MaxOcc: a web portal for maximum occurrence analysis

Computational modeling multiple conformational states of proteins with residual dipolar coupling data

Solution nuclear magnetic resonance spectroscopy provides unique opportunities to study the structure and dynamics of biomolecules in aqueous environments. While spin relaxation methods are well recognized for their ability to probe timescales of motion, residual dipolar couplings (RDCs) provide access to amplitudes and directions of motion, characteristics that are important to the function of these molecules. Although observed in the 1960s, the acquisition and computational analysis of RDCs has gained significant momentum in recent years, and particularly applications to motion in proteins have become more numerous. This trend may well continue as RDCs can easily leverage structures produced by new computational methods (e.g., AlphaFold) to produce functional descriptions. In this report, we provide examples and a summary of the ways that RDCs have been used to confirm the existence of internal dynamics, characterize the type of dynamics, and recover atomic-scale structural ensembles that define the full range of conformational sampling.

Paramagnetic NMR restraints for the characterization of protein structural rearrangements

Mobility is a common feature of biomacromolecules, often fundamental for their function. Thus, in many cases, biomacromolecules cannot be described by a single conformation, but rather by a conformational ensemble. NMR paramagnetic data demonstrated quite informative to monitor this conformational variability, especially when used in conjunction with data from different sources. Due to their long-range nature, paramagnetic data can, for instance, i) clearly demonstrate the occurrence of conformational rearrangements, ii) reveal the presence of minor conformational states, sampled only for a short time, iii) indicate the most representative conformations within the conformational ensemble sampled by the molecule, iv) provide an upper limit to the weight of each conformation.

Reweighting methods for elucidation of conformation ensembles of proteins

Proteins are inherently dynamic macromolecules that exist in equilibrium among multiple conformational states, and motions of protein backbone and side chains are fundamental to biological function. The ability to characterize the conformational landscape is particularly important for intrinsically disordered proteins, multidomain proteins, and weakly bound complexes, where single-structure representations are inadequate. As the focus of structural biology shifts from relatively rigid macromolecules toward larger and more complex systems and molecular assemblies, there is a need for structural approaches that can paint a more realistic picture of such conformationally heterogeneous systems. Here, we review reweighting methods for elucidation of structural ensembles based on experimental data, with the focus on applications to multidomain proteins.

Characterizing conformational ensembles of multi-domain proteins using anisotropic paramagnetic NMR restraints

It has been over two decades since paramagnetic NMR started to form part of the essential techniques for structural analysis of proteins under physiological conditions. Paramagnetic NMR has significantly expanded our understanding of the inherent flexibility of proteins, in particular, those that are formed by combinations of two or more domains. Here, we present a brief overview of techniques to characterize conformational ensembles of such multi-domain proteins using paramagnetic NMR restraints produced through anisotropic metals, with a focus on the basics of anisotropic paramagnetic effects, the general procedures of conformational ensemble reconstruction, and some representative reweighting approaches.

Conformational Space Sampled by Domain Reorientation of Linear Diubiquitin Reflected in Its Binding Mode for Target Proteins

Linear polyubiquitin chains regulate diverse signaling proteins, in which the chains adopt various conformations to recognize different target proteins. Thus, the structural plasticity of the chains plays an important role in controlling the binding events. Herein, paramagnetic NMR spectroscopy is employed to explore the conformational space sampled by linear diubiquitin, a minimal unit of linear polyubiquitin, in its free state. Rigorous analysis of the data suggests that, regarding the relative positions of the ubiquitin units, particular regions of conformational space are preferentially sampled by the molecule. By combining these results with further data collected for charge-reversal derivatives of linear diubiquitin, structural insights into the factors underlying the binding events of linear diubiquitin are obtained.

Characterization of lanthanoid-binding proteins using NMR spectroscopy

The variety of magnetic properties exhibited by paramagnetic lanthanoids provides outstanding information in NMR-based structural biology and therefore can be a very useful tool for characterizing lanthanoid-binding proteins. Because of their dependence on the relative positions of the protein nuclei and of the lanthanoid ion, the paramagnetic restraints (PCS, PRDC and PRE) provide information on structure and dynamics of proteins. In this Chapter, we cover the use of lanthanoids in structural biology including protein sample preparation, NMR experiments and data interpretation.

