The dynamics of linear polyubiquitin

Rescaling protein-protein interactions improves Martini 3 for flexible proteins in solution

Multidomain proteins with flexible linkers and disordered regions play important roles in many cellular processes, but characterizing their conformational ensembles is difficult. We have previously shown that the coarse-grained model, Martini 3, produces too compact ensembles in solution, that may in part be remedied by strengthening protein-water interactions. Here, we show that decreasing the strength of protein-protein interactions leads to improved agreement with experimental data on a wide set of systems. We show that the 'symmetry' between rescaling protein-water and protein-protein interactions breaks down when studying interactions with or within membranes; rescaling protein-protein interactions better preserves the binding specificity of proteins with lipid membranes, whereas rescaling protein-water interactions preserves oligomerization of transmembrane helices. We conclude that decreasing the strength of protein-protein interactions improves the accuracy of Martini 3 for IDPs and multidomain proteins, both in solution and in the presence of a lipid membrane.

Assessing the Martini 3 protein model: A review of its path and potential

Coarse-grained (CG) protein models have become indispensable tools for studying many biological protein details, from conformational dynamics to the organization of protein macro-complexes, and even the interaction of proteins with other molecules. The Martini force field is one of the most widely used CG models for bio-molecular simulations, partly because of the enormous success of its protein model. With the recent release of a new and improved version of the Martini force field - Martini 3 - a new iteration of its protein model was also made available. The Martini 3 protein force field is an evolution of its Martini 2 counterpart, aimed at improving many of the shortcomings that had been previously identified. In this mini-review, we first provide a general overview of the model and then focus on the successful advances made in the short time since its release, many of which would not have been possible before. Furthermore, we discuss reported limitations, potential directions for model improvement and comment on what the likely future development and application avenues are.

Accurate model and ensemble refinement using cryo-electron microscopy maps and Bayesian inference

Converting cryo-electron microscopy (cryo-EM) data into high-quality structural models is a challenging problem of outstanding importance. Current refinement methods often generate unbalanced models in which physico-chemical quality is sacrificed for excellent fit to the data. Furthermore, these techniques struggle to represent the conformational heterogeneity averaged out in low-resolution regions of density maps. Here we introduce EMMIVox, a Bayesian inference approach to determine single-structure models as well as structural ensembles from cryo-EM maps. EMMIVox automatically balances experimental information with accurate physico-chemical models of the system and the surrounding environment, including waters, lipids, and ions. Explicit treatment of data correlation and noise as well as inference of accurate B-factors enable determination of structural models and ensembles with both excellent fit to the data and high stereochemical quality, thus outperforming state-of-the-art refinement techniques. EMMIVox represents a flexible approach to determine high-quality structural models that will contribute to advancing our understanding of the molecular mechanisms underlying biological functions.

Cryo-electron Microscopy and Molecular Modeling Methods to Characterize the Dynamics of Tau Bound to Microtubules

The electron microscopy metainference integrative structural biology method enables the combination of cryo-electron microscopy electron density maps with molecular modeling techniques such as molecular dynamics to unveil the atomistic biomolecular structural ensemble and the error in the map data in an efficient manner. Here we illustrate the electron microscopy metainference protocol and analysis used to elucidate the atomistic structural ensemble of the microtubule-associated protein tau bound to microtubules by using state-of-the-art molecular mechanic force field and the electron density map.

Accurate and Efficient SAXS/SANS Implementation Including Solvation Layer Effects Suitable for Molecular Simulations

Small-angle X-ray and neutron scattering (SAXS/SANS) provide valuable insights into the structure and dynamics of biomolecules in solution, complementing a wide range of structural techniques, including molecular dynamics simulations. As contrast-based methods, they are sensitive not only to structural properties but also to solvent-solute interactions. Their use in molecular dynamics simulations requires a forward model that should be as fast and accurate as possible. In this work, we demonstrate the feasibility of calculating SAXS and SANS intensities using a coarse-grained representation consisting of one bead per amino acid and three beads per nucleic acid, with form factors that can be corrected on the fly to account for solvation effects at no additional computational cost. By coupling this forward model with molecular dynamics simulations restrained with SAS data, it is possible to determine conformational ensembles or refine the structure and dynamics of proteins and nucleic acids in agreement with the experimental results. To assess the robustness of this approach, we applied it to gelsolin, for which we acquired SAXS data on its closed state, and to a UP1-microRNA complex, for which we used previously collected measurements. Our hybrid-resolution small-angle scattering (hySAS) implementation, being distributed in PLUMED, can be used with atomistic and coarse-grained simulations using diverse restraining strategies.

