CryoEM Structure Refinement by Integrating NMR Chemical Shifts with Molecular Dynamics Simulations

In-cell Structure and Variability of Pyrenoid Rubisco

Ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) is a key enzyme in the global carbon cycle, catalyzing CO2 fixation during photosynthesis. To overcome Rubisco's inherent catalytic inefficiency, many photosynthetic organisms have evolved CO2-concentrating mechanisms. Central to these mechanisms is the pyrenoid, a protein-dense organelle within the chloroplast of eukaryotic algae, which increases the local concentration of CO2 around Rubisco and thereby enhances its catalytic efficiency. Although the structure of Rubisco has been extensively studied by in vitro methods such as X-ray crystallography and single particle cryo-EM, its native structure within the pyrenoid, its dynamics, and its association with binding partners remain elusive. Here, we investigate the structure of native pyrenoid Rubisco inside the green alga Chlamydomonas reinhardtii by applying cryo-electron tomography (cryo-ET) on cryo-focused ion beam (cryo-FIB) milled cells, followed by subtomogram averaging and 3D classification. Reconstruction at sub-nanometer resolution allowed accurate modeling and determination of a closed (activated) Rubisco conformation. Comparison to other reconstructed subsets revealed local variations at the complex active site and at the large subunit dimers interface, as well as association with binding proteins. The different structural subsets distribute stochastically within the pyrenoid. Taken together, these findings offer a comprehensive description of the structure, dynamics, and functional organization of Rubisco within the pyrenoid, providing valuable insights into its critical role in CO2 fixation.

Integrating 19F Distance Restraints for Accurate Protein Structure Determination by Magic Angle Spinning NMR Spectroscopy

Traditional protein structure determination by magic angle spinning (MAS) solid-state NMR spectroscopy primarily relies on interatomic distances up to 8 Å, extracted from 13C-, 15N-, and 1H-based dipolar-based correlation experiments. Here, we show that 19F fast (60 kHz) MAS NMR spectroscopy can supply additional, longer distances. Using 4F-Trp,U-13C,15N crystalline Oscillatoria agardhii agglutinin (OAA), we demonstrate that judiciously designed 2D and 3D 19F-based dipolar correlation experiments such as (H)CF, (H)CHF, and FF can yield interatomic distances in the 8-16 Å range. Incorporation of fluorine-based restraints into structure calculation improved the precision of Trp side chain conformations as well as regions in the protein around the fluorine containing residues, with notable improvements observed for residues in proximity to the Trp pairs (W10/W17 and W77/W84) in the carbohydrate-binding loops, which lacked sufficient long-range 13C-13C distance restraints. Our work highlights the use of fluorine and 19F fast MAS NMR spectroscopy as a powerful structural biology tool.

Structural Basis for Alternative Self-Assembly Pathways Leading to Different Human Immunodeficiency Virus Capsid-Like Nanoparticles

The mechanisms that underlie the spontaneous and faithful assembly of virus particles are guiding the design of self-assembling protein-based nanostructures for biomedical or nanotechnological uses. In this study, the human immunodeficiency virus (HIV-1) capsid was used as a model to investigate what molecular feature(s) may determine whether a protein nanoparticle with the intended architecture, instead of an aberrant particle, will be self-assembled in vitro. Attempts of using the HIV-1 capsid protein CA for achieving in vitro the self-assembly of cone-shaped nanoparticles that contain CA hexamers and pentamers, similar to authentic viral capsids, had typically yielded hexamer-only tubular particles. We hypothesized that a reduction in the stability of a transient major assembly intermediate, a trimer of CA dimers (ToD), will increase the propensity of CA to assemble in vitro into cone-shaped particles instead of tubes. Certain amino acid substitutions at CA-CA interfaces strongly favored in vitro the assembly of cone-shaped nanoparticles that resembled authentic HIV-1 capsids. All-atom MD simulations indicated that ToDs formed by CA mutants with increased propensity for assembly into cone-shaped particles are destabilized relative to ToDs formed by wt CA or by another mutant that assembles into tubes. The results also indicated that ToD destabilization is mediated by conformational distortion of different CA-CA interfaces, which removes some interprotein interactions within the ToD. A model is proposed to rationalize the linkage between reduced ToD stability and increased propensity for the formation of CA pentamers during particle growth in vitro, favoring the assembly of cone-shaped HIV-1 capsid-like nanoparticles.