The Photocatalyzed Thiol-ene reaction: A New Tag to Yield Fast, Selective and reversible Paramagnetic Tagging of Proteins

Paramagnetic restraints have been used in biomolecular NMR for the last three decades to elucidate and refine biomolecular structures, but also to characterize protein-ligand interactions. A common technique to generate such restraints in proteins, which do not naturally contain a (paramagnetic) metal, consists in the attachment to the protein of a lanthanide-binding-tag (LBT). In order to design such LBTs, it is important to consider the efficiency and stability of the conjugation, the geometry of the complex (conformational exchanges and coordination) and the chemical inertness of the ligand. Here we describe a photo-catalyzed thiol-ene reaction for the cysteine-selective paramagnetic tagging of proteins. As a model, we designed an LBT with a vinyl-pyridine moiety which was used to attach our tag to the protein GB1 in fast and irreversible fashion. Our tag T1 yields magnetic susceptibility tensors of significant size with different lanthanides and has been characterized using NMR and relaxometry measurements.

Assessing protein conformational landscapes: integration of DEER data in Maximum Occurrence analysis

The properties of the conformational landscape of a biomolecule are of capital importance to understand its function. It is widely accepted that a statistical ensemble is far more representative than a single structure, especially for proteins with disordered regions. While experimental data provide the most important handle on the conformational variability that the system is experiencing, they usually report on either time or ensemble averages. Since the available conformations largely outnumber the (independent) available experimental data, the latter can be equally well reproduced by a variety of ensembles. We have proposed the Maximum Occurrence (MaxOcc) approach to provide an upper bound of the statistical weight of each conformation. This method is expected to converge towards the true statistical weights by increasing the number of independent experimental datasets. In this paper we explore the ability of DEER (Double Electron Electron Resonance) data, which report on the distance distribution between two spin labels attached to a biomolecule, to restrain the MaxOcc values and its complementarity to previously introduced experimental techniques such as NMR and Small-Angle X-ray Scattering. We here present the case of Ca2+ bound calmodulin (CaM) as a test case and show that DEER data impose a sizeable reduction of the conformational space described by high MaxOcc conformations.

Treating Biomacromolecular Conformational Variability

The function of a biomacromolecule is related not only to its structure but also to the different conformations that its structural elements can sample. It is therefore important to determine the extent of the structural fluctuations and to identify the states that are actually populated as a result of the rearrangement. However, this accomplishment is undermined by an intrinsic limitation: the amount of experimental data is by and large inferior to the number of the states that a biomacromolecule can actually sample. This means that additional, a priori information must be applied in order to derive the most from the available experimental data but not to run into overinterpretation. In this chapter we will give a summary of the experimental observables that can be used towards the reconstruction of structural ensembles, how the data can be profitably combined and to what extent the data are affected by error; finally we will give an overview of the computational methods that have been developed to model structural ensembles, highlighting their difference and similarities, advantages and disadvantages.

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.

Perspectives on paramagnetic NMR from a life sciences infrastructure

The effects arising in NMR spectroscopy because of the presence of unpaired electrons, collectively referred to as "paramagnetic NMR" have attracted increasing attention over the last decades. From the standpoint of the structural and mechanistic biology, paramagnetic NMR provides long range restraints that can be used to assess the accuracy of crystal structures in solution and to improve them by simultaneous refinements through NMR and X-ray data. These restraints also provide information on structure rearrangements and conformational variability in biomolecular systems. Theoretical improvements in quantum chemistry calculations can nowadays allow for accurate calculations of the paramagnetic data from a molecular structural model, thus providing a tool to refine the metal coordination environment by matching the paramagnetic effects observed far away from the metal. Furthermore, the availability of an improved technology (higher fields and faster magic angle spinning) has promoted paramagnetic NMR applications in the fast-growing area of biomolecular solid-state NMR. Major improvements in dynamic nuclear polarization have been recently achieved, especially through the exploitation of the Overhauser effect occurring through the contact-driven relaxation mechanism: the very large enhancement of the ¹³C signal observed in a variety of liquid organic compounds at high fields is expected to open up new perspectives for applications of solution NMR.

Combining NMR and small angle X-ray scattering for the study of biomolecular structure and dynamics

Small-angle X-ray scattering (SAXS) and Nuclear Magnetic Resonance (NMR) are established methods to analyze the structure and structural transitions of biological macromolecules in solution. Both methods are directly applicable to near-native macromolecular solutions and allow one to study structural responses to physical and chemical changes or ligand additions. Whereas SAXS is applied to elucidate overall structure, interactions and flexibility over a wide range of particle sizes, NMR yields atomic resolution detail for moderately sized macromolecules. NMR is arguably the most powerful technique for the experimental analysis of dynamics. The joint application of these two highly complementary techniques provides an extremely useful approach that facilitates comprehensive characterization of biomacromolecular solutions.

