Go hybrid: EM, crystallography, and beyond

Biophysical applications in structural and molecular biology

The main objective of structural biology is to model proteins and other biological macromolecules and link the structural information to function and dynamics. The biological functions of protein molecules and nucleic acids are inherently dependent on their conformational dynamics. Imaging of individual molecules and their dynamic characteristics is an ample source of knowledge that brings new insights about mechanisms of action. The atomic-resolution structural information on most of the biomolecules has been solved by biophysical techniques; either by X-ray diffraction in single crystals or by nuclear magnetic resonance (NMR) spectroscopy in solution. Cryo-electron microscopy (cryo-EM) is emerging as a new tool for analysis of a larger macromolecule that couldn't be solved by X-ray crystallography or NMR. Now a day's low-resolution Cryo-EM is used in combination with either X-ray crystallography or NMR. The present review intends to provide updated information on applications like X-ray crystallography, cryo-EM and NMR which can be used independently and/or together in solving structures of biological macromolecules for our full comprehension of their biological mechanisms.

Reconstruction of low-resolution molecular structures from simulated atomic force microscopy images

BACKGROUND

Atomic Force Microscopy (AFM) is an experimental technique to study structure-function relationship of biomolecules. AFM provides images of biomolecules at nanometer resolution. High-speed AFM experiments produce a series of images following dynamics of biomolecules. To further understand biomolecular functions, information on three-dimensional (3D) structures is beneficial.

METHOD

We aim to recover 3D information from an AFM image by computational modeling. The AFM image includes only low-resolution representation of a molecule; therefore we represent the structures by a coarse grained model (Gaussian mixture model). Using Monte-Carlo sampling, candidate models are generated to increase similarity between AFM images simulated from the models and target AFM image.

RESULTS

The algorithm was tested on two proteins to model their conformational transitions. Using a simulated AFM image as reference, the algorithm can produce a low-resolution 3D model of the target molecule. Effect of molecular orientations captured in AFM images on the 3D modeling performance was also examined and it is shown that similar accuracy can be obtained for many orientations.

CONCLUSIONS

The proposed algorithm can generate 3D low-resolution protein models, from which conformational transitions observed in AFM images can be interpreted in more detail.

GENERAL SIGNIFICANCE

High-speed AFM experiments allow us to directly observe biomolecules in action, which provides insights on biomolecular function through dynamics. However, as only partial structural information can be obtained from AFM data, this new AFM based hybrid modeling method would be useful to retrieve 3D information of the entire biomolecule.

Combining X-Ray Crystallography with Small Angle X-Ray Scattering to Model Unstructured Regions of Nsa1 from S. Cerevisiae

Determination of the full-length structure of ribosome assembly factor Nsa1 from Saccharomyces cerevisiae (S. cerevisiae) is challenging because of the disordered and protease labile C-terminus of the protein. This manuscript describes the methods to purify recombinant Nsa1 from S. cerevisiae for structural analysis by both X-ray crystallography and SAXS. X-ray crystallography was utilized to solve the structure of the well-ordered N-terminal WD40 domain of Nsa1, and then SAXS was used to resolve the structure of the C-terminus of Nsa1 in solution. Solution scattering data was collected from full-length Nsa1 in solution. The theoretical scattering amplitudes were calculated from the high-resolution crystal structure of the WD40 domain, and then a combination of rigid body and ab initio modeling revealed the C-terminus of Nsa1. Through this hybrid approach the quaternary structure of the entire protein was reconstructed. The methods presented here should be generally applicable for the hybrid structural determination of other proteins composed of a mix of structured and unstructured domains.

