Ensemble calculations of unstructured proteins constrained by RDC and PRE data: a case study of urea-denatured ubiquitin

Conformational and Interaction Landscape of Histone H4 Tails in Nucleosomes Probed by Paramagnetic NMR Spectroscopy

The fundamental repeat unit of chromatin, the nucleosome, consists of approximately 147 base pairs of double-stranded DNA and a histone protein octamer containing two copies each of histones H2A, H2B, H3, and H4. Each histone possesses a dynamically disordered N-terminal tail domain, and it is well-established that the tails of histones H3 and H4 play key roles in chromatin compaction and regulation. Here we investigate the conformational ensemble and interactions of the H4 tail in nucleosomes by means of solution NMR measurements of paramagnetic relaxation enhancements (PREs) in recombinant samples reconstituted with 15N-enriched H4 and nitroxide spin-label tagged H3. The experimental PREs, which report on the proximities of individual H4 tail residues to the different H3 spin-label sites, are interpreted by using microsecond time-scale molecular dynamics simulations of the nucleosome core particle. Collectively, these data enable improved localization of histone H4 tails in nucleosomes and support the notion that H4 tails engage in a fuzzy complex interaction with nucleosomal DNA.

Nuclear magnetic resonance/single molecule fluorescence combinations to study dynamic protein systems

Many proteins require different structural states or conformations for function, and intrinsically disordered proteins, i.e. proteins without stable three-dimensional structure, are certainly an extreme. Single molecule fluorescence and nuclear magnetic resonance (NMR) spectroscopy are both exceptionally well suited to decipher and describe these states and their interconversion. Different time scales, from picoseconds to several milliseconds, can be addressed by both techniques. The length scales probed and the sample requirements (e.g. concentration, molecular weight, sample complexity) are, however, vastly different, making NMR and single molecule fluorescence an excellent combination for integrated studies. Here, we review recently undertaken approaches for the combined use of NMR and single molecule fluorescence to study protein dynamics.

DMSO-Quenched H/D-Exchange 2D NMR Spectroscopy and Its Applications in Protein Science

Hydrogen/deuterium (H/D) exchange combined with two-dimensional (2D) NMR spectroscopy has been widely used for studying the structure, stability, and dynamics of proteins. When we apply the H/D-exchange method to investigate non-native states of proteins such as equilibrium and kinetic folding intermediates, H/D-exchange quenching techniques are indispensable, because the exchange reaction is usually too fast to follow by 2D NMR. In this article, we will describe the dimethylsulfoxide (DMSO)-quenched H/D-exchange method and its applications in protein science. In this method, the H/D-exchange buffer is replaced by an aprotic DMSO solution, which quenches the exchange reaction. We have improved the DMSO-quenched method by using spin desalting columns, which are used for medium exchange from the H/D-exchange buffer to the DMSO solution. This improvement has allowed us to monitor the H/D exchange of proteins at a high concentration of salts or denaturants. We describe methodological details of the improved DMSO-quenched method and present a case study using the improved method on the H/D-exchange behavior of unfolded human ubiquitin in 6 M guanidinium chloride.

Generating Ensembles of Dynamic Misfolding Proteins

The early stages of protein misfolding and aggregation involve disordered and partially folded protein conformers that contain a high degree of dynamic disorder. These dynamic species may undergo large-scale intra-molecular motions of intrinsically disordered protein (IDP) precursors, or flexible, low affinity inter-molecular binding in oligomeric assemblies. In both cases, generating atomic level visualization of the interconverting species that captures the conformations explored and their physico-chemical properties remains hugely challenging. How specific sub-ensembles of conformers that are on-pathway to aggregation into amyloid can be identified from their aggregation-resilient counterparts within these large heterogenous pools of rapidly moving molecules represents an additional level of complexity. Here, we describe current experimental and computational approaches designed to capture the dynamic nature of the early stages of protein misfolding and aggregation, and discuss potential challenges in describing these species because of the ensemble averaging of experimental restraints that arise from motions on the millisecond timescale. We give a perspective of how machine learning methods can be used to extract aggregation-relevant sub-ensembles and provide two examples of such an approach in which specific interactions of defined species within the dynamic ensembles of α-synuclein (αSyn) and β2-microgloblulin (β2m) can be captured and investigated.

Heterogeneity in Protein Folding and Unfolding Reactions

Proteins have dynamic structures that undergo chain motions on time scales spanning from picoseconds to seconds. Resolving the resultant conformational heterogeneity is essential for gaining accurate insight into fundamental mechanistic aspects of the protein folding reaction. The use of high-resolution structural probes, sensitive to population distributions, has begun to enable the resolution of site-specific conformational heterogeneity at different stages of the folding reaction. Different states populated during protein folding, including the unfolded state, collapsed intermediate states, and even the native state, are found to possess significant conformational heterogeneity. Heterogeneity in protein folding and unfolding reactions originates from the reduced cooperativity of various kinds of physicochemical interactions between various structural elements of a protein, and between a protein and solvent. Heterogeneity may arise because of functional or evolutionary constraints. Conformational substates within the unfolded state and the collapsed intermediates that exchange at rates slower than the subsequent folding steps give rise to heterogeneity on the protein folding pathways. Multiple folding pathways are likely to represent distinct sequences of structure formation. Insight into the nature of the energy barriers separating different conformational states populated during (un)folding can also be obtained by resolving heterogeneity.

