Sensitivity of NMR Residual Dipolar Couplings to Perturbations in Folded and Denatured Staphylococcal Nuclease

Common sequence motifs of nascent chains engage the ribosome surface and trigger factor

Proteins are produced by ribosomes in the cell, and during this process, can begin to adopt their biologically active forms assisted by molecular chaperones such as trigger factor. This fundamental cellular mechanism is crucial to maintaining a functional proteome and avoiding deleterious misfolding. Here, we study how disordered nascent chains emerge from the ribosome exit tunnel, and find that interactions with the ribosome surface dominate their dynamics in vitro and in vivo. Moreover, we show that the types of amino acids that mediate such interactions are also those that recruit trigger factor. This lays the foundation to describe how nascent chains are handed over from the ribosome surface to chaperones during biosynthesis within the crowded cytosol.

In the cell, the conformations of nascent polypeptide chains during translation are modulated by both the ribosome and its associated molecular chaperone, trigger factor. The specific interactions that underlie these modulations, however, are still not known in detail. Here, we combine protein engineering, in-cell and in vitro NMR spectroscopy, and molecular dynamics simulations to explore how proteins interact with the ribosome during their biosynthesis before folding occurs. Our observations of α-synuclein nascent chains in living Escherichia coli cells reveal that ribosome surface interactions dictate the dynamics of emerging disordered polypeptides in the crowded cytosol. We show that specific basic and aromatic motifs drive such interactions and directly compete with trigger factor binding while biasing the direction of the nascent chain during its exit out of the tunnel. These results reveal a structural basis for the functional role of the ribosome as a scaffold with holdase characteristics and explain how handover of the nascent chain to specific auxiliary proteins occurs among a host of other factors in the cytosol.

Monitoring protein folding through high pressure NMR spectroscopy

High-pressure is a well-known perturbation method used to destabilize globular proteins. It is perfectly reversible, which is essential for a proper thermodynamic characterization of a protein equilibrium. In contrast to other perturbation methods such as heat or chemical denaturant that destabilize protein structures uniformly, pressure exerts local effects on regions or domains of a protein containing internal cavities. When combined with NMR spectroscopy, hydrostatic pressure offers the possibility to monitor at a residue level the structural transitions occurring upon unfolding and to determine the kinetic properties of the process. High-pressure NMR experiments can now be routinely performed, owing to the recent development of commercially available high-pressure sample cells. This review summarizes recent advances and some future directions of high-pressure NMR techniques for the characterization at atomic resolution of the energy landscape of protein folding.

NMR characterization of long-range order in intrinsically disordered proteins

Intrinsically disordered proteins (IDPs) are predicted to represent a significant fraction of the human genome, and the development of meaningful molecular descriptions of these proteins remains a key challenge for contemporary structural biology. In order to describe the conformational behavior of IDPs, a molecular representation of the disordered state based on diverse sources of structural data that often exhibit complex and very different averaging behavior is required. In this study, we propose a combination of paramagnetic relaxation enhancements (PREs) and residual dipolar couplings (RDCs) to define both long-range and local structural features of IDPs in solution. We demonstrate that ASTEROIDS, an ensemble selection algorithm, faithfully reproduces intramolecular contacts, even in the presence of highly diffuse, ill-defined target interactions. We also show that explicit modeling of spin-label mobility significantly improves the reproduction of experimental PRE data, even in the case of highly disordered proteins. Prediction of the effects of transient long-range contacts on RDC profiles reveals that weak intramolecular interactions can induce a severe distortion of the profiles that compromises the description of local conformational sampling if it is not correctly taken into account. We have developed a solution to this problem that involves efficiently combining RDC and PRE data to simultaneously determine long-range and local structure in highly flexible proteins. This combined analysis is shown to be essential for the accurate interpretation of experimental data from alpha-synuclein, an important IDP involved in human neurodegenerative disease, confirming the presence of long-range order between distant regions in the protein.