Current and future directions of USP7 interactome in cancer study

The ubiquitin-proteasome system (UPS) is an essential protein quality controller for regulating protein homeostasis and autophagy. Ubiquitination is a protein modification process that involves the binding of one or more ubiquitins to substrates through a series of enzymatic processes. These include ubiquitin-activating enzymes (E1), ubiquitin-conjugating enzymes (E2), and ubiquitin ligases (E3). Conversely, deubiquitination is a reverse process that removes ubiquitin from substrates via deubiquitinating enzymes (DUBs). Dysregulation of ubiquitination-related enzymes can lead to various human diseases, including cancer, through the modulation of protein ubiquitination. The most structurally and functionally studied DUB is the ubiquitin-specific protease 7 (USP7). Both the TRAF and UBL domains of USP7 are known to bind to the [P/A/E]-X-X-S or K-X-X-X-K motif of substrates. USP7 has been shown to be involved in cancer pathogenesis by binding with numerous substrates. Recently, a novel substrate of USP7 was discovered through a systemic analysis of its binding motif. This review summarizes the currently discovered substrates and cellular functions of USP7 in cancer and suggests putative substrates of USP7 through a comprehensive systemic analysis.

Pragmatic Coarse-Graining of Proteins: Models and Applications

The molecular details involved in the folding, dynamics, organization, and interaction of proteins with other molecules are often difficult to assess by experimental techniques. Consequently, computational models play an ever-increasing role in the field. However, biological processes involving large-scale protein assemblies or long time scale dynamics are still computationally expensive to study in atomistic detail. For these applications, employing coarse-grained (CG) modeling approaches has become a key strategy. In this Review, we provide an overview of what we call pragmatic CG protein models, which are strategies combining, at least in part, a physics-based implementation and a top-down experimental approach to their parametrization. In particular, we focus on CG models in which most protein residues are represented by at least two beads, allowing these models to retain some degree of chemical specificity. A description of the main modern pragmatic protein CG models is provided, including a review of the most recent applications and an outlook on future perspectives in the field.

Polyubiquitin ligand-induced phase transitions are optimized by spacing between ubiquitin units

Biomolecular condensates form via multivalent interactions among key macromolecules and are regulated through ligand binding and/or posttranslational modifications. One such modification is ubiquitination, the covalent addition of ubiquitin (Ub) or polyubiquitin chains to target macromolecules. Specific interactions between polyubiquitin chains and partner proteins, including hHR23B, NEMO, and UBQLN2, regulate condensate assembly or disassembly. Here, we used a library of designed polyubiquitin hubs and UBQLN2 as model systems for determining the driving forces of ligand-mediated phase transitions. Perturbations to either the UBQLN2-binding surface of Ub or the spacing between Ub units reduce the ability of hubs to modulate UBQLN2 phase behavior. By developing an analytical model based on polyphasic linkage principles that accurately described the effects of different hubs on UBQLN2 phase separation, we determined that introduction of Ub to UBQLN2 condensates incurs a significant inclusion energetic penalty. This penalty antagonizes the ability of polyUb hubs to scaffold multiple UBQLN2 molecules and cooperatively amplify phase separation. The extent to which polyubiquitin hubs promote UBQLN2 phase separation is encoded in the spacings between Ub units. This spacing is modulated by chains of different linkages and designed chains of different architectures, thus illustrating how the ubiquitin code regulates functionality via the emergent properties of the condensate. The spacing in naturally occurring linear polyubiquitin chains is already optimized to promote phase separation with UBQLN2. We expect our findings to extend to other condensates, emphasizing the importance of ligand properties, including concentration, valency, affinity, and spacing between binding sites in studies and designs of condensates.