Hybrid Methods for Macromolecular Modeling by Molecular Mechanics Simulations with Experimental Data

Hybrid approaches for the modeling of macromolecular complexes that combine computational molecular mechanics simulations with experimental data are discussed. Experimental data for biological molecular structures are often low-resolution, and thus, do not contain enough information to determine the atomic positions of molecules. This is especially true when the dynamics of large macromolecules are the focus of the study. However, computational modeling can complement missing information. Significant increase in computational power, as well as the development of new modeling algorithms allow us to model structures of biological macromolecules reliably, using experimental data as references. We review the basics of molecular mechanics approaches, such as atomic model force field, and coarse-grained models, molecular dynamics simulation and normal mode analysis and describe how they could be used for flexible fitting hybrid modeling with experimental data, especially from cryo-EM and SAXS.

Flexible fitting to cryo-EM density map using ensemble molecular dynamics simulations

Flexible fitting is a computational algorithm to derive a new conformational model that conforms to low-resolution experimental data by transforming a known structure. A common application is against data from cryo-electron microscopy to obtain conformational models in new functional states. The conventional flexible fitting algorithms cannot derive correct structures in some cases due to the complexity of conformational transitions. In this study, we show the importance of conformational ensemble in the refinement process by performing multiple fittings trials using a variety of different force constants. Application to simulated maps of Ca²⁺ ATPase and diphtheria toxin as well as experimental data of release factor 2 revealed that for these systems, multiple conformations with similar agreement with the density map exist and a large number of fitting trials are necessary to generate good models. Clustering analysis can be an effective approach to avoid over-fitting models. In addition, we show that an automatic adjustment of the biasing force constants during the fitting process, implemented as replica-exchange scheme, can improve the success rate. © 2017 Wiley Periodicals, Inc.

Towards an efficient compression of 3D coordinates of macromolecular structures

The size and complexity of 3D macromolecular structures available in the Protein Data Bank is constantly growing. Current tools and file formats have reached limits of scalability. New compression approaches are required to support the visualization of large molecular complexes and enable new and scalable means for data analysis. We evaluated a series of compression techniques for coordinates of 3D macromolecular structures and identified the best performing approaches. By balancing compression efficiency in terms of the decompression speed and compression ratio, and code complexity, our results provide the foundation for a novel standard to represent macromolecular coordinates in a compact and useful file format.

Validation of Protein-Ligand Crystal Structure Models: Small Molecule and Peptide Ligands

Models of target proteins in complex with small molecule ligands or peptide ligands are of significant interest to the biomedical research community. Structure-guided lead discovery and structure-based drug design make extensive use of such models. The bound ligands comprise only a small fraction of the total X-ray scattering mass, and therefore particular care must be taken to properly validate the atomic model of the ligand as experimental data can often be scarce. The ligand model must be validated against both the primary experimental data and the local environment, specifically: (1) the primary evidence in the form of the electron density, (2) examined for reasonable stereochemistry, and (3) the chemical plausibility of the binding interactions must be inspected. Tools that assist the researcher in the validation process are presented.

New generation of elastic network models

The intrinsic flexibility of proteins and nucleic acids can be grasped from remarkably simple mechanical models of particles connected by springs. In recent decades, Elastic Network Models (ENMs) combined with Normal Model Analysis widely confirmed their ability to predict biologically relevant motions of biomolecules and soon became a popular methodology to reveal large-scale dynamics in multiple structural biology scenarios. The simplicity, robustness, low computational cost, and relatively high accuracy are the reasons behind the success of ENMs. This review focuses on recent advances in the development and application of ENMs, paying particular attention to combinations with experimental data. Successful application scenarios include large macromolecular machines, structural refinement, docking, and evolutionary conservation.

EM∩IM: software for relating ion mobility mass spectrometry and electron microscopy data

We present EM∩IM, software that allows the calculation of collision cross-sections from electron density maps obtained for example by means of transmission electron microscopy. This allows the assessment of structures other than those described by atomic coordinates with ion mobility mass spectrometry data, and provides a new means for contouring and validating electron density maps. EM∩IM thereby facilitates the use of data obtained in the gas phase within structural biology studies employing diverse experimental methodologies.