Synergies of Single Molecule Fluorescence and NMR for the Study of Intrinsically Disordered Proteins

Single molecule fluorescence and nuclear magnetic resonance spectroscopy (NMR) are two very powerful techniques for the analysis of intrinsically disordered proteins (IDPs). Both techniques have individually made major contributions to deciphering the complex properties of IDPs and their interactions, and it has become evident that they can provide very complementary views on the distance-dynamics relationships of IDP systems. We now review the first approaches using both NMR and single molecule fluorescence to decipher the molecular properties of IDPs and their interactions. We shed light on how these two techniques were employed synergistically for multidomain proteins harboring intrinsically disordered linkers, for veritable IDPs, but also for liquid–liquid phase separated systems. Additionally, we provide insights into the first approaches to use single molecule Förster resonance energy transfer (FRET) and NMR for the description of multiconformational models of IDPs.

Advances in NMR Spectroscopy of Weakly Aligned Biomolecular Systems

The measurement and application of residual dipolar couplings (RDCs) in solution NMR studies of biological macromolecules has become well established over the past quarter of a century. Numerous methods for generating the requisite anisotropic orientational molecular distribution have been demonstrated, each with its specific strengths and weaknesses. In parallel, an enormous number of pulse schemes have been introduced to measure the many different types of RDCs, ranging from the most widely measured backbone amide ¹⁵N-¹H RDCs, to ¹H-¹H RDCs and couplings between low-γ nuclei. Applications of RDCs range from structure validation and refinement to the determination of relative domain orientations, the measurement of backbone and domain motions, and de novo structure determination. Nevertheless, it appears that the power of the RDC methodology remains underutilized. This review aims to highlight the practical aspects of sample preparation and RDC measurement while describing some of the most straightforward applications that take advantage of the exceptionally precise information contained in such data. Some emphasis will be placed on more recent developments that enable the accurate measurement of RDCs in larger systems, which is key to the ongoing shift in focus of biological NMR spectroscopy from structure determination toward gaining improved understanding of how molecular flexibility drives protein function.

ESCASA: Analytical estimation of atomic coordinates from coarse-grained geometry for nuclear-magnetic-resonance-assisted protein structure modeling. I. Backbone and Hβ protons

A method for the estimation of coordinates of atoms in proteins from coarse-grained geometry by simple analytical formulas (ESCASA), for use in nuclear-magnetic-resonance (NMR) data-assisted coarse-grained simulations of proteins is proposed. In this paper, the formulas for the backbone H^α and amide (H^N ) protons, and the side-chain H^β protons, given the C^α -trace, have been derived and parameterized, by using the interproton distances calculated from a set of 140 high-resolution non-homologous protein structures. The mean standard deviation over all types of proton pairs in the set was 0.44 Å after fitting. Validation against a set of 41 proteins with NMR-determined structures, which were not considered in parameterization, resulted in average standard deviation from average proton-proton distances of the NMR-determined structures of 0.25 Å, compared to 0.21 Å obtained with the PULCHRA all-atom-chain reconstruction algorithm and to the 0.12 Å standard deviation of the average-structure proton-proton distance of NMR-determined ensembles. The formulas provide analytical forces and can, therefore, be used in coarse-grained molecular dynamics.

Residual Structure of Unfolded Ubiquitin as Revealed by Hydrogen/Deuterium-Exchange 2D NMR

The characterization of residual structures persistent in unfolded proteins in concentrated denaturant solution is currently an important issue in studies of protein folding because the residual structure present, if any, in the unfolded state may form a folding initiation site and guide the subsequent folding reactions. Here, we studied the hydrogen/deuterium (H/D)-exchange behavior of unfolded human ubiquitin in 6 M guanidinium chloride. We employed a dimethylsulfoxide (DMSO)-quenched H/D-exchange NMR technique with the use of spin desalting columns, which allowed us to perform a quick medium exchange from 6 M guanidinium chloride to a quenching DMSO solution. Based on the backbone resonance assignment of ubiquitin in the DMSO solution, we successfully investigated the H/D-exchange kinetics of 60 identified peptide amide groups in the ubiquitin sequence. Although a majority of these amide groups were not protected, certain amide groups involved in a middle helix (residues 23-34) and an N-terminal β-hairpin (residues 2-16) were significantly protected with a protection factor of 2.1-4.2, indicating that there were residual structures in unfolded ubiquitin and that these amide groups were more than 52% hydrogen bonded in the residual structures. We show that the hydrogen-bonded residual structures in the α-helix and the β-hairpin are formed even in 6 M guanidinium chloride, suggesting that these residual structures may function as a folding initiation site to guide the subsequent folding reactions of ubiquitin.

