The future is hybrid

Resolving distance variations by single-molecule FRET and EPR spectroscopy using rotamer libraries

Förster resonance energy transfer (FRET) and electron paramagnetic resonance (EPR) spectroscopy are complementary techniques for quantifying distances in the nanometer range. Both approaches are commonly employed for probing the conformations and conformational changes of biological macromolecules based on site-directed fluorescent or paramagnetic labeling. FRET can be applied in solution at ambient temperature and thus provides direct access to dynamics, especially if used at the single-molecule level, whereas EPR requires immobilization or work at cryogenic temperatures but provides data that can be more reliably used to extract distance distributions. However, a combined analysis of the complementary data from the two techniques has been complicated by the lack of a common modeling framework. Here, we demonstrate a systematic analysis approach based on rotamer libraries for both FRET and EPR labels to predict distance distributions between two labels from a structural model. Dynamics of the fluorophores within these distance distributions are taken into account by diffusional averaging, which improves the agreement with experiment. Benchmarking this methodology with a series of surface-exposed pairs of sites in a structured protein domain reveals that the lowest resolved distance differences can be as small as ∼0.25 nm for both techniques, with quantitative agreement between experimental and simulated transfer efficiencies within a range of ±0.045. Rotamer library analysis thus establishes a coherent way of treating experimental data from EPR and FRET and provides a basis for integrative structural modeling, including studies of conformational distributions and dynamics of biological macromolecules using both techniques.

Rapid Simulation of Unprocessed DEER Decay Data for Protein Fold Prediction

Despite advances in sampling and scoring strategies, Monte Carlo modeling methods still struggle to accurately predict de novo the structures of large proteins, membrane proteins, or proteins of complex topologies. Previous approaches have addressed these shortcomings by leveraging sparse distance data gathered using site-directed spin labeling and electron paramagnetic resonance spectroscopy to improve protein structure prediction and refinement outcomes. However, existing computational implementations entail compromises between coarse-grained models of the spin label that lower the resolution and explicit models that lead to resource-intense simulations. These methods are further limited by their reliance on distance distributions, which are calculated from a primary refocused echo decay signal and contain uncertainties that may require manual refinement. Here, we addressed these challenges by developing RosettaDEER, a scoring method within the Rosetta software suite capable of simulating double electron-electron resonance spectroscopy decay traces and distance distributions between spin labels fast enough to fold proteins de novo. We demonstrate that the accuracy of resulting distance distributions match or exceed those generated by more computationally intensive methods. Moreover, decay traces generated from these distributions recapitulate intermolecular background coupling parameters even when the time window of data collection is truncated. As a result, RosettaDEER can discriminate between poorly folded and native-like models by using decay traces that cannot be accurately converted into distance distributions using regularized fitting approaches. Finally, using two challenging test cases, we demonstrate that RosettaDEER leverages these experimental data for protein fold prediction more effectively than previous methods. These benchmarking results confirm that RosettaDEER can effectively leverage sparse experimental data for a wide array of modeling applications built into the Rosetta software suite.

Histone Interaction Landscapes Visualized by Crosslinking Mass Spectrometry in Intact Cell Nuclei

Cells organize their actions partly through tightly controlled protein-protein interactions-collectively termed the interactome. Here we use crosslinking mass spectrometry (XL-MS) to chart the protein-protein interactions in intact human nuclei. Overall, we identified ∼8,700 crosslinks, of which 2/3 represent links connecting distinct proteins. From these data, we gain insights on interactions involving histone proteins. We observed that core histones on the nucleosomes expose well-defined interaction hot spots. For several nucleosome-interacting proteins, such as USF3 and Ran GTPase, the data allowed us to build low-resolution models of their binding mode to the nucleosome. For HMGN2, the data guided the construction of a refined model of the interaction with the nucleosome, based on complementary NMR, XL-MS, and modeling. Excitingly, the analysis of crosslinks carrying posttranslational modifications allowed us to extract how specific modifications influence nucleosome interactions. Overall, our data depository will support future structural and functional analysis of cell nuclei, including the nucleoprotein assemblies they harbor.