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SAXS and NMR are effective and highly complementary techniques in structural biology.

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Constraints from SAXS can be readily incorporated in NMR structure calculations.

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High resolution NMR models of domains can serve as building blocks for SAXS-based rigid body modeling.

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Flexible systems can be well described using ensemble approaches combining SAXS and NMR.

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Dynamics studies can be enhanced by combining SAXS and NMR.

Identification of productive and futile encounters in an electron transfer protein complex

Well-defined, stereospecific states in protein complexes are often in exchange with an ensemble of more dynamic orientations: the encounter states. The structure of the stereospecific complex between cytochrome P450cam and putidaredoxin was solved recently by X-ray diffraction as well as paramagnetic NMR spectroscopy. Other than the stereospecific complex, the NMR data clearly show the presence of additional states in the complex in solution. In these encounter states, populated for a small percentage of the time, putidaredoxin assumes multiple orientations and samples a large part of the surface of cytochrome P450cam. To characterize the nature of the encounter states, an extensive paramagnetic NMR dataset has been analyzed using the Maximum Occurrence of Regions methodology. The analysis reveals the location and maximal spatial extent of the additional states needed to fully explain the NMR data. Under the assumption of sparsity of the size of the conformational ensemble, several minor states can be located quite precisely. The distribution of these minor states correlates with the electrostatic potential map around cytochrome P450cam. Whereas some minor states are on isolated positively charged patches, others are connected to the stereospecific site via positively charged paths. The existence of electrostatically favorable pathways between the stereospecific interaction site and the different minor states or lack thereof suggests a means to discriminate between productive and futile encounter states.

Inter-helical conformational preferences of HIV-1 TAR-RNA from maximum occurrence analysis of NMR data and molecular dynamics simulations

Detecting conformational heterogeneity in biological macromolecules is a key for the understanding of their biological function. We here provide a comparison between two independent approaches to assess conformational heterogeneity: molecular dynamics simulations, performed without inclusion of any experimental data, and maximum occurrence (MaxOcc) distribution over the topologically available conformational space. The latter only reflects the extent of the averaging and identifies regions which are most compliant with the experimentally measured NMR Residual Dipolar Couplings (RDCs). The analysis was performed for the HIV-1 TAR RNA, consisting of two helical domains connected by a flexible bulge junction, for which four sets of RDCs were available as well as an 8.2 μs all-atom molecular dynamics simulation. A sample and select approach was previously applied to extract from the molecular dynamics trajectory conformational ensembles in agreement with the four sets of RDCs. The MaxOcc analysis performed here identifies the most likely sampled region in the conformational space of the system which, strikingly, overlaps well with the structures independently sampled in the molecular dynamics calculations and even better with the RDC selected ensemble.

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.

Prion Protein-Antibody Complexes Characterized by Chromatography-Coupled Small-Angle X-Ray Scattering

Aberrant self-assembly, induced by structural misfolding of the prion proteins, leads to a number of neurodegenerative disorders. In particular, misfolding of the mostly α-helical cellular prion protein (PrP(C)) into a β-sheet-rich disease-causing isoform (PrP(Sc)) is the key molecular event in the formation of PrP(Sc) aggregates. The molecular mechanisms underlying the PrP(C)-to-PrP(Sc) conversion and subsequent aggregation remain to be elucidated. However, in persistently prion-infected cell-culture models, it was shown that treatment with monoclonal antibodies against defined regions of the prion protein (PrP) led to the clearing of PrP(Sc) in cultured cells. To gain more insight into this process, we characterized PrP-antibody complexes in solution using a fast protein liquid chromatography coupled with small-angle x-ray scattering (FPLC-SAXS) procedure. High-quality SAXS data were collected for full-length recombinant mouse PrP [denoted recPrP(23-230)] and N-terminally truncated recPrP(89-230), as well as their complexes with each of two Fab fragments (HuM-P and HuM-R1), which recognize N- and C-terminal epitopes of PrP, respectively. In-line measurements by fast protein liquid chromatography coupled with SAXS minimized data artifacts caused by a non-monodispersed sample, allowing structural analysis of PrP alone and in complex with Fab antibodies. The resulting structural models suggest two mechanisms for how these Fabs may prevent the conversion of PrP(C) into PrP(Sc).

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.

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.