Cryo-EM and solid state NMR together provide a more comprehensive structural investigation of protein fibrils

The tropomyosin 1 isoform I/C C-terminal domain (Tm1-LC) fibril structure is studied jointly with cryogenic electron microscopy (cryo-EM) and solid state nuclear magnetic resonance (NMR). This study demonstrates the complementary nature of these two structural biology techniques. Chemical shift assignments from solid state NMR are used to determine the secondary structure at the level of individual amino acids, which is faithfully seen in cryo-EM reconstructions. Additionally, solid state NMR demonstrates that the region not observed in the reconstructed cryo-EM density is primarily in a highly mobile random coil conformation rather than adopting multiple rigid conformations. Overall, this study illustrates the benefit of investigations combining cryo-EM and solid state NMR to investigate protein fibril structure.

Biomolecular NMR spectroscopy in the era of artificial intelligence

Biomolecular nuclear magnetic resonance (NMR) spectroscopy and artificial intelligence (AI) have a burgeoning synergy. Deep learning-based structural predictors have forever changed structural biology, yet these tools currently face limitations in accurately characterizing protein dynamics, allostery, and conformational heterogeneity. We begin by highlighting the unique abilities of biomolecular NMR spectroscopy to complement AI-based structural predictions toward addressing these knowledge gaps. We then highlight the direct integration of deep learning approaches into biomolecular NMR methods. AI-based tools can dramatically improve the acquisition and analysis of NMR spectra, enhancing the accuracy and reliability of NMR measurements, thus streamlining experimental processes. Additionally, deep learning enables the development of novel types of NMR experiments that were previously unattainable, expanding the scope and potential of biomolecular NMR spectroscopy. Ultimately, a combination of AI and NMR promises to further revolutionize structural biology on several levels, advance our understanding of complex biomolecular systems, and accelerate drug discovery efforts.

Understanding Virus Structure and Dynamics through Molecular Simulations

Viral outbreaks remain a serious threat to human and animal populations and motivate the continued development of antiviral drugs and vaccines, which in turn benefits from a detailed understanding of both viral structure and dynamics. While great strides have been made in characterizing these systems experimentally, molecular simulations have proven to be an essential, complementary approach. In this work, we review the contributions of molecular simulations to the understanding of viral structure, functional dynamics, and processes related to the viral life cycle. Approaches ranging from coarse-grained to all-atom representations are discussed, including current efforts at modeling complete viral systems. Overall, this review demonstrates that computational virology plays an essential role in understanding these systems.

gmxapi: A GROMACS-native Python interface for molecular dynamics with ensemble and plugin support

Gmxapi provides an integrated, native Python API for both standard and advanced molecular dynamics simulations in GROMACS. The Python interface permits multiple levels of integration with the core GROMACS libraries, and legacy support is provided via an interface that mimics the command-line syntax, so that all GROMACS commands are fully available. Gmxapi has been officially supported since the GROMACS 2019 release and is enabled by default in current versions of the software. Here we describe gmxapi 0.3 and later. Beyond simply wrapping GROMACS library operations, the API permits several advanced operations that are not feasible using the prior command-line interface. First, the API allows custom user plugin code within the molecular dynamics force calculations, so users can execute custom algorithms without modifying the GROMACS source. Second, the Python interface allows tasks to be dynamically defined, so high-level algorithms for molecular dynamics simulation and analysis can be coordinated with loop and conditional operations. Gmxapi makes GROMACS more accessible to custom Python scripting while also providing support for high-level data-flow simulation algorithms that were previously feasible only in external packages.

Imaging active site chemistry and protonation states: NMR crystallography of the tryptophan synthase α-aminoacrylate intermediate

NMR-assisted crystallography-the integrated application of solid-state NMR, X-ray crystallography, and first-principles computational chemistry-holds significant promise for mechanistic enzymology: by providing atomic-resolution characterization of stable intermediates in enzyme active sites, including hydrogen atom locations and tautomeric equilibria, NMR crystallography offers insight into both structure and chemical dynamics. Here, this integrated approach is used to characterize the tryptophan synthase α-aminoacrylate intermediate, a defining species for pyridoxal-5'-phosphate-dependent enzymes that catalyze β-elimination and replacement reactions. For this intermediate, NMR-assisted crystallography is able to identify the protonation states of the ionizable sites on the cofactor, substrate, and catalytic side chains as well as the location and orientation of crystallographic waters within the active site. Most notable is the water molecule immediately adjacent to the substrate β-carbon, which serves as a hydrogen bond donor to the ε-amino group of the acid-base catalytic residue βLys87. From this analysis, a detailed three-dimensional picture of structure and reactivity emerges, highlighting the fate of the L-serine hydroxyl leaving group and the reaction pathway back to the preceding transition state. Reaction of the α-aminoacrylate intermediate with benzimidazole, an isostere of the natural substrate indole, shows benzimidazole bound in the active site and poised for, but unable to initiate, the subsequent bond formation step. When modeled into the benzimidazole position, indole is positioned with C3 in contact with the α-aminoacrylate Cβ and aligned for nucleophilic attack. Here, the chemically detailed, three-dimensional structure from NMR-assisted crystallography is key to understanding why benzimidazole does not react, while indole does.