γ-TEMPy: Simultaneous Fitting of Components in 3D-EM Maps of Their Assembly Using a Genetic Algorithm

We have developed a genetic algorithm for building macromolecular complexes using only a 3D-electron microscopy density map and the atomic structures of the relevant components. For efficient sampling the method uses map feature points calculated by vector quantization. The fitness function combines a mutual information score that quantifies the goodness of fit with a penalty score that helps to avoid clashes between components. Testing the method on ten assemblies (containing 3–8 protein components) and simulated density maps at 10, 15, and 20 Å resolution resulted in identification of the correct topology in 90%, 70%, and 60% of the cases, respectively. We further tested it on four assemblies with experimental maps at 7.2–23.5 Å resolution, showing the ability of the method to identify the correct topology in all cases. We have also demonstrated the importance of the map feature-point quality on assembly fitting in the lack of additional experimental information.

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γ-TEMPy uses a genetic algorithm to fit multiple components into 3D-EM density maps

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The fitness score is a combination of a Mutual Information score and a clash penalty

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Efficient sampling is aided by using map feature points from vector quantization

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Native topologies for assemblies containing up to eight components can be predicted

TEMPy: a Python library for assessment of three-dimensional electron microscopy density fits

TEMPy is an object-oriented Python library that provides the means to validate density fits in electron microscopy reconstructions. This article highlights several features of particular interest for this purpose and includes some customized examples.

Three-dimensional electron microscopy is currently one of the most promising techniques used to study macromolecular assemblies. Rigid and flexible fitting of atomic models into density maps is often essential to gain further insights into the assemblies they represent. Currently, tools that facilitate the assessment of fitted atomic models and maps are needed. TEMPy (template and electron microscopy comparison using Python) is a toolkit designed for this purpose. The library includes a set of methods to assess density fits in intermediate-to-low resolution maps, both globally and locally. It also provides procedures for single-fit assessment, ensemble generation of fits, clustering, and multiple and consensus scoring, as well as plots and output files for visualization purposes to help the user in analysing rigid and flexible fits. The modular nature of TEMPy helps the integration of scoring and assessment of fits into large pipelines, making it a tool suitable for both novice and expert structural biologists.

Pathogenesis of human diffusely adhering Escherichia coli expressing Afa/Dr adhesins (Afa/Dr DAEC): current insights and future challenges

The pathogenicity and clinical pertinence of diffusely adhering Escherichia coli expressing the Afa/Dr adhesins (Afa/Dr DAEC) in urinary tract infections (UTIs) and pregnancy complications are well established. In contrast, the implication of intestinal Afa/Dr DAEC in diarrhea is still under debate. These strains are age dependently involved in diarrhea in children, are apparently not involved in diarrhea in adults, and can also be asymptomatic intestinal microbiota strains in children and adult. This comprehensive review analyzes the epidemiology and diagnosis and highlights recent progress which has improved the understanding of Afa/Dr DAEC pathogenesis. Here, I summarize the roles of Afa/Dr DAEC virulence factors, including Afa/Dr adhesins, flagella, Sat toxin, and pks island products, in the development of specific mechanisms of pathogenicity. In intestinal epithelial polarized cells, the Afa/Dr adhesins trigger cell membrane receptor clustering and activation of the linked cell signaling pathways, promote structural and functional cell lesions and injuries in intestinal barrier, induce proinflammatory responses, create angiogenesis, instigate epithelial-mesenchymal transition-like events, and lead to pks-dependent DNA damage. UTI-associated Afa/Dr DAEC strains, following adhesin-membrane receptor cell interactions and activation of associated lipid raft-dependent cell signaling pathways, internalize in a microtubule-dependent manner within urinary tract epithelial cells, develop a particular intracellular lifestyle, and trigger a toxin-dependent cell detachment. In response to Afa/Dr DAEC infection, the host epithelial cells generate antibacterial defense responses. Finally, I discuss a hypothetical role of intestinal Afa/Dr DAEC strains that can act as "silent pathogens" with the capacity to emerge as "pathobionts" for the development of inflammatory bowel disease and intestinal carcinogenesis.