Investigating the Conformational Ensembles of Intrinsically Disordered Proteins with a Simple Physics-Based Model

Intrinsically disordered proteins (IDPs) play an important role in an array of biological processes but present a number of fundamental challenges for computational modeling. Recently, simple polymer models have regained popularity for interpreting the experimental characterization of IDPs. Homopolymer theory provides a strong foundation for understanding generic features of phenomena ranging from single-chain conformational dynamics to the properties of entangled polymer melts, but is difficult to extend to the copolymer context. This challenge is magnified for proteins due to the variety of competing interactions and large deviations in side-chain properties. In this work, we apply a simple physics-based coarse-grained model for describing largely disordered conformational ensembles of peptides, based on the premise that sampling sterically forbidden conformations can compromise the faithful description of both static and dynamical properties. The Hamiltonian of the employed model can be easily adjusted to investigate the impact of distinct interactions and sequence specificity on the randomness of the resulting conformational ensemble. In particular, starting with a bead–spring-like model and then adding more detailed interactions one by one, we construct a hierarchical set of models and perform a detailed comparison of their properties. Our analysis clarifies the role of generic attractions, electrostatics, and side-chain sterics, while providing a foundation for developing efficient models for IDPs that retain an accurate description of the hierarchy of conformational dynamics, which is nontrivially influenced by interactions with surrounding proteins and solvent molecules.

Salient Features of Monomeric Alpha-Synuclein Revealed by NMR Spectroscopy

Elucidating the structural details of proteins is highly valuable and important for the proper understanding of protein function. In the case of intrinsically disordered proteins (IDPs), however, obtaining the structural details is quite challenging, as the traditional structural biology tools have only limited use. Nuclear magnetic resonance (NMR) is a unique experimental tool that provides ensemble conformations of IDPs at atomic resolution, and when studying IDPs, a slightly different experimental strategy needs to be employed than the one used for globular proteins. We address this point by reviewing many NMR investigations carried out on the α-synuclein protein, the aggregation of which is strongly correlated with Parkinson’s disease.

Pro-islet amyloid polypeptide in micelles contains a helical prohormone segment

Pro-islet amyloid polypeptide (proIAPP) is the prohormone precursor molecule to IAPP, also known as amylin. IAPP is a calcitonin family peptide hormone that is cosecreted with insulin, and largely responsible for hunger satiation and metabolic homeostasis. Amyloid plaques containing mixtures of mature IAPP and misprocessed proIAPP deposit on, and destroy pancreatic β-cell membranes, and they are recognized as a clinical hallmark of type 2 diabetes mellitus. In order to better understand the interaction with cellular membranes, we solved the solution NMR structure of proIAPP bound to dodecylphosphocholine micelles at pH 4.5. We show that proIAPP is a dynamic molecule with four α-helices. The first two helices are contained within the mature IAPP sequence, while the second two helices are part of the C-terminal prohormone segment (Cpro). We mapped the membrane topology of the amphipathic helices by paramagnetic relaxation enhancement, and we used CD and diffusion-ordered spectroscopy to identify environmental factors that impact proIAPP membrane affinity. We discuss how our structural results relate to prohormone processing based on the varied pH environments and lipid compositions of organelle membranes within the regulated secretory pathway, and the likelihood of Cpro survival for cosecretion with IAPP. DATABASE: The assigned resonances have been deposited in the Biological Magnetic Resonance Bank (BMRB) with accession numbers 50007 and 50019 for proIAPP and Cpro, respectively. The lowest energy structures have been deposited in the Protein Data Bank (PDB) with access codes 6UCJ and 6UCK.

Characterization of intrinsically disordered proteins and their dynamic complexes: From in vitro to cell-like environments

Over the last two decades, it has become increasingly clear that a large fraction of the human proteome is intrinsically disordered or contains disordered segments of significant length. These intrinsically disordered proteins (IDPs) play important regulatory roles throughout biology, underlining the importance of understanding their conformational behavior and interaction mechanisms at the molecular level. Here we review recent progress in the NMR characterization of the structure and dynamics of IDPs in various functional states and environments. We describe the complementarity of different NMR parameters for quantifying the conformational propensities of IDPs in their isolated and phosphorylated states, and we discuss the challenges associated with obtaining structural models of dynamic protein-protein complexes involving IDPs. In addition, we review recent progress in understanding the conformational behavior of IDPs in cell-like environments such as in the presence of crowding agents, in membrane-less organelles and in the complex environment of the human cell.

Conformational states of Zika virus non-structural protein 3 determined by molecular dynamics simulations with small-angle X-Ray scattering data

Zika virus (ZIKV) has become a great public health emergency. Its non-structural protein 3 (NS3) is a key enzyme in viral replication and has been considered as a potential therapeutic target. A conformational characterization of ZIKV NS3 is critical for a comprehensive understanding of its molecular interactions and functions. However, the high conformational flexibility of solution NS3 obstacles the structural characterization of NS3 solely from the experimental observable that averages over its heterogeneous conformations. Here, we employed replica exchange with solute tempering (REST) method to simulate the di-domain protein ZIKV NS3. Three independent MD simulations identified a conserved conformational ensemble of NS3, consisting of a major conformational state and several minor states from compact to loose conformations. The major state agrees well with the scattering profile from small-angle X-ray scattering (SAXS) experiments. Moreover, the simulated ensemble is supported by a direct data-fitting result that requires both short- and long-range structural contacts to recover the experimental data. We discussed the interplay between simulation and experiment in ensemble construction of flexible biomolecules and shed light on the physically derived conformational ensembles.