Anomalous amide proton chemical shifts as signatures of hydrogen bonding to aromatic sidechains

Hydrogen bonding between an amide group and the p-π cloud of an aromatic ring was first identified in a protein in the 1980s. Subsequent surveys of high-resolution X-ray crystal structures found multiple instances, but their preponderance was determined to be infrequent. Hydrogen atoms participating in a hydrogen bond to the p-π cloud of an aromatic ring are expected to experience an upfield chemical shift arising from a shielding ring current shift. We surveyed the Biological Magnetic Resonance Data Bank for amide hydrogens exhibiting unusual shifts as well as corroborating nuclear Overhauser effects between the amide protons and ring protons. We found evidence that Trp residues are more likely to be involved in p-π hydrogen bonds than other aromatic amino acids, whereas His residues are more likely to be involved in in-plane hydrogen bonds, with a ring nitrogen acting as the hydrogen acceptor. The p-π hydrogen bonds may be more abundant than previously believed. The inclusion in NMR structure refinement protocols of shift effects in amide protons from aromatic sidechains, or explicit hydrogen bond restraints between amides and aromatic rings, could improve the local accuracy of sidechain orientations in solution NMR protein structures, but their impact on global accuracy is likely be limited.

Changes in dynamic and static structures of the HIV-1 p24 capsid protein N-domain caused by amino-acid substitution are associated with its viral viability

HIV-1 capsid is comprised of over a hundred p24 protein molecules, arranged as either pentamers or hexamers. Three p24 mutants with amino acid substitutions in capsid N-terminal domain protein were examined: G60W (α3-4 loop), M68T (helix 4), and P90T (α4-5 loop), which exhibited no viability for biological activity. One common structural feature of the three p24 N-domain mutants, examined by NMR, was the long-range effect of more β-structures at the β2-strand in the N-terminal region compared with the wild-type. In addition, the presence of fewer helical structures was observed in M68T and P90T, beyond the broad area from helix 1 to the C-terminal part of helix 4. This suggests that both N-terminal beta structures and helices play important roles in the formation of p24 hexamers and pentamers. Next, compared with P90T, we examined cis-conformation or trans-conformation of wild-type adopted by isomerization at G89-P90. Since P90T mutant adopts only a trans-conformation, comparison of chemical shifts and signal intensities between each spectra revealed that the major peaks (about 85%) in the spectrum of wild-type correspond to trans-conformation. Furthermore, it was indicated that the region in cis-conformation (minor; 15%) was more stabilized than that observed in trans-conformation, based on the analyses of heteronuclear Overhauser effect as well as the order-parameter. Therefore, it was concluded that the cis-conformation is more favorable than the trans-conformation for the interaction between the p24 N-terminal domain and cyclophilin-A. This is because HIV-1 with a P90T protein, which adopts only a trans-conformation, is associated with non-viability of biological activity.

Fighting viruses with computers, right now

The synergistic conjunction of various technological revolutions with the accumulated knowledge and workflows is rapidly transforming several scientific fields. Particularly, Virology can now feed from accurate physical models, polished computational tools, and massive computational power to readily integrate high-resolution structures into biological representations of unprecedented detail. That preparedness allows for the first time to get crucial information for vaccine and drug design from in-silico experiments against emerging pathogens of worldwide concern at relevant action windows. The present work reviews some of the main milestones leading to these breakthroughs in Computational Virology, providing an outlook for future developments in capacity building and accessibility to computational resources.

