potency using a random forest model. When measurements of physical stability are included into the model, the MAE in the prediction of TD decreases to 0.148 for the MLP model. Using a similar strategy for the prediction of potency, the MAE decreases to 0.705 for the random forest model. Therefore, we can conclude two important points: first, chemical stability can be modeled using machine learning techniques and second there is a relationship between the physical stability of a peptide and its chemical stability

Unfolding kinetic constant derived from limited proteolysis of HLL.

<p>A range of concentrations of trypsin (A) and thermolysin (B) are used and degradation is followed by tryptophan fluorescence emission at 330 nm. The fits are to <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0146232#pone.0146232.e009" target="_blank">Eq 5</a> as indicated in the methods.</p

Representative kinetic traces generated from our plate reader method for AbpSH3 WT.

<p>The final guanidine concentration is at the top of each graph. Excitation is at 280 nm and emission is at 330 nm. The black line is fit to an exponential decay (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0146232#pone.0146232.e005" target="_blank">Eq 2</a>). Guanidine injection starts at 10 s.</p

Representative guanidine denaturation curves of proteins.

<p>AbpSH3 WT (open square), V21K (open triangle), E7L (line), Triple (open circle) and HLL (open diamond) denaturation monitored by tryptophan fluorescence emission at 330 nm. Fluorescence values are expressed as a fraction of the total change. The lines joining the points in each graph are theoretical fits to the data based on <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0146232#pone.0146232.e007" target="_blank">Eq 4</a> and the resultant thermodynamic parameters are shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0146232#pone.0146232.t002" target="_blank">Table 2</a>.</p