Structural basis of protein-protein interactions

Regulated interactions between proteins govern signaling pathways within and between cells. Structural studies on protein complexes formed reversibly and/or transiently illustrate the remarkable diversity of interactions, both in terms of interfacial size and nature. In recent years, "domain-peptide" interactions have gained much greater recognition and may be viewed as both pre-translational and posttranslational-dependent functional switches. Our understanding of the multistep regulation of auto-inhibited multidomain proteins has also grown. Their activity may be understood as the "combinatorial" output of multiple input signals, including phosphorylation, location, and mechanical force. The prospects for bridging the gap between the new "systems biology" data and the traditional "reductionist" data are also discussed.

Topological models of heteromeric protein assemblies from mass spectrometry: application to the yeast eIF3:eIF5 complex

Describing, understanding, and modulating the function of the cell require elucidation of the structures of macromolecular assemblies. Here, we describe an integrative method for modeling heteromeric complexes using as a starting point disassembly pathways determined by native mass spectrometry (MS). In this method, the pathway data and other available information are encoded as a scoring function on the positions of the subunits of the complex. The method was assessed on its ability to reproduce the native contacts in five benchmark cases with simulated MS data and two cases with real MS data. To illustrate the power of our method, we purified the yeast initiation factor 3 (eIF3) complex and characterized it by native MS and chemical crosslinking MS. We established substoichiometric binding of eIF5 and derived a model for the five-subunit eIF3 complex, at domain level, consistent with its role as a scaffold for other initiation factors.

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Integrative MS method allows topological characterization of heteromeric complexes

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Intersubunit crosslinks increase the precision of the predicted topologies

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A 3D model of eIF3:eIF5 complex was built using restraints from MS-based methods

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Integrative modeling reveals two submodules within eIF3: eIF3b:i:g and eIF3a:c

Signal transduction: From the atomic age to the post-genomic era

We have come a long way in the 55 years since Edmond Fischer and the late Edwin Krebs discovered that the activity of glycogen phosphorylase is regulated by reversible protein phosphorylation. Many of the fundamental molecular mechanisms that operate in biological signaling have since been characterized and the vast web of interconnected pathways that make up the cellular signaling network has been mapped in considerable detail. Nonetheless, it is important to consider how fast this field is still moving and the issues at the current boundaries of our understanding. One must also appreciate what experimental strategies have allowed us to attain our present level of knowledge. We summarize here some key issues (both conceptual and methodological), raise unresolved questions, discuss potential pitfalls, and highlight areas in which our understanding is still rudimentary. We hope these wide-ranging ruminations will be useful to investigators who carry studies of signal transduction forward during the rest of the 21st century.

Deep mutational scanning: a new style of protein science

Mutagenesis provides insight into proteins, but only recently have assays that couple genotype to phenotype been used to assess the activities of as many as 1 million mutant versions of a protein in a single experiment. This approach-'deep mutational scanning'-yields large-scale data sets that can reveal intrinsic protein properties, protein behavior within cells and the consequences of human genetic variation. Deep mutational scanning is transforming the study of proteins, but many challenges must be tackled for it to fulfill its promise.

Structure of the VipA/B type VI secretion complex suggests a contraction-state-specific recycling mechanism

The bacterial type VI secretion system is a multicomponent molecular machine directed against eukaryotic host cells and competing bacteria. An intracellular contractile tubular structure that bears functional homology with bacteriophage tails is pivotal for ejection of pathogenic effectors. Here, we present the 6 Å cryoelectron microscopy structure of the contracted Vibrio cholerae tubule consisting of the proteins VipA and VipB. We localized VipA and VipB in the protomer and identified structural homology between the C-terminal segment of VipB and the tail-sheath protein of T4 phages. We propose that homologous segments in VipB and T4 phages mediate tubule contraction. We show that in type VI secretion, contraction leads to exposure of the ClpV recognition motif, which is embedded in the type VI-specific four-helix-bundle N-domain of VipB. Disaggregation of the tubules by the AAA+ protein ClpV and recycling of the VipA/B subunits are thereby limited to the contracted state.