Visualizing transient dark states by NMR spectroscopy

Myriad biological processes proceed through states that defy characterization by conventional atomic-resolution structural biological methods. The invisibility of these 'dark' states can arise from their transient nature, low equilibrium population, large molecular weight, and/or heterogeneity. Although they are invisible, these dark states underlie a range of processes, acting as encounter complexes between proteins and as intermediates in protein folding and aggregation. New methods have made these states accessible to high-resolution analysis by nuclear magnetic resonance (NMR) spectroscopy, as long as the dark state is in dynamic equilibrium with an NMR-visible species. These methods - paramagnetic NMR, relaxation dispersion, saturation transfer, lifetime line broadening, and hydrogen exchange - allow the exploration of otherwise invisible states in exchange with a visible species over a range of timescales, each taking advantage of some unique property of the dark state to amplify its effect on a particular NMR observable. In this review, we introduce these methods and explore two specific techniques - paramagnetic relaxation enhancement and dark state exchange saturation transfer - in greater detail.

FANTEN: a new web-based interface for the analysis of magnetic anisotropy-induced NMR data

Pseudocontact shifts (PCSs) and residual dipolar couplings (RDCs) arising from the presence of paramagnetic metal ions in proteins as well as RDCs due to partial orientation induced by external orienting media are nowadays routinely measured as a part of the NMR characterization of biologically relevant systems. PCSs and RDCs are becoming more and more popular as restraints (1) to determine and/or refine protein structures in solution, (2) to monitor the extent of conformational heterogeneity in systems composed of rigid domains which can reorient with respect to one another, and (3) to obtain structural information in protein-protein complexes. The use of both PCSs and RDCs proceeds through the determination of the anisotropy tensors which are at the origin of these NMR observables. A new user-friendly web tool, called FANTEN (Finding ANisotropy TENsors), has been developed for the determination of the anisotropy tensors related to PCSs and RDCs and has been made freely available through the WeNMR ( http://fanten-enmr.cerm.unifi.it:8080 ) gateway. The program has many new features not available in other existing programs, among which the possibility of a joint analysis of several sets of PCS and RDC data and the possibility to perform rigid body minimizations.

Structural characterization of a flexible two-domain protein in solution using small angle X-ray scattering and NMR data

Multidomain proteins in which individual domains are connected by linkers often possess inherent interdomain flexibility that significantly complicates their structural characterization in solution using either nuclear magnetic resonance (NMR) spectroscopy or small-angle X-ray scattering (SAXS) alone. Here, we report a protocol for joint refinement of flexible multidomain protein structures against NMR distance and angular restraints, residual dipolar couplings, and SAXS data. The protocol is based on the ensemble optimization method principle (Bernadó et al., 2007) and is compared with different refinement strategies for the structural characterization of the flexible two-domain protein sf3636 from Shigella flexneri 2a. The results of our refinement suggest the existence of a dominant population of configurational states in solution possessing an overall elongated shape and restricted relative twisting of the two domains.

Insights into domain-domain motions in proteins and RNA from solution NMR

Many multidomain proteins and ribonucleic acids consist of domains that autonomously fold and that are linked together by flexible junctions. This architectural design allows domains to sample a wide range of positions with respect to one another, yet do so in a way that retains structural specificity, since the number of sampled conformations remains extremely small compared to the total conformations that would be sampled if the domains were connected by an infinitely long linker. This “tuned” flexibility in interdomain conformation is in turn used in many biochemical processes.

There is great interest in characterizing the dynamic properties of multidomain systems, and moving beyond conventional descriptions in terms of static structures, toward the characterization of population-weighted ensembles describing a distribution of many conformations sampled in solution. There is also great interest in understanding the design principles and underlying physical and chemical interactions that specify the nature of interdomain flexibility. NMR spectroscopy is one of the most powerful techniques for characterizing motions in complex biomolecules and has contributed greatly toward our basic understanding of dynamics in proteins and nucleic acids and its role in folding, recognition, and signaling.

Here, we review methods that have been developed in our laboratories to address these challenges. Our approaches are based on the ability of one domain of the molecule to self-align in a magnetic field, or to dominate the overall orientation of the molecule, so that the conformational freedom of other domains can be assessed by their degree of alignment induced by the aligned part. In turn, this self-alignment ability can be intrinsic or can be caused by tagging appropriate constructs to the molecule of interest. In general, self-alignment is due to magnetic susceptibility anisotropy. Nucleic acids with elongated helices have this feature, as well as several paramagnetic metal centers that can be found in, or attached to, a protein domain.

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.