Specifying conformational heterogeneity of multi-domain proteins at atomic resolution

The conformational landscape of multi-domain proteins is inherently linked to their specific functions. This also holds for polyubiquitin chains that are assembled by two or more ubiquitin domains connected by a flexible linker thus showing a large interdomain mobility. However, molecular recognition and signal transduction are associated with particular conformational substates that are populated in solution. Here, we apply high-resolution NMR spectroscopy in combination with dual-scale MD simulations to explore the conformational space of K6-, K29-, and K33-linked diubiquitin molecules. The conformational ensembles are evaluated utilizing a paramagnetic cosolute reporting on solvent exposure plus a set of complementary NMR parameters. This approach unravels a conformational heterogeneity of diubiquitins and explains the diversity of structural models that have been determined for K6-, K29-, and K33-linked diubiquitins in free and ligand-bound states so far. We propose a general application of the approach developed here to demystify multi-domain proteins occurring in nature.

Solution structure of the HOIL-1L NZF domain reveals a conformational switch regulating linear ubiquitin affinity

Attachment of polyubiquitin (poly-Ub) chains to proteins is a major posttranslational modification in eukaryotes. Linear ubiquitin chain assembly complex, consisting of HOIP (HOIL-1-interacting protein), HOIL-1L (heme-oxidized IRP2 Ub ligase 1), and SHARPIN (Shank-associated RH domain-interacting protein), specifically synthesizes "head-to-tail" poly-Ub chains, which are linked via the N-terminal methionine α-amino and C-terminal carboxylate of adjacent Ub units and are thus commonly called "linear" poly-Ub chains. Linear ubiquitin chain assembly complex-assembled linear poly-Ub chains play key roles in immune signaling and suppression of cell death and have been associated with immune diseases and cancer; HOIL-1L is one of the proteins known to selectively bind linear poly-Ub via its Npl4 zinc finger (NZF) domain. Although the structure of the bound form of the HOIL-1L NZF domain with linear di-Ub is known, several aspects of the recognition specificity remain unexplained. Here, we show using NMR and orthogonal biophysical methods, how the NZF domain evolves from a free to the specific linear di-Ub-bound state while rejecting other potential Ub species after weak initial binding. The solution structure of the free NZF domain revealed changes in conformational stability upon linear Ub binding, and interactions between the NZF core and tail revealed conserved electrostatic contacts, which were sensitive to charge modulation at a reported phosphorylation site: threonine-207. Phosphomimetic mutations reduced linear Ub affinity by weakening the integrity of the linear di-Ub-bound conformation. The described molecular determinants of linear di-Ub binding provide insight into the dynamic aspects of the Ub code and the NZF domain's role in full-length HOIL-1L.

SANS Spectra with PLUMED: Implementation and Application to Metainference

Using small-angle scattering with either X-ray or neutron sources has become common in the investigation of soft-matter systems. These experiments provide information about the coarse shape of the scattered objects, but obtaining more-detailed information can usually only be achieved with the aid of molecular simulations. In this Application Note, we report the implementation of an extension in PLUMED to compute the small-angle neutron scattering (SANS), which can be used for data processing as well for enhanced sampling, in particular with the metainference method to bias simulations and sample structures with a resulting spectrum in agreement with an experimental reference. Our implementation includes a resolution function that can be used to smear the SANS intensities according to beamline error sources and is compatible with both all-atom and coarse-grained simulations. Scripts to aid in the calculation of the scattering lengths when the system is coarse-grained and to aid in preparing the inputs are provided. We illustrate the use of the implementation with metainference by performing coarse-grained simulations of beta-octylglucoside and dodecylphosphocholine micelles in water. With different software and different Hamiltonians, we show that the metainference SANS bias can drive micelles to be split and to change shapes to achieve a better agreement with the experimental reference.

Determination of the Structure and Dynamics of the Fuzzy Coat of an Amyloid Fibril of IAPP Using Cryo-Electron Microscopy

In recent years, major advances in cryo-electron microscopy (cryo-EM) have enabled the routine determination of complex biomolecular structures at atomistic resolution. An open challenge for this approach, however, concerns large systems that exhibit continuous dynamics. To address this problem, we developed the metadynamic electron microscopy metainference (MEMMI) method, which incorporates metadynamics, an enhanced conformational sampling approach, into the metainference method of integrative structural biology. MEMMI enables the simultaneous determination of the structure and dynamics of large heterogeneous systems by combining cryo-EM density maps with prior information through molecular dynamics, while at the same time modeling the different sources of error. To illustrate the method, we apply it to elucidate the dynamics of an amyloid fibril of the islet amyloid polypeptide (IAPP). The resulting conformational ensemble provides an accurate description of the structural variability of the disordered region of the amyloid fibril, known as fuzzy coat. The conformational ensemble also reveals that in nearly half of the structural core of this amyloid fibril, the side chains exhibit liquid-like dynamics despite the presence of the highly ordered network backbone of hydrogen bonds characteristic of the cross-β structure of amyloid fibrils.