Fitting Low-Resolution Protein Structures into Cryo-EM Density Maps by Multiobjective Optimization of Global and Local Correlations

The rigid-body fitting of predicted structural models into cryo-electron microscopy (cryo-EM) density maps is a necessary procedure for density map-guided protein structure determination and prediction. We proposed a novel multiobjective optimization protocol, MOFIT, which performs a rigid-body density-map fitting based on particle swarm optimization (PSO). MOFIT was tested on a large set of 292 nonhomologous single-domain proteins. Starting from structural models predicted by I-TASSER, MOFIT achieved an average coordinate root-mean-square deviation of 2.46 Å, which was 1.57, 2.79, and 3.95 Å lower than three leading single-objective function-based methods, where the differences were statistically significant with p-values of 1.65 × 10^-6, 6.36 × 10^-8, and 6.44 × 10^-11 calculated using two-tail Student's t tests. Detailed analyses showed that the major advantages of MOFIT lie in the multiobjective protocol and the extensive PSO search simulations guided by the composite objective functions, which integrates complementary correlation coefficients from the global structure, local fragments, and individual residues with the cryo-EM density maps.

Permeability of the HIV-1 capsid to metabolites modulates viral DNA synthesis

Reverse transcription, an essential event in the HIV-1 life cycle, requires deoxynucleotide triphosphates (dNTPs) to fuel DNA synthesis, thus requiring penetration of dNTPs into the viral capsid. The central cavity of the capsid protein (CA) hexamer reveals itself as a plausible channel that allows the passage of dNTPs into assembled capsids. Nevertheless, the molecular mechanism of nucleotide import into the capsid remains unknown. Employing all-atom molecular dynamics (MD) simulations, we established that cooperative binding between nucleotides inside a CA hexamer cavity results in energetically favorable conditions for passive translocation of dNTPs into the HIV-1 capsid. Furthermore, binding of the host cell metabolite inositol hexakisphosphate (IP₆) enhances dNTP import, while binding of synthesized molecules like benzenehexacarboxylic acid (BHC) inhibits it. The enhancing effect on reverse transcription by IP₆ and the consequences of interactions between CA and nucleotides were corroborated using atomic force microscopy, transmission electron microscopy, and virological assays. Collectively, our results provide an atomistic description of the permeability of the HIV-1 capsid to small molecules and reveal a novel mechanism for the involvement of metabolites in HIV-1 capsid stabilization, nucleotide import, and reverse transcription.

This study shows that the HIV-1 capsid protein, in addition to its structural role, regulates reverse transcription, an essential metabolic process of the virus, by mediating the import of nucleotides. In addition, host cell metabolites such as inositol phosphates are recruited by the capsid to regulate viral DNA synthesis.

Atomic-resolution structure of HIV-1 capsid tubes by magic-angle spinning NMR

HIV-1 capsid plays multiple key roles in viral replication, and inhibition of capsid assembly is an attractive target for therapeutic intervention. Here, we report the atomic-resolution structure of the capsid protein (CA) tubes, determined by magic-angle-spinning NMR and data-guided molecular dynamics simulations. Functionally important regions, including the NTD β-hairpin, the cyclophilin A loop, residues in the hexamer center pore, and the NTD-CTD linker region, are well defined. The structure of individual CA chains, their arrangement in the pseudo-hexameric units of the tube and the inter-hexamer interfaces are consistent with those in intact capsid cores and substantially different from the organization in crystal structures, which featured flat hexamers. The inherent curvature in the CA tubes is controlled by conformational variability of residues in the linker region and of dimer and trimer interfaces. The present structure reveals atomic-level detail into capsid architecture and provides important guidance for the design of novel capsid inhibitors.

Using NMR Chemical Shifts and Cryo-EM Density Restraints in Iterative Rosetta-MD Protein Structure Refinement

Cryo-EM has become one of the prime methods for protein structure elucidation, frequently yielding density maps with near-atomic or medium resolution. If protein structures cannot be deduced unambiguously from the density maps, computational structure refinement tools are needed to generate protein structural models. We have previously developed an iterative Rosetta-MDFF protocol that used cryo-EM densities to refine protein structures. Here we show that, in addition to cryo-EM densities, incorporation of other experimental restraints into the Rosetta-MDFF protocol further improved refined structures. We used NMR chemical shift (CS) data integrated with cryo-EM densities in our hybrid protocol in both the Rosetta step and the molecular dynamics (MD) simulations step. In 15 out of 18 cases for all MD rounds, the refinement results obtained when density maps and NMR chemical shift data were used in combination outperformed those of density map-only refinement. Notably, the improvement in refinement was highest when medium and low-resolution density maps were used. With our hybrid method, the RMSDs of final models obtained were always better than the RMSDs obtained by our previous protocol with just density refinement for both medium (6.9 Å) and low (9 Å) resolution maps. For all the six test proteins with medium resolution density maps (6.9 Å), the final refined structure RMSDs were lower for the hybrid method than for the cryo-EM only refinement. The final refined RMSDs were less than 1.5 Å when our hybrid protocol was used with 4 Å density maps. For four out of the six proteins the final RMSDs were even less than 1 Å. This study demonstrates that by using a combination of cryo-EM and NMR restraints, it is possible to refine structures to atomic resolution, outperforming single restraint refinement. This hybrid protocol will be a valuable tool when only low-resolution cryo-EM density data and NMR chemical shift data are available to refine structures.