Dissecting ribosomal particles throughout the kingdoms of life using advanced hybrid mass spectrometry methods

Biomolecular mass spectrometry has matured strongly over the past decades and has now reached a stage where it can provide deep insights into the structure and composition of large cellular assemblies. Here, we describe a three-tiered hybrid mass spectrometry approach that enables the dissection of macromolecular complexes in order to complement structural studies. To demonstrate the capabilities of the approach, we investigate ribosomes, large ribonucleoprotein particles consisting of a multitude of protein and RNA subunits. We identify sites of sequence processing, protein post-translational modifications, and the assembly and stoichiometry of individual ribosomal proteins in four distinct ribosomal particles of bacterial, plant and human origin. Amongst others, we report extensive cysteine methylation in the zinc finger domain of the human S27 protein, the heptameric stoichiometry of the chloroplastic stalk complex, the heterogeneous composition of human 40S ribosomal subunits and their association to the CrPV, and HCV internal ribosome entry site RNAs.

The contribution of modern EPR to structural biology

Electron paramagnetic resonance (EPR) spectroscopy combined with site-directed spin labelling is applicable to biomolecules and their complexes irrespective of system size and in a broad range of environments. Neither short-range nor long-range order is required to obtain structural restraints on accessibility of sites to water or oxygen, on secondary structure, and on distances between sites. Many of the experiments characterize a static ensemble obtained by shock-freezing. Compared with characterizing the dynamic ensemble at ambient temperature, analysis is simplified and information loss due to overlapping timescales of measurement and system dynamics is avoided. The necessity for labelling leads to sparse restraint sets that require integration with data from other methodologies for building models. The double electron–electron resonance experiment provides distance distributions in the nanometre range that carry information not only on the mean conformation but also on the width of the native ensemble. The distribution widths are often inconsistent with Anfinsen's concept that a sequence encodes a single native conformation defined at atomic resolution under physiological conditions.

MMM: A toolbox for integrative structure modeling

Structural characterization of proteins and their complexes may require integration of restraints from various experimental techniques. MMM (Multiscale Modeling of Macromolecules) is a Matlab-based open-source modeling toolbox for this purpose with a particular emphasis on distance distribution restraints obtained from electron paramagnetic resonance experiments on spin-labelled proteins and nucleic acids and their combination with atomistic structures of domains or whole protomers, small-angle scattering data, secondary structure information, homology information, and elastic network models. MMM does not only integrate various types of restraints, but also various existing modeling tools by providing a common graphical user interface to them. The types of restraints that can support such modeling and the available model types are illustrated by recent application examples.

High Precision FRET at Single-molecule Level for Biomolecule Structure Determination

A protocol on how to perform high-precision interdye distance measurements using Förster resonance energy transfer (FRET) at the single-molecule level in multiparameter fluorescence detection (MFD) mode is presented here. MFD maximizes the usage of all "dimensions" of fluorescence to reduce photophysical and experimental artifacts and allows for the measurement of interdye distance with an accuracy up to ~1 Å in rigid biomolecules. This method was used to identify three conformational states of the ligand-binding domain of the N-methyl-D-aspartate (NMDA) receptor to explain the activation of the receptor upon ligand binding. When comparing the known crystallographic structures with experimental measurements, they agreed within less than 3 Å for more dynamic biomolecules. Gathering a set of distance restraints that covers the entire dimensionality of the biomolecules would make it possible to provide a structural model of dynamic biomolecules.

Reliable nanometre-range distance distributions from 5-pulse double electron electron resonance

The partial excitation artefact in 5-pulse DEER data can be eliminated by experimental time shifting and signal processing.

Native Mass Spectrometry: What is in the Name?

Electrospray ionization mass spectrometry (ESI-MS) is nowadays one of the cornerstones of biomolecular mass spectrometry and proteomics. Advances in sample preparation and mass analyzers have enabled researchers to extract much more information from biological samples than just the molecular weight. In particular, relevant for structural biology, noncovalent protein-protein and protein-ligand complexes can now also be analyzed by MS. For these types of analyses, assemblies need to be retained in their native quaternary state in the gas phase. This initial small niche of biomolecular mass spectrometry, nowadays often referred to as "native MS," has come to maturation over the last two decades, with dozens of laboratories using it to study mostly protein assemblies, but also DNA and RNA-protein assemblies, with the goal to define structure-function relationships. In this perspective, we describe the origins of and (re)define the term native MS, portraying in detail what we meant by "native MS," when the term was coined and also describing what it does (according to us) not entail. Additionally, we describe a few examples highlighting what native MS is, showing its successes to date while illustrating the wide scope this technology has in solving complex biological questions. Graphical Abstract ᅟ.