Conformational Ensemble of Disordered Proteins Probed by Solvent Paramagnetic Relaxation Enhancement (sPRE)

Characterization of the conformational ensemble of disordered proteins is highly important for understanding protein folding and aggregation mechanisms, but remains a computational and experimental challenge owing to the dynamic nature of these proteins. New observables that can provide unique insights into transient residual structures in disordered proteins are needed. Here using denatured ubiquitin as a model system, NMR solvent paramagnetic relaxation enhancement (sPRE) measurements provide an accurate and highly sensitive probe for detecting low populations of residual structure in a disordered protein. Furthermore, a new ensemble calculation approach based on sPRE restraints in conjunction with residual dipolar couplings (RDCs) and small-angle X-ray scattering (SAXS) is used to define the conformational ensemble of disordered proteins at atomic resolution. The approach presented should be applicable to a wide range of dynamic macromolecules.

Determination of the conformational states of strychnine in solution using NMR residual dipolar couplings in a tensor-free approach

Small molecules with rotatable bonds can occupy different conformational states in solution as a consequence of their thermal fluctuations. The accurate determination of the structures of such states, as well as of their statistical weights, has been challenging because of the technical difficulties in extracting information from experimental measurements, which are normally averaged over the conformational space available. Here, to achieve this objective, we present an approach based on a recently proposed tensor-free method for incorporating NMR residual dipolar couplings as structural restraints in replica-averaged molecular dynamics simulations. This approach enables the information provided by the experimental data to be used in the spirit of the maximum entropy principle to determine the structural ensembles of small molecules. Furthermore, in order to enhance the sampling of the conformational space we incorporated the metadynamics method in the simulations. We illustrate the method in the case of strychnine, determining the three major conformational states of this small molecule and their associated occupation probabilities.

Hypothesis: structural heterogeneity of the unfolded proteins originating from the coupling of the local clusters and the long-range distance distribution

We propose a hypothesis that explains two apparently contradicting observations for the heterogeneity of the unfolded proteins. First, the line confocal method of the single-molecule Förster resonance energy transfer (sm-FRET) spectroscopy revealed that the unfolded proteins possess broad peaks in the FRET efficiency plot, implying the significant heterogeneity that lasts longer than milliseconds. Second, the fluorescence correlation method demonstrated that the unfolded proteins fluctuate in the time scale shorter than 100 ns. To formulate the hypothesis, we first summarize the recent consensus for the structure and dynamics of the unfolded proteins. We next discuss the conventional method of the sm-FRET spectroscopy and its limitations for the analysis of the unfolded proteins, followed by the advantages of the line confocal method that revealed the heterogeneity. Finally, we propose that the structural heterogeneity formed by the local clustering of hydrophobic residues modulates the distribution of the long-range distance between the labeled chromophores, resulting in the broadening of the peak in the FRET efficiency plot. A clustering of hydrophobic residues around the chromophore might further contribute to the broadening. The proposed clusters are important for the understanding of protein folding mechanism.

Paramagnetic NMR as a new tool in structural biology

NMR (nuclear magnetic resonance) investigation through the exploitation of paramagnetic effects is passing from an approach limited to few specialists in the field to a generally applicable method that must be considered, especially for the characterization of systems hardly affordable with other techniques. This is mostly due to the fact that paramagnetic data are long range in nature, thus providing information for the structural and dynamic characterization of complex biomolecular architectures in their native environment. On the other hand, this information usually needs to be complemented by data from other sources. Integration of paramagnetic NMR with other techniques, and the development of protocols for a joint analysis of all available data, is fundamental for achieving a comprehensive characterization of complex biological systems. We describe here a few examples of the new possibilities offered by paramagnetic data used in integrated structural approaches.

Investigating energy-based pool structure selection in the structure ensemble modeling with experimental distance constraints: The example from a multidomain protein Pub1

The structural variations of multidomain proteins with flexible parts mediate many biological processes, and a structure ensemble can be determined by selecting a weighted combination of representative structures from a simulated structure pool, producing the best fit to experimental constraints such as interatomic distance. In this study, a hybrid structure-based and physics-based atomistic force field with an efficient sampling strategy is adopted to simulate a model di-domain protein against experimental paramagnetic relaxation enhancement (PRE) data that correspond to distance constraints. The molecular dynamics simulations produce a wide range of conformations depicted on a protein energy landscape. Subsequently, a conformational ensemble recovered with low-energy structures and the minimum-size restraint is identified in good agreement with experimental PRE rates, and the result is also supported by chemical shift perturbations and small-angle X-ray scattering data. It is illustrated that the regularizations of energy and ensemble-size prevent an arbitrary interpretation of protein conformations. Moreover, energy is found to serve as a critical control to refine the structure pool and prevent data overfitting, because the absence of energy regularization exposes ensemble construction to the noise from high-energy structures and causes a more ambiguous representation of protein conformations. Finally, we perform structure-ensemble optimizations with a topology-based structure pool, to enhance the understanding on the ensemble results from different sources of pool candidates.

Protein Structure Elucidation from NMR Data with the Program Xplor-NIH

Xplor-NIH is a popular software package for biomolecular structure determination from NMR (and other) experimental data. This chapter illustrates its use with the de novo structure determination of the B1 domain of streptococcal protein G (GB1), based on distances from nuclear Overhauser effects, torsion angles from scalar couplings, and bond-vector orientations from residual dipolar couplings. Including Xplor-NIH's latest developments, a complete structure calculation script is discussed in detail, and is intended to serve as a basis for other applications.