Enhanced sampling and free energy calculations for protein simulations

Molecular dynamics simulation is a powerful computational technique to study biomolecular systems, which complements experiments by providing insights into the structural dynamics relevant to biological functions at atomic scale. It can also be used to calculate the free energy landscapes of the conformational transitions to better understand the functions of the biomolecules. However, the sampling of biomolecular configurations is limited by the free energy barriers that need to be overcome, leading to considerable gaps between the timescales reached by MD simulation and those governing biological processes. To address this issue, many enhanced sampling methodologies have been developed to increase the sampling efficiency of molecular dynamics simulations and free energy calculations. Usually, enhanced sampling algorithms can be classified into methods based on collective variables (CV-based) and approaches which do not require predefined CVs (CV-free). In this chapter, the theoretical basis of free energy estimation is briefly reviewed first, followed by the reviews of the most common CV-based and CV-free methods including the presentation of some examples and recent developments. Finally, the combination of different enhanced sampling methods is discussed.

Integrating cryo-EM and NMR data

Single-particle cryo-electron microscopy (cryo-EM) is increasingly used as a technique to determine the atomic structure of challenging biological systems. Recent advances in microscope engineering, electron detection, and image processing have allowed the structural determination of bigger and more flexible targets than possible with the complementary techniques X-ray crystallography and NMR spectroscopy. However, there exist many biological targets for which atomic resolution cannot be currently achieved with cryo-EM, making unambiguous determination of the protein structure impossible. Although determining the structure of large biological systems using solely NMR is often difficult, highly complementary experimental atomic-level data for each molecule can be derived from the spectra, and used in combination with cryo-EM data. We review here strategies with which both techniques can be synergistically combined, in order to reach detail and understanding unattainable by each technique acting alone; and the types of biological systems for which such an approach would be desirable.

High-Performance Analysis of Biomolecular Containers to Measure Small-Molecule Transport, Transbilayer Lipid Diffusion, and Protein Cavities

Compartmentalization is a central theme in biology. Cells are composed of numerous membrane-enclosed structures, evolved to facilitate specific biochemical processes; viruses act as containers of genetic material, optimized to drive infection. Molecular dynamics simulations provide a mechanism to study biomolecular containers and the influence they exert on their environments; however, trajectory analysis software generally lacks knowledge of container interior versus exterior. Further, many relevant container analyses involve large-scale particle tracking endeavors, which may become computationally prohibitive with increasing system size. Here, a novel method based on 3-D ray casting is presented, which rapidly classifies the space surrounding biomolecular containers of arbitrary shape, enabling fast determination of the identities and counts of particles (e.g., solvent molecules) found inside and outside. The method is broadly applicable to the study of containers and enables high-performance characterization of properties such as solvent density, small-molecule transport, transbilayer lipid diffusion, and topology of protein cavities. The method is implemented in VMD, a widely used simulation analysis tool that supports personal computers, clouds, and parallel supercomputers, including ORNL's Summit and Titan and NCSA's Blue Waters, where the method can be employed to efficiently analyze trajectories encompassing millions of particles. The ability to rapidly characterize the spatial relationships of particles relative to a biomolecular container over many trajectory frames, irrespective of large particle counts, enables analysis of containers on a scale that was previously unfeasible, at a level of accuracy that was previously unattainable.

Emerging solution NMR methods to illuminate the structural and dynamic properties of proteins

The first recognition of protein breathing was more than 50 years ago. Today, we are able to detect the multitude of interaction modes, structural polymorphisms, and binding-induced changes in protein structure that direct function. Solution-state NMR spectroscopy has proved to be a powerful technique, not only to obtain high-resolution structures of proteins, but also to provide unique insights into the functional dynamics of proteins. Here, we summarize recent technical landmarks in solution NMR that have enabled characterization of key biological macromolecular systems. These methods have been fundamental to atomic resolution structure determination and quantitative analysis of dynamics over a wide range of time scales by NMR. The ability of NMR to detect lowly populated protein conformations and transiently formed complexes plays a critical role in its ability to elucidate functionally important structural features of proteins and their dynamics.