Robotically assisted titration coupled to ion mobility-mass spectrometry reveals the interface structures and analysis parameters critical for multiprotein topology mapping

Multiprotein complexes have three-dimensional shapes and dynamic functions that impact almost every aspect of biochemistry. Despite this, our ability to rapidly assess the structures of such macromolecules lags significantly behind high-throughput efforts to identify their function, especially in the context of human disease. Here, we describe results obtained by coupling ion mobility-mass spectrometry with automated robotic sampling of different solvent compositions. This combination of technologies has allowed us to explore an extensive set of solution conditions for a group of eight protein homotetramers, representing a broad sample of protein structure and stability space. We find that altering solution ionic strength in concert with dimethylsulfoxide content is sufficient to disrupt the protein-protein interfaces of all of the complexes studied here. Ion mobility measurements captured for both intact assemblies and subcomplexes match expected values from available X-ray structures in all cases save two. For these exceptions, we find that distorted subcomplexes result from extreme disruption conditions, and are accompanied by small shifts in intact tetramers size, thus enabling the removal of distorted subcomplex data in downstream models. Furthermore, we find strong correlations between the relative intensities of disrupted protein tetramers and the relative number and type of interactions present at interfaces as a function of disrupting agent added. In most cases, this correlation appears strong enough to quantify various types of protein interfacial interactions within unknown proteins following appropriate calibration.

From lows to highs: using low-resolution models to phase X-ray data

The study of virus structures has contributed to methodological advances in structural biology that are generally applicable (molecular replacement and noncrystallographic symmetry are just two of the best known examples). Moreover, structural virology has been instrumental in forging the more general concept of exploiting phase information derived from multiple structural techniques. This hybridization of structural methods, primarily electron microscopy (EM) and X-ray crystallography, but also small-angle X-ray scattering (SAXS) and nuclear magnetic resonance (NMR) spectroscopy, is central to integrative structural biology. Here, the interplay of X-ray crystallography and EM is illustrated through the example of the structural determination of the marine lipid-containing bacteriophage PM2. Molecular replacement starting from an ~13 Å cryo-EM reconstruction, followed by cycling density averaging, phase extension and solvent flattening, gave the X-ray structure of the intact virus at 7 Å resolution This in turn served as a bridge to phase, to 2.5 Å resolution, data from twinned crystals of the major coat protein (P2), ultimately yielding a quasi-atomic model of the particle, which provided significant insights into virus evolution and viral membrane biogenesis.

Optimizing scoring function of protein-nucleic acid interactions with both affinity and specificity

Protein-nucleic acid (protein-DNA and protein-RNA) recognition is fundamental to the regulation of gene expression. Determination of the structures of the protein-nucleic acid recognition and insight into their interactions at molecular level are vital to understanding the regulation function. Recently, quantitative computational approach has been becoming an alternative of experimental technique for predicting the structures and interactions of biomolecular recognition. However, the progress of protein-nucleic acid structure prediction, especially protein-RNA, is far behind that of the protein-ligand and protein-protein structure predictions due to the lack of reliable and accurate scoring function for quantifying the protein-nucleic acid interactions. In this work, we developed an accurate scoring function (named as SPA-PN, SPecificity and Affinity of the Protein-Nucleic acid interactions) for protein-nucleic acid interactions by incorporating both the specificity and affinity into the optimization strategy. Specificity and affinity are two requirements of highly efficient and specific biomolecular recognition. Previous quantitative descriptions of the biomolecular interactions considered the affinity, but often ignored the specificity owing to the challenge of specificity quantification. We applied our concept of intrinsic specificity to connect the conventional specificity, which circumvents the challenge of specificity quantification. In addition to the affinity optimization, we incorporated the quantified intrinsic specificity into the optimization strategy of SPA-PN. The testing results and comparisons with other scoring functions validated that SPA-PN performs well on both the prediction of binding affinity and identification of native conformation. In terms of its performance, SPA-PN can be widely used to predict the protein-nucleic acid structures and quantify their interactions.