The pros and cons of ubiquitination on the formation of protein condensates

Ubiquitination, a post-translational modification that attaches one or more ubiquitin (Ub) molecules to another protein, plays a crucial role in the phase-separation processes. Ubiquitination can modulate the formation of membrane-less organelles in two ways. First, a scaffold protein drives phase separation, and Ub is recruited to the condensates. Second, Ub actively phase-separates through the interactions with other proteins. Thus, the role of ubiquitination and the resulting polyUb chains ranges from bystanders to active participants in phase separation. Moreover, long polyUb chains may be the primary driving force for phase separation. We further discuss that the different roles can be determined by the lengths and linkages of polyUb chains which provide preorganized and multivalent binding platforms for other client proteins. Together, ubiquitination adds a new layer of regulation for the flow of material and information upon cellular compartmentalization of proteins.

Protein posttranslational modifications in health and diseases: Functions, regulatory mechanisms, and therapeutic implications

Protein posttranslational modifications (PTMs) refer to the breaking or generation of covalent bonds on the backbones or amino acid side chains of proteins and expand the diversity of proteins, which provides the basis for the emergence of organismal complexity. To date, more than 650 types of protein modifications, such as the most well-known phosphorylation, ubiquitination, glycosylation, methylation, SUMOylation, short-chain and long-chain acylation modifications, redox modifications, and irreversible modifications, have been described, and the inventory is still increasing. By changing the protein conformation, localization, activity, stability, charges, and interactions with other biomolecules, PTMs ultimately alter the phenotypes and biological processes of cells. The homeostasis of protein modifications is important to human health. Abnormal PTMs may cause changes in protein properties and loss of protein functions, which are closely related to the occurrence and development of various diseases. In this review, we systematically introduce the characteristics, regulatory mechanisms, and functions of various PTMs in health and diseases. In addition, the therapeutic prospects in various diseases by targeting PTMs and associated regulatory enzymes are also summarized. This work will deepen the understanding of protein modifications in health and diseases and promote the discovery of diagnostic and prognostic markers and drug targets for diseases.

Experiment-guided molecular simulations define a heterogeneous structural ensemble for the PTPN11 tandem SH2 domains

SHP2 plays an important role in regulating cellular processes, and its pathogenic mutations cause developmental disorders and are linked to cancer. SHP2 is a multidomain protein, comprising two SH2 domains arranged in tandem, a catalytic PTP domain, and a disordered C-terminal tail. SHP2 is activated upon binding two linked phosphopeptides to its SH2 domains, and the peptide orientation and spacing between binding sites are critical for enzymatic activation. For decades, the tandem SH2 has been extensively studied to identify the relative orientation of the two SH2 domains that most effectively binds effectors. So far, neither crystallography nor experiments in solution have provided conclusive results. Using experiment-guided molecular simulations, we determine the heterogeneous structural ensemble of the tandem SH2 in solution in agreement with experimental data from small-angle X-ray scattering and NMR residual dipolar couplings. In the solution ensemble, N-SH2 adopts different orientations and positions relative to C-SH2. We suggest that the intrinsic structural plasticity of the tandem SH2 allows SHP2 to respond to external stimuli and is essential for its functional activity.