Xplor-NIH for molecular structure determination from NMR and other data sources

Xplor-NIH is a popular software package for biomolecular structure determination from nuclear magnetic resonance (NMR) and other data sources. Here, some of Xplor-NIH's most useful data-associated energy terms are reviewed, including newer alternative options for using residual dipolar coupling data in structure calculations. Further, we discuss new developments in the implementation of strict symmetry for the calculation of symmetric homo-oligomers, and in the representation of the system as an ensemble of structures to account for motional effects. Finally, the different available force fields are presented, among other Xplor-NIH capabilities.

Molecular modeling of biomolecules by paramagnetic NMR and computational hybrid methods

The 3D atomic structures of biomolecules and their complexes are key to our understanding of biomolecular function, recognition, and mechanism. However, it is often difficult to obtain structures, particularly for systems that are complex, dynamic, disordered, or exist in environments like cell membranes. In such cases sparse data from a variety of paramagnetic NMR experiments offers one possible source of structural information. These restraints can be incorporated in computer modeling algorithms that can accurately translate the sparse experimental data into full 3D atomic structures. In this review, we discuss various types of paramagnetic NMR/computational hybrid modeling techniques that can be applied to successful modeling of not only the atomic structure of proteins but also their interacting partners. This article is part of a Special Issue entitled: Biophysics in Canada, edited by Lewis Kay, John Baenziger, Albert Berghuis and Peter Tieleman.

Dynamic Descriptions of Highly Flexible Molecules from NMR Dipolar Couplings: Physical Basis and Limitations

Biomolecules that control physiological function by changing their conformation play key roles in biology and remain poorly characterized. NMR dipolar couplings (DCs) depend intrinsically on both molecular shape and structural fluctuations, thereby providing the enticing prospect of tracking these conformational changes at atomic detail. Although this dual dependence has until now severely complicated analysis of DCs from highly dynamic systems, general approaches have recently been proposed that simplify interpretation of experimental DCs, by entirely eliminating molecular alignment from the analysis. Using simple and intuitive simulation of target ensembles, we investigate the impact of such approaches on the resulting descriptions of the conformational energy landscape. We find that ensemble descriptions of highly flexible systems derived from DCs without explicit consideration of the alignment properties of the constituent conformations can be compromised and inaccurate, despite exhibiting high correlation with experimental measurement.

A critical assessment of methods to recover information from averaged data

Conformational heterogeneity is key to the function of many biomacromolecules, but only a few groups have tried to characterize it until recently. Now, thanks to the increased throughput of experimental data and the increased computational power, the problem of the characterization of protein structural variability has become more and more popular. Several groups have devoted their efforts in trying to create quantitative, reliable and accurate protocols for extracting such information from averaged data. We analyze here different approaches, discussing strengths and weaknesses of each. All approaches can roughly be clustered into two groups: those satisfying the maximum entropy principle and those recovering ensembles composed of a restricted number of molecular conformations. In the first case, the solution focuses on the features that are common to all the infinite solutions satisfying the experimental data; in the second case, the reconstructed ensemble shows the conformational regions where a large probability can be placed. The upper limits for conformational probabilities (MaxOcc) can also be calculated. We also give an overview of the mainstream experimental observables, with considerations on the assumptions underlying their usage.

Comprehensive structural and dynamical view of an unfolded protein from the combination of single-molecule FRET, NMR, and SAXS

The properties of unfolded proteins are essential both for the mechanisms of protein folding and for the function of the large group of intrinsically disordered proteins. However, the detailed structural and dynamical characterization of these highly dynamic and conformationally heterogeneous ensembles has remained challenging. Here we combine and compare three of the leading techniques for the investigation of unfolded proteins, NMR spectroscopy (NMR), small-angle X-ray scattering (SAXS), and single-molecule Förster resonance energy transfer (FRET), with the goal of quantitatively testing their consistency and complementarity and for obtaining a comprehensive view of the unfolded-state ensemble. Using unfolded ubiquitin as a test case, we find that its average dimensions derived from FRET and from structural ensembles calculated using the program X-PLOR-NIH based on NMR and SAXS restraints agree remarkably well; even the shapes of the underlying intramolecular distance distributions are in good agreement, attesting to the reliability of the approaches. The NMR-based results provide a highly sensitive way of quantifying residual structure in the unfolded state. FRET-based nanosecond fluorescence correlation spectroscopy allows long-range distances and chain dynamics to be probed in a time range inaccessible by NMR. The combined techniques thus provide a way of optimally using the complementarity of the available methods for a quantitative structural and dynamical description of unfolded proteins both at the global and the local level.

Finding Our Way in the Dark Proteome

The traditional structure-function paradigm has provided significant insights for well-folded proteins in which structures can be easily and rapidly revealed by X-ray crystallography beamlines. However, approximately one-third of the human proteome is comprised of intrinsically disordered proteins and regions (IDPs/IDRs) that do not adopt a dominant well-folded structure, and therefore remain "unseen" by traditional structural biology methods. This Perspective considers the challenges raised by the "Dark Proteome", in which determining the diverse conformational substates of IDPs in their free states, in encounter complexes of bound states, and in complexes retaining significant disorder requires an unprecedented level of integration of multiple and complementary solution-based experiments that are analyzed with state-of-the art molecular simulation, Bayesian probabilistic models, and high-throughput computation. We envision how these diverse experimental and computational tools can work together through formation of a "computational beamline" that will allow key functional features to be identified in IDP structural ensembles.