Quantitative description of backbone conformational sampling of unfolded proteins at amino acid resolution from NMR residual dipolar couplings

An atomic resolution characterization of the structural properties of unfolded proteins that explicitly invokes the highly dynamic nature of the unfolded state will be extremely important for the development of a quantitative understanding of the thermodynamic basis of protein folding and stability. Here we develop a novel approach using residual dipolar couplings (RDCs) from unfolded proteins to determine conformational behavior on an amino acid specific basis. Conformational sampling is described in terms of ensembles of structures selected from a large pool of conformers. We test this approach, using extensive simulation, to determine how well the fitting of RDCs to reduced conformational ensembles containing few copies of the molecule can correctly reproduce the backbone conformational behavior of the protein. Having established approaches that allow accurate mapping of backbone dihedral angle conformational space from RDCs, we apply these methods to obtain an amino acid specific description of ubiquitin denatured in 8 M urea at pH 2.5. Cross-validation of data not employed in the fit verifies that an ensemble size of 200 structures is appropriate to characterize the highly fluctuating backbone. This approach allows us to identify local conformational sampling properties of urea-unfolded ubiquitin, which shows that the backbone sampling of certain types of charged or polar amino acids, in particular threonine, glutamic acid, and arginine, is affected more strongly by urea binding than amino acids with hydrophobic side chains. In general, the approach presented here establishes robust procedures for the study of all denatured and intrinsically disordered states.

Model-independent interpretation of NMR relaxation data for unfolded proteins: the acid-denatured state of ACBP

We have investigated the acid-unfolded state of acyl-coenzyme A binding protein (ACBP) using 15N laboratory frame nuclear magnetic resonance (NMR) relaxation experiments at three magnetic field strengths. The data have been analyzed using standard model-free fitting and models involving distribution of correlation times. In particular, a model-independent method of analysis that does not assume any analytical form for the correlation time distribution is proposed. This method explains correlations between model-free parameters and the analytical distribution parameters found by other authors. The analysis also shows that the relaxation data are consistent with and complementary to information obtained from other parameters, especially secondary chemical shifts and residual dipolar couplings, and strengthens the conclusions of previous observations that three out of the four regions that form helices in the native structure appear to contain residual secondary structure also in the acid-denatured state.

A shorter peptide model from staphylococcal nuclease for the folding-unfolding equilibrium of a beta-hairpin shows that unfolded state has significant contribution from compact conformational states

It is important to understand the conformational features of the unfolded state in equilibrium with folded state under physiological conditions. In this paper, we consider a short peptide model LMYKGQPM from staphylococcal nuclease to model the conformational equilibrium between a hairpin conformation and its unfolded state using molecular dynamics simulation under NVT conditions at 300K using GROMOS96 force field. The free energy landscape has overall funnel-like shape with hairpin conformations sampling the minima. The "unfolded" state has a higher free energy of approximately 12kJ/mol with respect to native hairpin minimum and occupies a plateau region. We find that the unfolded state has significant contributions from compact conformations. Many of these conformations have hairpin-like topology. Further, these compact conformational forms are stabilized by hydrophobic interactions. Conversion between native and non-native hairpins occurs via unfolded states. Frequent conversions between folded and unfolded hairpins are observed with single exponential kinetics. We compare our results with the emerging picture of unfolded state from both experimental and theoretical studies.

Theoretical framework for NMR residual dipolar couplings in unfolded proteins

A theoretical framework for the prediction of nuclear magnetic resonance (NMR) residual dipolar couplings (RDCs) in unfolded proteins under weakly aligning conditions is presented. The unfolded polypeptide chain is modeled as a random flight chain while the alignment medium is represented by a set of regularly arranged obstacles. For the case of bicelles oriented perpendicular to the magnetic field, a closed-form analytical result is derived. With the obtained analytical expression the RDCs are readily accessible for any locus along the chain, for chains of differing length, and for varying bicelle concentrations. The two general features predicted by the model are (i) RDCs in the center segments of a polypeptide chain are larger than RDCs in the end segments, resulting in a bell-shaped sequential distribution of RDCs, and (ii) couplings are larger for shorter chains than for longer chains at a given bicelle concentration. Experimental data available from the literature confirm the first prediction of the model, providing a tool for recognizing fully unfolded polypeptide chains. With less certainty experimental data appear to support the second prediction as well. However, more systematic experimental studies are needed in order to validate or disprove the predictions of the model. The presented framework is an important step towards a solid theoretical foundation for the analysis of experimentally measured RDCs in unfolded proteins in the case of alignment media such as polyacrylamide gels and neutral bicelle systems which align biomacromolecules by a steric mechanism. Various improvements and generalizations are possible within the suggested approach.