Integrated BioNMR - "getting by with a little help from my friends"

Single types of methodologies are insufficient to adequately describe complex biological structures. As a result, integrated approaches that combine complementary data are being developed. Here, I describe the benefits of integrating solution and magic angle spinning BioNMR approaches to characterize structure and dynamics of protein assemblies.

Integrative Approaches in Structural Biology: A More Complete Picture from the Combination of Individual Techniques

With the recent technological and computational advancements, structural biology has begun to tackle more and more difficult questions, including complex biochemical pathways and transient interactions among macromolecules. This has demonstrated that, to approach the complexity of biology, one single technique is largely insufficient and unable to yield thorough answers, whereas integrated approaches have been more and more adopted with successful results. Traditional structural techniques (X-ray crystallography and Nuclear Magnetic Resonance (NMR)) and the emerging ones (cryo-electron microscopy (cryo-EM), Small Angle X-ray Scattering (SAXS)), together with molecular modeling, have pros and cons which very nicely complement one another. In this review, three examples of synergistic approaches chosen from our previous research will be revisited. The first shows how the joint use of both solution and solid-state NMR (SSNMR), X-ray crystallography, and cryo-EM is crucial to elucidate the structure of polyethylene glycol (PEG)ylated asparaginase, which would not be obtainable through any of the techniques taken alone. The second deals with the integrated use of NMR, X-ray crystallography, and SAXS in order to elucidate the catalytic mechanism of an enzyme that is based on the flexibility of the enzyme itself. The third one shows how it is possible to put together experimental data from X-ray crystallography and NMR restraints in order to refine a protein model in order to obtain a structure which simultaneously satisfies both experimental datasets and is therefore closer to the ‘real structure’.

The Retrovirus Capsid Core

The retrovirus capsid core is a metastable structure that disassembles during the early phase of viral infection after membrane fusion. The core is intact and permeable to essential nucleotides during reverse transcription, but it undergoes disassembly for nuclear entry and genome integration. Increasing or decreasing the stability of the capsid core has a substantial negative impact on virus infectivity, which makes the core an attractive anti-viral target. The retrovirus capsid core also encounters a variety of virus- and organism-specific host cellular factors that promote or restrict viral replication. This review describes the structural elements fundamental to the formation and stability of the capsid core. The physical and chemical properties of the capsid core that are critical to its functional role in reverse transcription and interaction with host cellular factors are highlighted to emphasize areas of current research.

All-atom virus simulations

The constant threat of viral disease can be combated by the development of novel vaccines and therapeutics designed to disrupt key features of virus structure or infection cycle processes. Such development relies on high-resolution characterization of viruses and their dynamical behaviors, which are often challenging to obtain solely by experiment. In response, all-atom molecular dynamics simulations are widely leveraged to study the structural components of viruses, leading to some of the largest simulation endeavors undertaken to date. The present work reviews exemplary all-atom simulation work on viruses, as well as progress toward simulating entire virions.

CryoEM-based hybrid modeling approaches for structure determination

Recent advances in cryo-electron microscopy (cryoEM) have dramatically improved the resolutions at which vitrified biological specimens can be studied, revealing new structural and mechanistic insights over a broad range of spatial scales. Bolstered by these advances, much effort has been directed toward the development of hybrid modeling methodologies for the construction and refinement of high-fidelity atomistic models from cryoEM data. In this brief review, we will survey the key elements of cryoEM-based hybrid modeling, providing an overview of available computational tools and strategies as well as several recent applications.

Chemical shift-based methods in NMR structure determination

Chemical shifts are highly sensitive probes harnessed by NMR spectroscopists and structural biologists as conformational parameters to characterize a range of biological molecules. Traditionally, assignment of chemical shifts has been a labor-intensive process requiring numerous samples and a suite of multidimensional experiments. Over the past two decades, the development of complementary computational approaches has bolstered the analysis, interpretation and utilization of chemical shifts for elucidation of high resolution protein and nucleic acid structures. Here, we review the development and application of chemical shift-based methods for structure determination with a focus on ab initio fragment assembly, comparative modeling, oligomeric systems, and automated assignment methods. Throughout our discussion, we point out practical uses, as well as advantages and caveats, of using chemical shifts in structure modeling. We additionally highlight (i) hybrid methods that employ chemical shifts with other types of NMR restraints (residual dipolar couplings, paramagnetic relaxation enhancements and pseudocontact shifts) that allow for improved accuracy and resolution of generated 3D structures, (ii) the utilization of chemical shifts to model the structures of sparsely populated excited states, and (iii) modeling of sidechain conformations. Finally, we briefly discuss the advantages of contemporary methods that employ sparse NMR data recorded using site-specific isotope labeling schemes for chemical shift-driven structure determination of larger molecules. With this review, we aim to emphasize the accessibility and versatility of chemical shifts for structure determination of challenging biological systems, and to point out emerging areas of development that lead us towards the next generation of tools.