The dynamic duo: combining NMR and small angle scattering in structural biology

Structural biology provides essential information for elucidating molecular mechanisms that underlie biological function. Advances in hardware, sample preparation, experimental methods, and computational approaches now enable structural analysis of protein complexes with increasing complexity that more closely represent biologically entities in the cellular environment. Integrated multidisciplinary approaches are required to overcome limitations of individual methods and take advantage of complementary aspects provided by different structural biology techniques. Although X-ray crystallography remains the method of choice for structural analysis of large complexes, crystallization of flexible systems is often difficult and does typically not provide insights into conformational dynamics present in solution. Nuclear magnetic resonance spectroscopy (NMR) is well-suited to study dynamics at picosecond to second time scales, and to map binding interfaces even of large systems at residue resolution but suffers from poor sensitivity with increasing molecular weight. Small angle scattering (SAS) methods provide low resolution information in solution and can characterize dynamics and conformational equilibria complementary to crystallography and NMR. The combination of NMR, crystallography, and SAS is, thus, very useful for analysis of the structure and conformational dynamics of (large) protein complexes in solution. In high molecular weight systems, where NMR data are often sparse, SAS provides additional structural information and can differentiate between NMR-derived models. Scattering data can also validate the solution conformation of a crystal structure and indicate the presence of conformational equilibria. Here, we review current state-of-the-art approaches for combining NMR, crystallography, and SAS data to characterize protein complexes in solution.

Simultaneous use of solution NMR and X-ray data in REFMAC5 for joint refinement/detection of structural differences

The program REFMAC5 from CCP4 was modified to allow the simultaneous use of X-ray crystallographic data and paramagnetic NMR data (pseudocontact shifts and self-orientation residual dipolar couplings) and/or diamagnetic residual dipolar couplings. Incorporation of these long-range NMR restraints in REFMAC5 can reveal differences between solid-state and solution conformations of molecules or, in their absence, can be used together with X-ray crystallographic data for structural refinement. Since NMR and X-ray data are complementary, when a single structure is consistent with both sets of data and still maintains reasonably `ideal' geometries, the reliability of the derived atomic model is expected to increase. The program was tested on five different proteins: the catalytic domain of matrix metalloproteinase 1, GB3, ubiquitin, free calmodulin and calmodulin complexed with a peptide. In some cases the joint refinement produced a single model consistent with both sets of observations, while in other cases it indicated, outside the experimental uncertainty, the presence of different protein conformations in solution and in the solid state.

Examination of matrix metalloproteinase-1 in solution: a preference for the pre-collagenolysis state

Catalysis of collagen degradation by matrix metalloproteinase 1 (MMP-1) has been proposed to critically rely on flexibility between the catalytic (CAT) and hemopexin-like (HPX) domains. A rigorous assessment of the most readily accessed conformations in solution is required to explain the onset of substrate recognition and collagenolysis. The present study utilized paramagnetic NMR spectroscopy and small angle x-ray scattering (SAXS) to calculate the maximum occurrence (MO) of MMP-1 conformations. The MMP-1 conformations with large MO values (up to 47%) are restricted into a relatively small conformational region. All conformations with high MO values differ largely from the closed MMP-1 structures obtained by x-ray crystallography. The MO of the latter is ~20%, which represents the upper limit for the presence of this conformation in the ensemble sampled by the protein in solution. In all the high MO conformations, the CAT and HPX domains are not in tight contact, and the residues of the HPX domain reported to be responsible for the binding to the collagen triple-helix are solvent exposed. Thus, overall analysis of the highest MO conformations indicated that MMP-1 in solution was poised to interact with collagen and then could readily proceed along the steps of collagenolysis.

Ensemble-based interpretations of NMR structural data to describe protein internal dynamics

NMR spectroscopy is the leading technique to characterize protein internal dynamics at the atomic level and on multiple time scales. However, the structural interpretation of the observables obtained by various measurements is not always straightforward and in many cases dynamics-related parameters are only used to “decorate” static structural models without offering explicit description of conformational heterogeneity. To overcome such limitations, several computational techniques have been developed to generate ensemble-based representations of protein structure and dynamics with the use of NMR-derived data. An important common aspect of the methods is that NMR observables and derived parameters are interpreted as properties of the ensemble instead of individual conformers. The resulting ensembles reflect the experimentally determined internal mobility of proteins at a given time scale and can be used to understand the role of internal motions in biological processes at atomic detail. In this review we provide an overview of the calculation methods currently available and examples of biological insights obtained by the ensemble-based models of the proteins investigated.