Hybrid Approaches to Structural Characterization of Conformational Ensembles of Complex Macromolecular Systems Combining NMR Residual Dipolar Couplings and Solution X-ray Scattering

Solving structures or structural ensembles of large macromolecular systems in solution poses a challenging problem. While NMR provides structural information at atomic resolution, increased spectral complexity, chemical shift overlap, and short transverse relaxation times (associated with slow tumbling) render application of the usual techniques that have been so successful for medium sized systems (<50 kDa) difficult. Solution X-ray scattering, on the other hand, is not limited by molecular weight but only provides low resolution structural information related to the overall shape and size of the system under investigation. Here we review how combining atomic resolution structures of smaller domains with sparse experimental data afforded by NMR residual dipolar couplings (which yield both orientational and shape information) and solution X-ray scattering data in rigid-body simulated annealing calculations provides a powerful approach for investigating the structural aspects of conformational dynamics in large multidomain proteins. The application of this hybrid methodology is illustrated for the 128 kDa dimer of bacterial Enzyme I which exists in a variety of open and closed states that are sampled at various points in the catalytic cycles, and for the capsid protein of the human immunodeficiency virus.

Under-folded proteins: Conformational ensembles and their roles in protein folding, function, and pathogenesis

For decades, protein function was intimately linked to the presence of a unique, aperiodic crystal‐like structure in a functional protein. The two only places for conformational ensembles of under‐folded (or partially folded) protein forms in this picture were either the end points of the protein denaturation processes or transiently populated folding intermediates. Recent years witnessed dramatic change in this perception and conformational ensembles, which the under‐folded proteins are, have moved from the shadow. Accumulated to date data suggest that a protein can exist in at least three global forms–functional and folded, functional and intrinsically disordered (nonfolded), and nonfunctional and misfolded/aggregated. Under‐folded protein states are crucial for each of these forms, serving as important folding intermediates of ordered proteins, or as functional states of intrinsically disordered proteins (IDPs) and IDP regions (IDPRs), or as pathology triggers of misfolded proteins. Based on these observations, conformational ensembles of under‐folded proteins can be classified as transient (folding and misfolding intermediates) and permanent (IDPs and stable misfolded proteins). Permanently under‐folded proteins can further be split into intentionally designed (IDPs and IDPRs) and unintentionally designed (misfolded proteins). Although intrinsic flexibility, dynamics, and pliability are crucial for all under‐folded proteins, the different categories of under‐foldedness are differently encoded in protein amino acid sequences. © 2013 Wiley Periodicals, Inc. Biopolymers 99: 870–887, 2013.

Quantitative Characterization of Configurational Space Sampled by HIV-1 Nucleocapsid Using Solution NMR, X-ray Scattering and Protein Engineering

Nucleic-acid-related events in the HIV-1 replication cycle are mediated by nucleocapsid, a small protein comprising two zinc knuckles connected by a short flexible linker and flanked by disordered termini. Combining experimental NMR residual dipolar couplings, solution X-ray scattering and protein engineering with ensemble simulated annealing, we obtain a quantitative description of the configurational space sampled by the two zinc knuckles, the linker and disordered termini in the absence of nucleic acids. We first compute the conformational ensemble (with an optimal size of three members) of an engineered nucleocapsid construct lacking the N- and C-termini that satisfies the experimental restraints, and then validate this ensemble, as well as characterize the disordered termini, using the experimental data from the full-length nucleocapsid construct. The experimental and computational strategy is generally applicable to multidomain proteins. Differential flexibility within the linker results in asymmetric motion of the zinc knuckles which may explain their functionally distinct roles despite high sequence identity. One of the configurations (populated at a level of ≈40 %) closely resembles that observed in various ligand-bound forms, providing evidence for conformational selection and a mechanistic link between protein dynamics and function.

How to tackle protein structural data from solution and solid state: An integrated approach

Long-range NMR restraints, such as diamagnetic residual dipolar couplings and paramagnetic data, can be used to determine 3D structures of macromolecules. They are also used to monitor, and potentially to improve, the accuracy of a macromolecular structure in solution by validating or "correcting" a crystal model. Since crystal structures suffer from crystal packing forces they may not be accurate models for the macromolecular structures in solution. However, the presence of real differences should be tested for by simultaneous refinement of the structure using both crystal and solution NMR data. To achieve this, the program REFMAC5 from CCP4 was modified to allow the simultaneous use of X-ray crystallographic and paramagnetic NMR data and/or diamagnetic residual dipolar couplings. Inconsistencies between crystal structures and solution NMR data, if any, may be due either to structural rearrangements occurring on passing from the solution to solid state, or to a greater degree of conformational heterogeneity in solution with respect to the crystal. In the case of multidomain proteins, paramagnetic restraints can provide the correct mutual orientations and positions of domains in solution, as well as information on the conformational variability experienced by the macromolecule.

Protein docking using an ensemble of spin labels optimized by intra-molecular paramagnetic relaxation enhancement

The effect of spin label mobility on the accuracy of protein–protein docking calculations was investigated using inter- and intra-molecular PRE data.

Investigating protein conformational energy landscapes and atomic resolution dynamics from NMR dipolar couplings: a review

Nuclear magnetic resonance spectroscopy is exquisitely sensitive to protein dynamics. In particular inter-nuclear dipolar couplings, that become measurable in solution when the protein is dissolved in a dilute liquid crystalline solution, report on all conformations sampled up to millisecond timescales. As such they provide the opportunity to describe the Boltzmann distribution present in solution at atomic resolution, and thereby to map the conformational energy landscape in unprecedented detail. The development of analytical methods and approaches based on numerical simulation and their application to numerous biologically important systems is presented.