Structural templates for modeling homodimers

Oligomeric proteins are more abundant in nature than monomeric proteins, and involved in all biological processes. In the absence of an experimental structure, their subunits can be modeled from their sequence like monomeric proteins, but reliable procedures to build the oligomeric assembly are scarce. Template-based methods, which start from known protein structures, are commonly applied to model subunits. We present a method to model homodimers that relies on a structural alignment of the subunits, and test it on a set of 511 target structures recently released by the Protein Data Bank, taking as templates the earlier released structures of 3108 homodimeric proteins (H-set), and 2691 monomeric proteins that form dimer-like assemblies in crystals (M-set). The structural alignment identifies a H-set template for 97% of the targets, and in half of the cases, it yields a correct model of the dimer geometry and residue-residue contacts in the target. It also identifies a M-set template for most of the targets, and some of the crystal dimers are very similar to the target homodimers. The procedure efficiently detects homology at low levels of sequence identities, and points to erroneous quaternary structures in the Protein Data Bank. The high coverage of the target set suggests that the content of the Protein Data Bank already approaches the structural diversity of protein assemblies in nature, and that template-based methods should become the choice method for modeling oligomeric as well as monomeric proteins.

Visualizing the bacterial cell surface: an overview

The ultrastructure of bacteria is only accessible by electron microscopy. Our insights into the architecture of cells and cellular compartments such as the envelope and appendages is thus dependent on the progress of preparative and imaging techniques in electron microscopy. Here, I give a short overview of the development and characteristics of methods applied for imaging (components of) the bacterial surface and refer to key investigations and exemplary results. In the beginning of electron microscopy, fixation of biological material and staining for contrast enhancement were the standard techniques. The results from freeze-etching, metal shadowing and from ultrathin-sections of plastic-embedded material shaped our view of the cellular organization of bacteria. The introduction of cryo-preparations, keeping samples in their natural environment, and three-dimensional (3D) electron microscopy of isolated protein complexes and intact cells opened the door to a new dimension and has provided insight into the native structure of macromolecules and the in situ organization of cells at molecular resolution. Cryo-electron microscopy of single particles, together with other methods of structure determination, and cellular cryo-electron tomography will provide us with a quasi-atomic model of the bacterial cell surface in the years to come.

Traveling-wave Ion Mobility-Mass Spectrometry Reveals Additional Mechanistic Details in the Stabilization of Protein Complex Ions through Tuned Salt Additives

Ion mobility-mass spectrometry is often applied to the structural elucidation of multiprotein assemblies in cases where X-ray crystallography or NMR experiments have proved challenging. Such applications are growing steadily as we continue to probe regions of the proteome that are less-accessible to such high-resolution structural biology tools. Since ion mobility measures protein structure in the absence of bulk solvent, strategies designed to more-broadly stabilize native-like protein structures in the gas-phase would greatly enable the application of such measurements to challenging structural targets. Recently, we have begun investigating the ability of salt-based solution additives that remain bound to protein ions in the gas-phase to stabilize native-like protein structures. These experiments, which utilize collision induced unfolding and collision induced dissociation in a tandem mass spectrometry mode to measure protein stability, seek to develop a rank-order similar to the Hofmeister series that categorizes the general ability of different anions and cations to stabilize gas-phase protein structure. Here, we study magnesium chloride as a potential stabilizing additive for protein structures in vacuo, and find that the addition of this salt to solutions prior to nano-electrospray ionization dramatically enhances multiprotein complex structural stability in the gas-phase. Based on these experiments, we also refine the physical mechanism of cation-based protein complex ion stabilization by tracking the unfolding transitions experienced by cation-bound complexes. Upon comparison with unbound proteins, we find strong evidence that stabilizing cations act to tether protein complex structure. We conclude by putting the results reported here in context, and by projecting the future applications of this method.