Finding the right fit: chiseling structures out of cryo-electron microscopy maps

Cryo-electron microscopy is a central tool for studying the architecture of macromolecular complexes at subnanometer resolution. Interpretation of an electron microscopy map requires its computational integration with data about the structure's components from all available sources, notably atomic models. Selecting a protocol for EM density-guided integrative structural modeling depends on the resolution and quality of the EM map as well as the available complimentary datasets. Here, we review rigid, flexible, and de novo integrative fitting into EM maps and provide guidelines and considerations for the design of modeling experiments. Finally, we discuss efforts towards establishing unified criteria for map and model assessment and validation.

Information-driven modeling of large macromolecular assemblies using NMR data

Availability of high-resolution atomic structures is one of the prerequisites for a mechanistic understanding of biomolecular function. This atomic information can, however, be difficult to acquire for interesting systems such as high molecular weight and multi-subunit complexes. For these, low-resolution and/or sparse data from a variety of sources including NMR are often available to define the interaction between the subunits. To make best use of all the available information and shed light on these challenging systems, integrative computational tools are required that can judiciously combine and accurately translate the sparse experimental data into structural information. In this Perspective we discuss NMR techniques and data sources available for the modeling of large and multi-subunit complexes. Recent developments are illustrated by particularly challenging application examples taken from the literature. Within this context, we also position our data-driven docking approach, HADDOCK, which can integrate a variety of information sources to drive the modeling of biomolecular complexes. It is the synergy between experimentation and computational modeling that will provides us with detailed views on the machinery of life and lead to a mechanistic understanding of biomolecular function.

Conformational States of macromolecular assemblies explored by integrative structure calculation

A detailed description of macromolecular assemblies in multiple conformational states can be very valuable for understanding cellular processes. At present, structural determination of most assemblies in different biologically relevant conformations cannot be achieved by a single technique and thus requires an integrative approach that combines information from multiple sources. Different techniques require different computational methods to allow efficient and accurate data processing and analysis. Here, we summarize the latest advances and future challenges in computational methods that help the interpretation of data from two techniques—mass spectrometry and three-dimensional cryo-electron microscopy (with focus on alignment and classification of heterogeneous subtomograms from cryo-electron tomography). We evaluate how new developments in these two broad fields will lead to further integration with atomic structures to broaden our picture of the dynamic behavior of assemblies in their native environment.

Modeling stochastic kinetics of molecular machines at multiple levels: from molecules to modules

A molecular machine is either a single macromolecule or a macromolecular complex. In spite of the striking superficial similarities between these natural nanomachines and their man-made macroscopic counterparts, there are crucial differences. Molecular machines in a living cell operate stochastically in an isothermal environment far from thermodynamic equilibrium. In this mini-review we present a catalog of the molecular machines and an inventory of the essential toolbox for theoretically modeling these machines. The tool kits include 1), nonequilibrium statistical-physics techniques for modeling machines and machine-driven processes; and 2), statistical-inference methods for reverse engineering a functional machine from the empirical data. The cell is often likened to a microfactory in which the machineries are organized in modular fashion; each module consists of strongly coupled multiple machines, but different modules interact weakly with each other. This microfactory has its own automated supply chain and delivery system. Buoyed by the success achieved in modeling individual molecular machines, we advocate integration of these models in the near future to develop models of functional modules. A system-level description of the cell from the perspective of molecular machinery (the mechanome) is likely to emerge from further integrations that we envisage here.