Dynamic equilibrium between closed and partially closed states of the bacterial Enzyme I unveiled by solution NMR and X-ray scattering

Enzyme I (EI) is the first component in the bacterial phosphotransferase system, a signal transduction pathway in which phosphoryl transfer through a series of bimolecular protein-protein interactions is coupled to sugar transport across the membrane. EI is a multidomain, 128-kDa homodimer that has been shown to exist in two conformational states related to one another by two large (50-90°) rigid body domain reorientations. The open conformation of apo EI allows phosphoryl transfer from His189 located in the N-terminal domain α/β (EIN(α/β)) subdomain to the downstream protein partner bound to the EIN(α) subdomain. The closed conformation, observed in a trapped phosphoryl transfer intermediate, brings the EIN(α/β) subdomain into close proximity to the C-terminal dimerization domain (EIC), thereby permitting in-line phosphoryl transfer from phosphoenolpyruvate (PEP) bound to EIC to His189. Here, we investigate the solution conformation of a complex of an active site mutant of EI (H189A) with PEP. Simulated annealing refinement driven simultaneously by solution small angle X-ray scattering and NMR residual dipolar coupling data demonstrates unambiguously that the EI(H189A)-PEP complex exists in a dynamic equilibrium between two approximately equally populated conformational states, one corresponding to the closed structure and the other to a partially closed species. The latter likely represents an intermediate in the open-to-closed transition.

Structural Impact of Tau Phosphorylation at Threonine 231

Phosphorylation of the microtubule-associated protein Tau influences the assembly and stabilization of microtubules and is deregulated in several neurodegenerative diseases. The high flexibility of Tau, however, has prevented an atomic-level description of its phosphorylation-induced structural changes. Employing an extensive set of distance and orientational restraints together with a novel ensemble calculation approach, we determined conformational ensembles of Tau fragments in the non-phosphorylated state and, when phosphorylated at T231/S235 or T231/S235/S237/S238, four important sites of phosphorylation in Alzheimer disease. Comparison of the molecular ensembles showed that phosphorylation of the regulatory T231 does not perturb the backbone conformation of the proximal microtubule-binding (225)KVAVVR(230) motif. Instead, phosphorylated T231 selectively engages in a salt bridge with R230 that can compete with the formation of intermolecular salt bridges to tubulin. Our study provides an ensemble description which will be useful for the analysis of conformational transitions in Tau and other intrinsically disordered proteins.

Information content of long-range NMR data for the characterization of conformational heterogeneity

Long-range NMR data, namely residual dipolar couplings (RDCs) from external alignment and paramagnetic data, are becoming increasingly popular for the characterization of conformational heterogeneity of multidomain biomacromolecules and protein complexes. The question addressed here is how much information is contained in these averaged data. We have analyzed and compared the information content of conformationally averaged RDCs caused by steric alignment and of both RDCs and pseudocontact shifts caused by paramagnetic alignment, and found that, despite the substantial differences, they contain a similar amount of information. Furthermore, using several synthetic tests we find that both sets of data are equally good towards recovering the major state(s) in conformational distributions.

Transient protein-protein interactions visualized by solution NMR

Proteins interact with each other to establish their identities in cell. The affinities for the interactions span more than ten orders of magnitude, and KD values in μM-mM regimen are considered transient and are important in cell signaling. Solution NMR including diamagnetic and paramagnetic techniques has enabled atomic-resolution depictions of transient protein-protein interactions. Diamagnetic NMR allows characterization of protein complexes with KD values up to several mM, whereas ultraweak and fleeting complexes can be modeled with the use of paramagnetic NMR especially paramagnetic relaxation enhancement (PRE). When tackling ever-larger protein complexes, PRE can be particularly useful in providing long-range intermolecular distance restraints. As NMR measurements are averaged over the ensemble of complex structures, structural information for dynamic protein-protein interactions besides the stereospecific one can often be extracted. Herein the protein interaction dynamics are exemplified by encounter complexes, alternative binding modes, and coupled binding/folding of intrinsically disordered proteins. Further integration of NMR with other biophysical techniques should allow better visualization of transient protein-protein interactions. In particular, single-molecule data may facilitate the interpretation of ensemble-averaged NMR data. Though same structures of proteins and protein complexes were found in cell as in diluted solution, we anticipate that the dynamics of transient protein protein-protein interactions be different, which awaits awaits exploration by NMR. This article is part of a Special Issue entitled: Physiological Enzymology and Protein Functions. This article is part of a Special Issue entitled: Physiological Enzymology and Protein Functions.