Decoding optimal ligand design for multicomponent condensates

Biomolecular condensates form via multivalent interactions among key macromolecules and are regulated through ligand binding and/or post-translational modifications. One such modification is ubiquitination, the covalent addition of ubiquitin (Ub) or polyubiquitin chains to target macromolecules for various cellular processes. Specific interactions between polyubiquitin chains and partner proteins, including hHR23B, NEMO, and UBQLN2, regulate condensate assembly or disassembly. Here, we used a library of designed polyubiquitin hubs and UBQLN2 as model systems for determining the driving forces of ligand-mediated phase transitions. Perturbations to the UBQLN2-binding surface of Ub or deviations from the optimal spacing between Ub units reduce the ability of hubs to modulate UBQLN2 phase behavior. By developing an analytical model that accurately described the effects of different hubs on UBQLN2 phase diagrams, we determined that introduction of Ub to UBQLN2 condensates incurs a significant inclusion energetic penalty. This penalty antagonizes the ability of polyUb hubs to scaffold multiple UBQLN2 molecules and cooperatively amplify phase separation. Importantly, the extent to which polyubiquitin hubs can promote UBQLN2 phase separation are encoded in the spacings between Ub units as found for naturally-occurring chains of different linkages and designed chains of different architectures, thus illustrating how the ubiquitin code regulates functionality via the emergent properties of the condensate. We expect our findings to extend to other condensates necessitating the consideration of ligand properties, including concentration, valency, affinity, and spacing between binding sites in studies and designs of condensates.

Effective Molecular Dynamics from Neural Network-Based Structure Prediction Models

Recent breakthroughs in neural network-based structure prediction methods, such as AlphaFold2 and RoseTTAFold, have dramatically improved the quality of computational protein structure prediction. These models also provide statistical confidence scores that can estimate uncertainties in the predicted structures, but it remains unclear to what extent these scores are related to the intrinsic conformational dynamics of proteins. Here, we compare AlphaFold2 prediction scores with explicit large-scale molecular dynamics simulations of 28 one- and two-domain proteins with varying degrees of flexibility. We demonstrate a strong correlation between the statistical prediction scores and the explicit motion derived from extensive atomistic molecular dynamics simulations and further derive an elastic network model based on the statistical scores of AlphFold2 (AF-ENM), which we benchmark in combination with coarse-grained molecular dynamics simulations. We show that our AF-ENM method reproduces the global protein dynamics with improved accuracy, providing a powerful way to derive effective molecular dynamics using neural network-based structure prediction models.

Linear ubiquitination induces NEMO phase separation to activate NF-κB signaling

The NF-κB essential modulator NEMO is the core regulatory component of the inhibitor of κB kinase complex, which is a critical checkpoint in canonical NF-κB signaling downstream of innate and adaptive immune receptors. In response to various stimuli, such as TNF or IL-1β, NEMO binds to linear or M1-linked ubiquitin chains generated by LUBAC, promoting its oligomerization and subsequent activation of the associated kinases. Here we show that M1-ubiquitin chains induce phase separation of NEMO and the formation of NEMO assemblies in cells after exposure to IL-1β. Phase separation is promoted by both binding of NEMO to linear ubiquitin chains and covalent linkage of M1-ubiquitin to NEMO and is essential but not sufficient for its phase separation. Supporting the functional relevance of NEMO phase separation in signaling, a pathogenic NEMO mutant, which is impaired in both binding and linkage to linear ubiquitin chains, does not undergo phase separation and is defective in mediating IL-1β-induced NF-κB activation.

Structure and ensemble refinement against SAXS data: Combining MD simulations with Bayesian inference or with the maximum entropy principle

Small-angle X-ray scattering (SAXS) is a powerful method for tracking conformational transitions of proteins or soft-matter complexes in solution. However, the interpretation of the experimental data is challenged by the low spatial resolution and the low information content of the data, which lead to a high risk of overinterpreting the data. Here, we illustrate how SAXS data can be integrated into all-atom molecular dynamics (MD) simulation to derive atomic structures or heterogeneous ensembles that are compatible with the data. Besides providing atomistic insight, the MD simulation adds physicochemical information, as encoded in the MD force fields, which greatly reduces the risk of overinterpretation. We present an introduction into the theory of SAXS-driven MD simulations as implemented in GROMACS-SWAXS, a modified version of the GROMACS simulation software. We discuss SAXS-driven parallel-replica ensemble refinement with commitment to the maximum entropy principle as well as a Bayesian formulation of SAXS-driven structure refinement. Practical considerations for running and interpreting the simulations are presented. The methods are freely available via GitLab at https://gitlab.com/cbjh/gromacs-swaxs.