Conventional electron microscopy, cryo-electron microscopy and cryo-electron tomography of viruses

Electron microscopy (EM) techniques have been crucial for understanding the structure of biological specimens such as cells, tissues and macromolecular assemblies. Viruses and related viral assemblies are ideal targets for structural studies that help to define essential biological functions. Whereas conventional EM methods use chemical fixation, dehydration, and staining of the specimens, cryo-electron microscopy (cryo-EM) preserves the native hydrated state. Combined with image processing and three-dimensional reconstruction techniques, cryo-EM provides 3D maps of these macromolecular complexes from projection images, at subnanometer to near-atomic resolutions. Cryo-EM is also a major technique in structural biology for dynamic studies of functional complexes, which are often unstable, flexible, scarce or transient in their native environments. As a tool, cryo-EM complements high-resolution techniques such as X-ray diffraction and NMR spectroscopy; these synergistic hybrid approaches provide important new information. Three-dimensional cryo-electron tomography goes further, and allows the study of viruses not only in their physiological state, but also in their natural environment in the cell, thereby bridging structural studies at the molecular and cellular levels.

Assembly of macromolecular complexes by satisfaction of spatial restraints from electron microscopy images

To obtain a structural model of a macromolecular assembly by single-particle EM, a large number of particle images need to be collected, aligned, clustered, averaged, and finally assembled via reconstruction into a 3D density map. This process is limited by the number and quality of the particle images, the accuracy of the initial model, and the compositional and conformational heterogeneity. Here, we describe a structure determination method that avoids the reconstruction procedure. The atomic structures of the individual complex components are assembled by optimizing a match against 2D EM class-average images, an excluded volume criterion, geometric complementarity, and optional restraints from proteomics and chemical cross-linking experiments. The optimization relies on a simulated annealing Monte Carlo search and a divide-and-conquer message-passing algorithm. Using simulated and experimentally determined EM class averages for 12 and 4 protein assemblies, respectively, we show that a few class averages can indeed result in accurate models for complexes of as many as five subunits. Thus, integrative structural biology can now benefit from the relative ease with which the EM class averages are determined.

Ion mobility-mass spectrometry for structural proteomics

Ion mobility coupled to mass spectrometry has been an important tool in the fields of chemical physics and analytical chemistry for decades, but its potential for interrogating the structure of proteins and multiprotein complexes has only recently begun to be realized. Today, ion mobility-mass spectrometry is often applied to the structural elucidation of protein assemblies that have failed high-throughput crystallization or NMR spectroscopy screens. Here, we highlight the technology, approaches and data that have led to this dramatic shift in use, including emerging trends such as the integration of ion mobility-mass spectrometry data with more classical (e.g., 'bottom-up') proteomics approaches for the rapid structural characterization of protein networks.

Hybrid computing: CPU+GPU co-processing and its application to tomographic reconstruction

Modern computers are equipped with powerful computing engines like multicore processors and GPUs. The 3DEM community has rapidly adapted to this scenario and many software packages now make use of high performance computing techniques to exploit these devices. However, the implementations thus far are purely focused on either GPUs or CPUs. This work presents a hybrid approach that collaboratively combines the GPUs and CPUs available in a computer and applies it to the problem of tomographic reconstruction. Proper orchestration of workload in such a heterogeneous system is an issue. Here we use an on-demand strategy whereby the computing devices request a new piece of work to do when idle. Our hybrid approach thus takes advantage of the whole computing power available in modern computers and further reduces the processing time. This CPU+GPU co-processing can be readily extended to other image processing tasks in 3DEM.

Structural analysis of nuclear receptors: from isolated domains to integral proteins

Nuclear receptors (NRs) are ligand dependent transcription factors that regulate gene expression. A number of in depth structure-function relationship studies have been performed, in particular with drug design perspectives. Recent structural results concerning integral receptors in diverse functional states, obtained using a combination of different methods, now allow a better understanding of the mechanisms involved in molecular regulation. The structural data highlight the importance of DNA sequences for binding selectivity and the role of promoter response elements in the spatial organization of the protein domains into functional complexes. The solution structures of several heterodimer complexes reveal how the DNA directs the positioning of coactivators. In the case of PPARγ-RXRα the comparison with the crystal structure reveals two different conformational states that illustrate the flexibility of the receptors. The results shed light on the dynamics of the molecular recognition process.

A coarse-grained force field for Protein-RNA docking

The awareness of important biological role played by functional, non coding (nc) RNA has grown tremendously in recent years. To perform their tasks, ncRNA molecules typically unite with protein partners, forming ribonucleoprotein complexes. Structural insight into their architectures can be greatly supplemented by computational docking techniques, as they provide means for the integration and refinement of experimental data that is often limited to fragments of larger assemblies or represents multiple levels of spatial resolution. Here, we present a coarse-grained force field for protein-RNA docking, implemented within the framework of the ATTRACT program. Complex structure prediction is based on energy minimization in rotational and translational degrees of freedom of binding partners, with possible extension to include structural flexibility. The coarse-grained representation allows for fast and efficient systematic docking search without any prior knowledge about complex geometry.