Ensemble MD simulations restrained via crystallographic data: accurate structure leads to accurate dynamics

Currently, the best existing molecular dynamics (MD) force fields cannot accurately reproduce the global free-energy minimum which realizes the experimental protein structure. As a result, long MD trajectories tend to drift away from the starting coordinates (e.g., crystallographic structures). To address this problem, we have devised a new simulation strategy aimed at protein crystals. An MD simulation of protein crystal is essentially an ensemble simulation involving multiple protein molecules in a crystal unit cell (or a block of unit cells). To ensure that average protein coordinates remain correct during the simulation, we introduced crystallography-based restraints into the MD protocol. Because these restraints are aimed at the ensemble-average structure, they have only minimal impact on conformational dynamics of the individual protein molecules. So long as the average structure remains reasonable, the proteins move in a native-like fashion as dictated by the original force field. To validate this approach, we have used the data from solid-state NMR spectroscopy, which is the orthogonal experimental technique uniquely sensitive to protein local dynamics. The new method has been tested on the well-established model protein, ubiquitin. The ensemble-restrained MD simulations produced lower crystallographic R factors than conventional simulations; they also led to more accurate predictions for crystallographic temperature factors, solid-state chemical shifts, and backbone order parameters. The predictions for (15) N R1 relaxation rates are at least as accurate as those obtained from conventional simulations. Taken together, these results suggest that the presented trajectories may be among the most realistic protein MD simulations ever reported. In this context, the ensemble restraints based on high-resolution crystallographic data can be viewed as protein-specific empirical corrections to the standard force fields.

The Protein Ensemble Database

The scientific community's major conceptual notion of structural biology has recently shifted in emphasis from the classical structure-function paradigm due to the emergence of intrinsically disordered proteins (IDPs). As opposed to their folded cousins, these proteins are defined by the lack of a stable 3D fold and a high degree of inherent structural heterogeneity that is closely tied to their function. Due to their flexible nature, solution techniques such as small-angle X-ray scattering (SAXS), nuclear magnetic resonance (NMR) spectroscopy and fluorescence resonance energy transfer (FRET) are particularly well-suited for characterizing their biophysical properties. Computationally derived structural ensembles based on such experimental measurements provide models of the conformational sampling displayed by these proteins, and they may offer valuable insights into the functional consequences of inherent flexibility. The Protein Ensemble Database (http://pedb.vib.be) is the first openly accessible, manually curated online resource storing the ensemble models, protocols used during the calculation procedure, and underlying primary experimental data derived from SAXS and/or NMR measurements. By making this previously inaccessible data freely available to researchers, this novel resource is expected to promote the development of more advanced modelling methodologies, facilitate the design of standardized calculation protocols, and consequently lead to a better understanding of how function arises from the disordered state.

Long-range correlated dynamics in intrinsically disordered proteins

Intrinsically disordered proteins (IDPs) are involved in a wide variety of physiological and pathological processes and are best described by ensembles of rapidly interconverting conformers. Using fast field cycling relaxation measurements we here show that the IDP α-synuclein as well as a variety of other IDPs undergoes slow reorientations at time scales comparable to folded proteins. The slow motions are not perturbed by mutations in α-synuclein, which are related to genetic forms of Parkinson's disease, and do not depend on secondary and tertiary structural propensities. Ensemble-based hydrodynamic calculations suggest that the time scale of the underlying correlated motion is largely determined by hydrodynamic coupling between locally rigid segments. Our study indicates that long-range correlated dynamics are an intrinsic property of IDPs and offers a general physical mechanism of correlated motions in highly flexible biomolecular systems.

Recovering a representative conformational ensemble from underdetermined macromolecular structural data

Structural analysis of proteins and nucleic acids is complicated by their inherent flexibility, conferred, for example, by linkers between their contiguous domains. Therefore, the macromolecule needs to be represented by an ensemble of conformations instead of a single conformation. Determining this ensemble is challenging because the experimental data are a convoluted average of contributions from multiple conformations. As the number of the ensemble degrees of freedom generally greatly exceeds the number of independent observables, directly deconvolving experimental data into a representative ensemble is an ill-posed problem. Recent developments in sparse approximations and compressive sensing have demonstrated that useful information can be recovered from underdetermined (ill-posed) systems of linear equations by using sparsity regularization. Inspired by these advances, we designed the Sparse Ensemble Selection (SES) method for recovering multiple conformations from a limited number of observations. SES is more general and accurate than previously published minimum-ensemble methods, and we use it to obtain representative conformational ensembles of Lys48-linked diubiquitin, characterized by the residual dipolar coupling data measured at several pH conditions. These representative ensembles are validated against NMR chemical shift perturbation data and compared to maximum-entropy results. The SES method reproduced and quantified the previously observed pH dependence of the major conformation of Lys48-linked diubiquitin, and revealed lesser-populated conformations that are preorganized for binding known diubiquitin receptors, thus providing insights into possible mechanisms of receptor recognition by polyubiquitin. SES is applicable to any experimental observables that can be expressed as a weighted linear combination of data for individual states.

Exploring regions of conformational space occupied by two-domain proteins

The presence of heterogeneity in the interdomain arrangement of several biomolecules is required for their function. Here we present a method to obtain crucial clues to distinguish between different kinds of protein conformational distributions based on experimental NMR data. The method explores subregions of the conformational space and provides both upper and lower bounds of probability for the system to be in each subregion.

Using small angle solution scattering data in Xplor-NIH structure calculations

This contribution describes the use of small and wide angle X-ray and small angle neutron scattering for biomolecular structure calculation using the program Xplor-NIH, both with and without NMR data. The current algorithms used for calculating scattering curves are described, and the use of scattering data as a structural restraint is given concrete form as a fragment of an Xplor-NIH structure calculation script. We review five examples of the use of scattering data in structure calculation, including the treatment of single domain proteins, nucleic acids, structure determination of large proteins, and the use of ensemble representations to characterize small and large amplitude motions.