Multi-eGO: An in silico lens to look into protein aggregation kinetics at atomic resolution

Protein aggregation into amyloid fibrils is the archetype of aberrant biomolecular self-assembly processes, with more than 50 associated diseases that are mostly uncurable. Understanding aggregation mechanisms is thus of fundamental importance and goes in parallel with the structural characterization of the transient oligomers formed during the process. Oligomers have been proven elusive to high-resolution structural techniques, while the large sizes and long time scales, typical of aggregation processes, have limited the use of computational methods to date. To surmount these limitations, we here present multi-eGO, an atomistic, hybrid structure-based model which, leveraging the knowledge of monomers conformational dynamics and of fibril structures, efficiently captures the essential structural and kinetics aspects of protein aggregation. Multi-eGO molecular dynamics simulations can describe the aggregation kinetics of thousands of monomers. The concentration dependence of the simulated kinetics, as well as the structural features of the resulting fibrils, are in qualitative agreement with in vitro experiments carried out on an amyloidogenic peptide from Transthyretin, a protein responsible for one of the most common cardiac amyloidoses. Multi-eGO simulations allow the formation of primary nuclei in a sea of transient lower-order oligomers to be observed over time and at atomic resolution, following their growth and the subsequent secondary nucleation events, until the maturation of multiple fibrils is achieved. Multi-eGO, combined with the many experimental techniques deployed to study protein aggregation, can provide the structural basis needed to advance the design of molecules targeting amyloidogenic diseases.

Extracting time series matching a small-angle X-ray scattering profile from trajectories of molecular dynamics simulations

Solving structural ensembles of flexible biomolecules is a challenging research area. Here, we propose a method to obtain possible structural ensembles of a biomolecule based on small-angle X-ray scattering (SAXS) and molecular dynamics simulations. Our idea is to clip a time series that matches a SAXS profile from a simulation trajectory. To examine its practicability, we applied our idea to a multi-domain protein ER-60 and successfully extracted time series longer than 1 micro second from trajectories of coarse-grained molecular dynamics simulations. In the extracted time series, the domain conformation was distributed continuously and smoothly in a conformational space. Preferred domain conformations were also observed. Diversity among scattering curves calculated from each ER-60 structure was interpreted to reflect an open-close motion of the protein. Although our approach did not provide a unique solution for the structural ensemble of the biomolecule, each extracted time series can be an element of the real behavior of ER-60. Considering its low computational cost, our approach will play a key role to identify biomolecular dynamics by integrating SAXS, simulations, and other experiments.

Extended conformational states dominate the Hsp90 chaperone dynamics

The heat shock protein 90 (Hsp90) is a molecular chaperone central to client protein folding and maturation in eukaryotic cells. During its chaperone cycle, Hsp90 undergoes ATPase-coupled large-scale conformational changes between open and closed states, where the N-terminal and middle domains of the protein form a compact dimerized conformation. However, the molecular principles of the switching motion between the open and closed states remain poorly understood. Here we show by integrating atomistic and coarse-grained molecular simulations with small-angle X-ray scattering experiments and NMR spectroscopy data that Hsp90 exhibits rich conformational dynamics modulated by the charged linker, which connects the N-terminal with the middle domain of the protein. We show that the dissociation of these domains is crucial for the conformational flexibility of the open state, with the separation distance controlled by a β-sheet motif next to the linker region. Taken together, our results suggest that the conformational ensemble of Hsp90 comprises highly extended states, which could be functionally crucial for client processing.

Improving Martini 3 for Disordered and Multidomain Proteins

Coarse-grained molecular dynamics simulations are a useful tool to determine conformational ensembles of proteins. Here, we show that the coarse-grained force field Martini 3 underestimates the global dimensions of intrinsically disordered proteins (IDPs) and multidomain proteins when compared with small-angle X-ray scattering (SAXS) data and that increasing the strength of protein-water interactions favors more expanded conformations. We find that increasing the strength of interactions between protein and water by ca. 10% results in improved agreement with the SAXS data for IDPs and multidomain proteins. We also show that this correction results in a more accurate description of self-association of IDPs and folded proteins and better agreement with paramagnetic relaxation enhancement data for most IDPs. While simulations with this revised force field still show deviations to experiments for some systems, our results suggest that it is overall a substantial improvement for coarse-grained simulations of soluble proteins.