Cryo-electron tomography: gaining insight into cellular processes by structural approaches

Visualization of cellular processes at a resolution of the individual protein should involve integrative and complementary approaches that can eventually draw realistic functional and cellular landscapes. Electron tomography of vitrified but otherwise unaltered cells emerges as a central method for three-dimensional reconstruction of cellular architecture at a resolution of 2-6 nm. While a combination of correlative light-based microscopy with cryo-electron tomography (cryo-ET) provides medium-resolution insight into pivotal cellular processes, fitting high-resolution structural approaches, for example, X-ray crystallography, into reconstructed macromolecular assemblies provides unprecedented information on native protein assemblies. Thus, cryo-ET bridges the resolution gap between cellular and structural biology. In this article, we focus on the study of eukaryotic cells and macromolecular complexes in a close-to-life-state. We discuss recent developments and structural findings enabling major strides to be made in understanding complex physiological functions.

The power of correlative microscopy: multi-modal, multi-scale, multi-dimensional

Correlative microscopy is a sophisticated approach that combines the capabilities of typically separate, but powerful microscopy platforms: often including, but not limited, to conventional light, confocal and super-resolution microscopy, atomic force microscopy, transmission and scanning electron microscopy, magnetic resonance imaging and micro/nano CT (computed tomography). When targeting rare or specific events within large populations or tissues, correlative microscopy is increasingly being recognized as the method of choice. Furthermore, this multi-modal assimilation of technologies provides complementary and often unique information, such as internal and external spatial, structural, biochemical and biophysical details from the same targeted sample. The development of a continuous stream of cutting-edge applications, probes, preparation methodologies, hardware and software developments will enable realization of the full potential of correlative microscopy.

Simulation of transmission electron microscope images of biological specimens

We present a new approach to simulate electron cryo-microscope images of biological specimens. The framework for simulation consists of two parts; the first is a phantom generator that generates a model of a specimen suitable for simulation, the second is a transmission electron microscope simulator. The phantom generator calculates the scattering potential of an atomic structure in aqueous buffer and allows the user to define the distribution of molecules in the simulated image. The simulator includes a well defined electron-specimen interaction model based on the scalar Schrödinger equation, the contrast transfer function for optics, and a noise model that includes shot noise as well as detector noise including detector blurring. To enable optimal performance, the simulation framework also includes a calibration protocol for setting simulation parameters. To test the accuracy of the new framework for simulation, we compare simulated images to experimental images recorded of the Tobacco Mosaic Virus (TMV) in vitreous ice. The simulated and experimental images show good agreement with respect to contrast variations depending on dose and defocus. Furthermore, random fluctuations present in experimental and simulated images exhibit similar statistical properties. The simulator has been designed to provide a platform for development of new instrumentation and image processing procedures in single particle electron microscopy, two-dimensional crystallography and electron tomography with well documented protocols and an open source code into which new improvements and extensions are easily incorporated.

NANOSCALE SELF-ASSEMBLY FOR DELIVERY OF THERAPEUTICS AND IMAGING AGENTS

Self-assemblies are complex structures spontaneously organized from simpler subcomponents, primarily through noncovalent interactions. These structures are being exploited as delivery vehicles of therapeutic and imaging agents. They have two unique advantages in comparison to other vehicles: 1) they are able to assume complex structures that are difficult to attain by chemical synthesis, and 2) the dissociation of self-assembled structures can be triggered by external stimuli, which can serve as a mechanism of payload release. In this review, we discuss two naturally occurring (proteins and viral capsids) and five engineered self-assemblies (vesicles, micelles, proteins, hydrogels, and inclusion complexes) that are under development for delivery of drugs and imaging agents. For each class of self-assembled supramolecular structures, we examine its structural and physicochemical properties, and potential applications within the context of assembly, loading, and payload release.