The Cytoplasmic Domain of the Chloride Channel ClC-0: Structural and Dynamic Characterization of Flexible Regions

Eukaryotic members of the ClC family of chloride channels and transporters are composed of a transmembrane ion transport domain followed by a cytoplasmic domain, which is believed to be involved in the modulation of ClC function. In some family members this putative regulatory domain contains next to a well-folded structured part, long sequence stretches with low sequence complexity. These regions, a 96 residue long linker connecting two structured sub-domains, and 35 residues on the C teminus of the domain were found disordered in a recent crystal structure of this domain in ClC-0. Both regions have a large influence on the modulation of channel function in closely related family members. Here we describe a NMR study to characterize the structural and dynamic properties of these putatively unstructured stretches. Our study reveals that the two regions indeed show large conformational flexibility with dynamics on the nanosecond timescale. However, small islands of secondary structure are found interdispersed between the unfolded regions. This study characterizes for the first time the biophysical properties of these protein segments, which may become important for the understanding of novel regulatory mechanisms within the ClC family.

Characterization of the residual structure in the unfolded state of the Δ131Δ fragment of staphylococcal nuclease

The determination of the conformational preferences in unfolded states of proteins constitutes an important challenge in structural biology. We use inter-residue distances estimated from site-directed spin-labeling NMR experimental measurements as ensemble-averaged restraints in all-atom molecular dynamics simulations to characterise the residual structure of the Delta131Delta fragment of staphylococcal nuclease under physiological conditions. Our findings indicate that Delta131Delta under these conditions shows a tendency to form transiently hydrophobic clusters similar to those present in the native state of wild-type staphylococcal nuclease. Only rarely, however, all these interactions are simultaneously realized to generate conformations with an overall native topology.

Building native protein conformation from highly approximate backbone torsion angles

Reconstructing a protein in three dimensions from its backbone torsion angles is an ongoing challenge because minor inaccuracies in these angles produce major errors in the structure. As a familiar example, a small change in an elbow angle causes a large displacement at the end of your arm, the longer the arm, the larger the displacement. Even accurate knowledge of the backbone torsions and Psi is insufficient, owing to the small, but cumulative, deviations from ideality in backbone planarity, which, if ignored, also lead to major errors in the structure. Against this background, we conducted a computational experiment to assess whether protein conformation can be determined from highly approximate backbone torsion angles, the kind of information that is now obtained readily from NMR. Specifically, backbone torsion angles were taken from proteins of known structure and mapped into 60 degrees x 60 degrees grid squares, called mesostates. Side-chain atoms beyond the beta -carbon were discarded. A mesostate representation of the protein backbone was then used to extract likely candidates from a fragment library of mesostate pentamers, followed by Monte Carlo-based fragment-assembly simulations to identify stable conformations compatible with the given mesostate sequence. Only three simple energy terms were used to gauge stability: molecular compaction, soft-sphere repulsion, and hydrogen bonding. For the six representative proteins described here, stable conformers can be partitioned into a remarkably small number of topologically distinct clusters. Among these, the native topology is found with high frequency and can be identified as the cluster with the most favorable energy.

Statistical coil model of the unfolded state: resolving the reconciliation problem

An unfolded state ensemble is generated by using a self-avoiding statistical coil model that is based on backbone conformational frequencies in a coil library, a subset of the Protein Data Bank. The model reproduces two apparently contradicting behaviors observed in the chemically denatured state for a variety of proteins, random coil scaling of the radius of gyration and the presence of significant amounts of local backbone structure (NMR residual dipolar couplings). The most stretched members of our unfolded ensemble dominate the residual dipolar coupling signal, whereas the uniformity of the sign of the couplings follows from the preponderance of polyproline II and beta conformers in the coil library. Agreement with the NMR data substantially improves when the backbone conformational preferences include correlations arising from the chemical and conformational identity of neighboring residues. Although the unfolded ensembles match the experimental observables, they do not display evidence of native-like topology. By providing an accurate representation of the unfolded state, our statistical coil model can be used to improve thermodynamic and kinetic modeling of protein folding.