Overall structure of fully assembled cyanobacterial KaiABC circadian clock complex by an integrated experimental-computational approach

In the cyanobacterial circadian clock system, KaiA, KaiB and KaiC periodically assemble into a large complex. Here we determined the overall structure of their fully assembled complex by integrating experimental and computational approaches. Small-angle X-ray and inverse contrast matching small-angle neutron scatterings coupled with size-exclusion chromatography provided constraints to highlight the spatial arrangements of the N-terminal domains of KaiA, which were not resolved in the previous structural analyses. Computationally built 20 million structural models of the complex were screened out utilizing the constrains and then subjected to molecular dynamics simulations to examine their stabilities. The final model suggests that, despite large fluctuation of the KaiA N-terminal domains, their preferential positionings mask the hydrophobic surface of the KaiA C-terminal domains, hindering additional KaiA-KaiC interactions. Thus, our integrative approach provides a useful tool to resolve large complex structures harboring dynamically fluctuating domains.

The revealed full KaiA₁₂B₆C₆ complex is assembled including the dynamic and asynchronous KaiA N-terminal domains that have been missing in cryo-EM structures.

Conformational ensembles of intrinsically disordered proteins and flexible multidomain proteins

Intrinsically disordered proteins (IDPs) and multidomain proteins with flexible linkers show a high level of structural heterogeneity and are best described by ensembles consisting of multiple conformations with associated thermodynamic weights. Determining conformational ensembles usually involves the integration of biophysical experiments and computational models. In this review, we discuss current approaches to determine conformational ensembles of IDPs and multidomain proteins, including the choice of biophysical experiments, computational models used to sample protein conformations, models to calculate experimental observables from protein structure, and methods to refine ensembles against experimental data. We also provide examples of recent applications of integrative conformational ensemble determination to study IDPs and multidomain proteins and suggest future directions for research in the field.

Multiscale simulations of protein and membrane systems

Classical multiscale simulations are perfectly suited to investigate biological soft matter systems. Owing to the bridging between microscopically realistic and lower-resolution models or the integration of a hierarchy of subsystems, one gets access to biologically relevant system sizes and timescales. In recent years, increasingly complex systems and processes have come into focus such as multidomain proteins, phase separation processes in biopolymer solutions, multicomponent biomembranes, or multiprotein complexes up to entire viruses. The review shows factors that have contributed to this progress - from improved models to machine-learning-based analysis and scale-bridging methods.

Conformational landscape of multidomain SMAD proteins

SMAD transcription factors, the main effectors of the TGFβ (transforming growth factor β) network, have a mixed architecture of globular domains and flexible linkers. Such a complicated architecture precluded the description of their full-length (FL) structure for many years. In this study, we unravel the structures of SMAD4 and SMAD2 proteins through an integrative approach combining Small-angle X-ray scattering, Nuclear Magnetic Resonance spectroscopy, X-ray, and computational modeling. We show that both proteins populate ensembles of conformations, with the globular domains tethered by disordered and flexible linkers, which defines a new dimension of regulation. The flexibility of the linkers facilitates DNA and protein binding and modulates the protein structure. Yet, SMAD4FL is monomeric, whereas SMAD2FL is in different monomer-dimer-trimer states, driven by interactions of the MH2 domains. Dimers are present regardless of the SMAD2FL activation state and concentration. Finally, we propose that SMAD2FL dimers are key building blocks for the quaternary structures of SMAD complexes.

Reweighting of molecular simulations with explicit-solvent SAXS restraints elucidates ion-dependent RNA ensembles

Small-angle X-ray scattering (SAXS) experiments are increasingly used to probe RNA structure. A number of forward models that relate measured SAXS intensities and structural features, and that are suitable to model either explicit-solvent effects or solute dynamics, have been proposed in the past years. Here, we introduce an approach that integrates atomistic molecular dynamics simulations and SAXS experiments to reconstruct RNA structural ensembles while simultaneously accounting for both RNA conformational dynamics and explicit-solvent effects. Our protocol exploits SAXS pure-solute forward models and enhanced sampling methods to sample an heterogenous ensemble of structures, with no information towards the experiments provided on-the-fly. The generated structural ensemble is then reweighted through the maximum entropy principle so as to match reference SAXS experimental data at multiple ionic conditions. Importantly, accurate explicit-solvent forward models are used at this reweighting stage. We apply this framework to the GTPase-associated center, a relevant RNA molecule involved in protein translation, in order to elucidate its ion-dependent conformational ensembles. We show that (a) both solvent and dynamics are crucial to reproduce experimental SAXS data and (b) the resulting dynamical ensembles contain an ion-dependent fraction of extended structures.