Separating and visualising protein assemblies by means of preparative mass spectrometry and microscopy

Many multi-protein assemblies exhibit characteristics which hamper their structural and dynamical characterization. These impediments include low copy number, heterogeneity, polydispersity, hydrophobicity, and intrinsic disorder. It is becoming increasingly apparent that both novel and hybrid structural biology approaches need to be developed to tackle the most challenging targets. Nanoelectrospray mass spectrometry has matured over the last decade to enable the elucidation of connectivity and composition of large protein assemblies. Moreover, comparing mass spectrometry data with transmission electron microscopy images has enabled the mapping of subunits within topological models. Here we describe a preparative form of mass spectrometry designed to isolate specific protein complexes from within a heterogeneous ensemble, and to 'soft-land' these target complexes for ex situ imaging. By building a retractable probe incorporating a versatile target holder, and modifying the ion optics of a commercial mass spectrometer, we show that we can steer the macromolecular ion beam onto a target for imaging by means of transmission electron microscopy and atomic force microscopy. Our data for the tetradecameric chaperonin GroEL show that not only are the molecular volumes of the landed particles consistent with the overall dimensions of the complex, but also that their gross topological features can be maintained.

Macromolecular docking restrained by a small angle X-ray scattering profile

While many structures of single protein components are becoming available, structural characterization of their complexes remains challenging. Methods for modeling assembly structures from individual components frequently suffer from large errors, due to protein flexibility and inaccurate scoring functions. However, when additional information is available, it may be possible to reduce the errors and compute near-native complex structures. One such type of information is a small angle X-ray scattering (SAXS) profile that can be collected in a high-throughput fashion from a small amount of sample in solution. Here, we present an efficient method for protein-protein docking with a SAXS profile (FoXSDock): generation of complex models by rigid global docking with PatchDock, filtering of the models based on the SAXS profile, clustering of the models, and refining the interface by flexible docking with FireDock. FoXSDock is benchmarked on 124 protein complexes with simulated SAXS profiles, as well as on 6 complexes with experimentally determined SAXS profiles. When induced fit is less than 1.5Å interface C(α) RMSD and the fraction residues of missing from the component structures is less than 3%, FoXSDock can find a model close to the native structure within the top 10 predictions in 77% of the cases; in comparison, docking alone succeeds in only 34% of the cases. Thus, the integrative approach significantly improves on molecular docking alone. The improvement arises from an increased resolution of rigid docking sampling and more accurate scoring.

Biocrystallography: past, present, future

The evolution of biocrystallography from the pioneers' time to the present era of global biology is presented in relation to the development of methodological and instrumental advances for molecular sample preparation and structure elucidation over the last 6 decades. The interdisciplinarity of the field that generated cross-fertilization between physics- and biology-focused themes is emphasized. In particular, strategies to circumvent the main bottlenecks of biocrystallography are discussed. They concern (i) the way macromolecular targets are selected, designed, and characterized, (ii) crystallogenesis and how to deal with physical and biological parameters that impact crystallization for growing and optimizing crystals, and (iii) the methods for crystal analysis and 3D structure determination. Milestones that have marked the history of biocrystallography illustrate the discussion. Finally, the future of the field is envisaged. Wide gaps of the structural space need to be filed and membrane proteins as well as intrinsically unstructured proteins still constitute challenging targets. Solving supramolecular assemblies of increasing complexity, developing a "4D biology" for decrypting the kinematic changes in macromolecular structures in action, integrating these structural data in the whole cell organization, and deciphering biomedical implications will represent the new frontiers.

Understanding biophysicochemical interactions at the nano-bio interface

Rapid growth in nanotechnology is increasing the likelihood of engineered nanomaterials coming into contact with humans and the environment. Nanoparticles interacting with proteins, membranes, cells, DNA and organelles establish a series of nanoparticle/biological interfaces that depend on colloidal forces as well as dynamic biophysicochemical interactions. These interactions lead to the formation of protein coronas, particle wrapping, intracellular uptake and biocatalytic processes that could have biocompatible or bioadverse outcomes. For their part, the biomolecules may induce phase transformations, free energy releases, restructuring and dissolution at the nanomaterial surface. Probing these various interfaces allows the development of predictive relationships between structure and activity that are determined by nanomaterial properties such as size, shape, surface chemistry, roughness and surface coatings. This knowledge is important from the perspective of safe use of nanomaterials.