New applications of solid-state NMR in structural biology

Various recent developments in solid-state nuclear magnetic resonance (ssNMR) spectroscopy have enabled an array of new insights regarding the structure, dynamics, and interactions of biomolecules. In the ever more integrated world of structural biology, ssNMR studies provide structural and dynamic information that is complementary to the data accessible by other means. ssNMR enables the study of samples lacking a crystalline lattice, featuring static as well as dynamic disorder, and does so independent of higher-order symmetry. The present study surveys recent applications of biomolecular ssNMR and examines how this technique is increasingly integrated with other structural biology techniques, such as (cryo) electron microscopy, solution-state NMR, and X-ray crystallography. Traditional ssNMR targets include lipid bilayer membranes and membrane proteins in a lipid bilayer environment. Another classic application has been in the area of protein misfolding and aggregation disorders, where ssNMR has provided essential structural data on oligomers and amyloid fibril aggregates. More recently, the application of ssNMR has expanded to a growing array of biological assemblies, ranging from non-amyloid protein aggregates, protein–protein complexes, viral capsids, and many others. Across these areas, multidimensional magic angle spinning (MAS) ssNMR has, in the last decade, revealed three-dimensional structures, including many that had been inaccessible by other structural biology techniques. Equally important insights in structural and molecular biology derive from the ability of MAS ssNMR to probe information beyond comprehensive protein structures, such as dynamics, solvent exposure, protein–protein interfaces, and substrate–enzyme interactions.

Combined 1H-Detected Solid-State NMR Spectroscopy and Electron Cryotomography to Study Membrane Proteins across Resolutions in Native Environments

Membrane proteins remain challenging targets for structural biology, despite much effort, as their native environment is heterogeneous and complex. Most methods rely on detergents to extract membrane proteins from their native environment, but this removal can significantly alter the structure and function of these proteins. Here, we overcome these challenges with a hybrid method to study membrane proteins in their native membranes, combining high-resolution solid-state nuclear magnetic resonance spectroscopy and electron cryotomography using the same sample. Our method allows the structure and function of membrane proteins to be studied in their native environments, across different spatial and temporal resolutions, and the combination is more powerful than each technique individually. We use the method to demonstrate that the bacterial membrane protein YidC adopts a different conformation in native membranes and that substrate binding to YidC in these native membranes differs from purified and reconstituted systems.

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CryoET and ssNMR give complementary information about proteins in native membranes

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One sample can be prepared for both methods without the use of detergents

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Hybrid method shows differences between purified and native preparations of YidC

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Sample preparation reduces costs and time and suggests new strategy for assignment

Expanding the horizons for structural analysis of fully protonated protein assemblies by NMR spectroscopy at MAS frequencies above 100 kHz

The recent breakthroughs in NMR probe technologies resulted in the development of MAS NMR probes with rotation frequencies exceeding 100 kHz. Herein, we explore dramatic increases in sensitivity and resolution observed at MAS frequencies of 110-111 kHz in a novel 0.7 mm HCND probe that enable structural analysis of fully protonated biological systems. Proton- detected 2D and 3D correlation spectroscopy under such conditions requires only 0.1-0.5 mg of sample and a fraction of time compared to conventional ¹³C-detected experiments. We discuss the performance of several proton- and heteronuclear- (¹³C-,¹⁵N-) based correlation experiments in terms of sensitivity and resolution, using a model microcrystalline fMLF tripeptide. We demonstrate the applications of ultrafast MAS to a large, fully protonated protein assembly of the 231-residue HIV-1 CA capsid protein. Resonance assignments of protons and heteronuclei, as well as ¹H-¹⁵N dipolar and ¹H^N CSA tensors are readily obtained from the high sensitivity and resolution proton-detected 3D experiments. The approach demonstrated here is expected to enable the determination of atomic-resolution structures of large protein assemblies, inaccessible by current methodologies.