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.

Structural and Biochemical Basis for Higher-Order Assembly between A20-Binding Inhibitor of NF-κB 1 (ABIN1) and M1-Linked Ubiquitins

Polyubiquitination is important in controlling NF-κB signaling. Excessive NF-κB activity has been linked to inflammatory disorders and autoimmune diseases, while ABIN1 could attenuate NF-κB activation to maintain immune homeostasis by utilizing UBAN to recognize linear (M1)-linked polyubiquitinated NF-κB activation mediators, including NEMO, IRAK1 and RIP1. PolyUb-mediated UBAN recruitment remains undetermined, since the recognition studies focused mostly on di-ubiquitin (diUb). Here we report three crystal structures of human ABIN1 UBAN (hABIN1^UBAN) in complex with M1-linked diUb, triUb, and tetraUb, respectively. Notably, the hABIN1^UBAN:diUb structure reveals that a diUb randomly binds one of the Ub-binding sites of the hABIN1^UBAN dimer and leaves the other site vacant. Together with the ITC and gel-filtration analyses, we found that M1-triUb and M1-tetraUb adopt two unique conformations, instead of an elongated one, and they preferentially use the N-terminal two-Ub unit to bind the primary Ub-binding site of a hABIN1^UBAN dimer and the C-terminal two-Ub unit to bind the secondary Ub-binding site of another hABIN1^UBAN dimer. Especially, our results suggest that two ABIN1^UBAN dimers cooperatively bind two UBAN-binding units of a tetraUb or vice versa. Since the UBAN family members share a conserved diUb-binding mode, our results suggest that M1-polyUb modification allows multiple copies of the two-tandem Ub unit to simultaneously coordinate multiple and/or different binding partners to increase their local concentrations and to facilitate the formation of a large signaling complex. Our study provides a structural-functional glimpse of M1-polyUb as a multiple-molecule binding platform to exert its intrinsic structural plasticity in mediating cellular signaling.

How to Determine Accurate Conformational Ensembles by Metadynamics Metainference: A Chignolin Study Case

The reliability and usefulness of molecular dynamics simulations of equilibrium processes rests on their statistical precision and their capability to generate conformational ensembles in agreement with available experimental knowledge. Metadynamics Metainference (M&M), coupling molecular dynamics with the enhanced sampling ability of Metadynamics and with the ability to integrate experimental information of Metainference, can in principle achieve both goals. Here we show that three different Metadynamics setups provide converged estimate of the populations of the three-states populated by a model peptide. Errors are estimated correctly by block averaging, but higher precision is obtained by performing independent replicates. One effect of Metadynamics is that of dramatically decreasing the number of effective frames resulting from the simulations and this is relevant for M&M where the number of replicas should be large enough to capture the conformational heterogeneity behind the experimental data. Our simulations allow also us to propose that monitoring the relative error associated with conformational averaging can help to determine the minimum number of replicas to be simulated in the context of M&M simulations. Altogether our data provides useful indication on how to generate sound conformational ensemble in agreement with experimental data.

Refinement of α-Synuclein Ensembles Against SAXS Data: Comparison of Force Fields and Methods

The inherent flexibility of intrinsically disordered proteins (IDPs) makes it difficult to interpret experimental data using structural models. On the other hand, molecular dynamics simulations of IDPs often suffer from force-field inaccuracies, and long simulation times or enhanced sampling methods are needed to obtain converged ensembles. Here, we apply metainference and Bayesian/Maximum Entropy reweighting approaches to integrate prior knowledge of the system with experimental data, while also dealing with various sources of errors and the inherent conformational heterogeneity of IDPs. We have measured new SAXS data on the protein α-synuclein, and integrate this with simulations performed using different force fields. We find that if the force field gives rise to ensembles that are much more compact than what is implied by the SAXS data it is difficult to recover a reasonable ensemble. On the other hand, we show that when the simulated ensemble is reasonable, we can obtain an ensemble that is consistent with the SAXS data, but also with NMR diffusion and paramagnetic relaxation enhancement data.