Structure, assembly and dynamics of macromolecular complexes by single particle cryo-electron microscopy

BACKGROUND

Proteins in their majority act rarely as single entities. Multisubunit macromolecular complexes are the actors in most of the cellular processes. These nanomachines are hold together by weak protein-protein interactions and undergo functionally important conformational changes. TFIID is such a multiprotein complex acting in eukaryotic transcription initiation. This complex is first to be recruited to the promoter of the genes and triggers the formation of the transcription preinitiation complex involving RNA polymerase II which leads to gene transcription. The exact role of TFIID in this process is not yet understood.

METHODS

Last generation electron microscopes, improved data collection and new image analysis tools made it possible to obtain structural information of biological molecules at atomic resolution. Cryo-electron microscopy of vitrified samples visualizes proteins in a fully hydrated, close to native state. Molecular images are recorded at liquid nitrogen temperature in low electron dose conditions to reduce radiation damage. Digital image analysis of these noisy images aims at improving the signal-to-noise ratio, at separating distinct molecular views and at reconstructing a three-dimensional model of the biological particle.

RESULTS

Using these methods we showed the early events of an activated transcription initiation process. We explored the interaction of the TFIID coactivator with the yeast Rap1 activator, the transcription factor TFIIA and the promoter DNA. We demonstrated that TFIID serves as an assembly platform for transient protein-protein interactions, which are essential for transcription initiation.

CONCLUSIONS

Recent developments in electron microscopy have provided new insights into the structural organization and the dynamic reorganization of large macromolecular complexes. Examples of near-atomic resolutions exist but the molecular flexibility of macromolecular complexes remains the limiting factor in most case. Electron microscopy has the potential to provide both structural and dynamic information of biological assemblies in order to understand the molecular mechanisms of their functions.

High-resolution network biology: connecting sequence with function

Proteins are not monolithic entities; rather, they can contain multiple domains that mediate distinct interactions, and their functionality can be regulated through post-translational modifications at multiple distinct sites. Traditionally, network biology has ignored such properties of proteins and has instead examined either the physical interactions of whole proteins or the consequences of removing entire genes. In this Review, we discuss experimental and computational methods to increase the resolution of protein-protein, genetic and drug-gene interaction studies to the domain and residue levels. Such work will be crucial for using interaction networks to connect sequence and structural information, and to understand the biological consequences of disease-associated mutations, which will hopefully lead to more effective therapeutic strategies.

Optimod--an automated approach for constructing and optimizing initial models for single-particle electron microscopy

Single-particle cryo-electron microscopy is now well established as a technique for the structural characterization of large macromolecules and macromolecular complexes. The raw data is very noisy and consists of two-dimensional projections, from which the 3D biological object must be reconstructed. The 3D object depends upon knowledge of proper angular orientations assigned to the 2D projection images. Numerous algorithms have been developed for determining relative angular orientations between 2D images, but the transition from 2D to 3D remains challenging and can result in erroneous and conflicting results. Here we describe a general, automated procedure, called OptiMod, for reconstructing and optimizing 3D models using common-lines methodologies. OptiMod approximates orientation angles and reconstructs independent maps from 2D class averages. It then iterates the procedure, while considering each map as a raw solution that needs to be compared with other possible outcomes. We incorporate procedures for 3D alignment, clustering, and refinement to optimize each map, as well as standard scoring metrics to facilitate the selection of the optimal model. We also show that small angle tilt-pair data can be included as one of the scoring metrics to improve the selection of the optimal initial model, and also to provide a validation check. The overall approach is demonstrated using two experimental cryo-EM data sets--the 80S ribosome that represents a relatively straightforward case for ab initio reconstruction, and the Tf-TfR complex that represents a challenging case in that it has previously been shown to provide multiple equally plausible solutions to the initial model problem.

Biochemistry. Integrative structural biology

Integrative approaches using data from a wide variety of methods are yielding model structures of complex biological assemblies.