Iterative Molecular Dynamics-Rosetta Membrane Protein Structure Refinement Guided by Cryo-EM Densities

Knowing atomistic details of proteins is essential not only for the understanding of protein function but also for the development of drugs. Experimental methods such as X-ray crystallography, NMR, and cryo-electron microscopy (cryo-EM) are the preferred forms of protein structure determination and have achieved great success over the most recent decades. Computational methods may be an alternative when experimental techniques fail. However, computational methods are severely limited when it comes to predicting larger macromolecule structures with little sequence similarity to known structures. The incorporation of experimental restraints in computational methods is becoming increasingly important to more reliably predict protein structure. One such experimental input used in structure prediction and refinement is cryo-EM densities. Recent advances in cryo-EM have arguably revolutionized the field of structural biology. Our previously developed cryo-EM-guided Rosetta-MD protocol has shown great promise in the refinement of soluble protein structures. In this study, we extended cryo-EM density-guided iterative Rosetta-MD to membrane proteins. We also improved the methodology in general by picking models based on a combination of their score and fit-to-density during the Rosetta model selection. By doing so, we have been able to pick models superior to those with the previous selection based on Rosetta score only and we have been able to further improve our previously refined models of soluble proteins. The method was tested with five membrane spanning protein structures. By applying density-guided Rosetta-MD iteratively we were able to refine the predicted structures of these membrane proteins to atomic resolutions. We also showed that the resolution of the density maps determines the improvement and quality of the refined models. By incorporating high-resolution density maps (∼4 Å), we were able to more significantly improve the quality of the models than when medium-resolution maps (6.9 Å) were used. Beginning from an average starting structure root mean square deviation (RMSD) to native of 4.66 Å, our protocol was able to refine the structures to bring the average refined structure RMSD to 1.66 Å when 4 Å density maps were used. The protocol also successfully refined the HIV-1 CTD guided by an experimental 5 Å density map.

Characterization of conformational deformation-coupled interaction between immunoglobulin G1 Fc glycoprotein and a low-affinity Fcγ receptor by deuteration-assisted small-angle neutron scattering

A recently developed integrative approach combining varied types of experimental data has been successfully applied to three-dimensional modelling of larger biomacromolecular complexes. Deuteration-assisted small-angle neutron scattering (SANS) plays a unique role in this approach by making it possible to observe selected components in the complex. It enables integrative modelling of biomolecular complexes based on building-block structures typically provided by X-ray crystallography. In this integrative approach, it is important to be aware of the flexible properties of the individual building blocks. Here we examine the ability of SANS to detect a subtle conformational change of a multidomain protein using the Fc portion of human immunoglobulin G (IgG) interacting with a soluble form of the low-affinity Fcγ receptor IIIb (sFcγRIIIb) as a model system. The IgG-Fc glycoprotein was subjected to SANS in the absence and presence of 75%-deuterated sFcγRIIIb, which was matched out in D₂O solution. This inverse contrast-matching technique enabled selective observation of SANS from IgG-Fc, thereby detecting its subtle structural deformation induced by the receptor binding. The SANS data were successfully interpreted by considering previously reported crystallographic data and an equilibrium between free and sFcγRIIIb-bound forms. Our SANS data thus demonstrate the applicability of SANS in the integrative approach dealing with biomacromolecular complexes composed of weakly associated building blocks with conformational plasticity.

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IgG-Fc glycoprotein was structurally characterized by small-angle neutron scattering.

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Fc was selectively observed under equilibrium between free and receptor-bound forms.

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Receptor-induced conformational change of Fc was successfully detected.

Physical properties of the HIV-1 capsid from all-atom molecular dynamics simulations

Human immunodeficiency virus type 1 (HIV-1) infection is highly dependent on its capsid. The capsid is a large container, made of ∼1,300 proteins with altogether 4 million atoms. Although the capsid proteins are all identical, they nevertheless arrange themselves into a largely asymmetric structure made of hexamers and pentamers. The large number of degrees of freedom and lack of symmetry pose a challenge to studying the chemical details of the HIV capsid. Simulations of over 64 million atoms for over 1 μs allow us to conduct a comprehensive study of the chemical–physical properties of an empty HIV-1 capsid, including its electrostatics, vibrational and acoustic properties, and the effects of solvent (ions and water) on the capsid. The simulations reveal critical details about the capsid with implications to biological function.

The large and complex HIV-1 capsid modulates several molecular events during HIV-1’s infective cycle. Here the authors use all-atom molecular dynamic simulations to probe the biophysical properties of the genome-free HIV-1 capsid.