Conformational States of macromolecular assemblies explored by integrative structure calculation

Mapping the Multiscale Proteomic Organization of Cellular and Disease Phenotypes

While the primary sequences of human proteins have been cataloged for over a decade, determining how these are organized into a dynamic collection of multiprotein assemblies, with structures and functions spanning biological scales, is an ongoing venture. Systematic and data-driven analyses of these higher-order structures are emerging, facilitating the discovery and understanding of cellular phenotypes. At present, knowledge of protein localization and function has been primarily derived from manual annotation and curation in resources such as the Gene Ontology, which are biased toward richly annotated genes in the literature. Here, we envision a future powered by data-driven mapping of protein assemblies. These maps can capture and decode cellular functions through the integration of protein expression, localization, and interaction data across length scales and timescales. In this review, we focus on progress toward constructing integrated cell maps that accelerate the life sciences and translational research.

Molecular Dynamics and Other HPC Simulations for Drug Discovery

High performance computing (HPC) is taking an increasingly important place in drug discovery. It makes possible the simulation of complex biochemical systems with high precision in a short time, thanks to the use of sophisticated algorithms. It promotes the advancement of knowledge in fields that are inaccessible or difficult to access through experimentation and it contributes to accelerating the discovery of drugs for unmet medical needs while reducing costs. Herein, we report how computational performance has evolved over the past years, and then we detail three domains where HPC is essential. Molecular dynamics (MD) is commonly used to explore the flexibility of proteins, thus generating a better understanding of different possible approaches to modulate their activity. Modeling and simulation of biopolymer complexes enables the study of protein-protein interactions (PPI) in healthy and disease states, thus helping the identification of targets of pharmacological interest. Virtual screening (VS) also benefits from HPC to predict in a short time, among millions or billions of virtual chemical compounds, the best potential ligands that will be tested in relevant assays to start a rational drug design process.

Are the Gas-Phase Structures of Molecular Elephants Enduring or Ephemeral? Results from Time-Dependent, Tandem Ion Mobility

The structural stability of biomolecules in the gas phase remains an important topic in mass spectrometry applications for structural biology. Here, we evaluate the kinetic stability of native-like protein ions using time-dependent, tandem ion mobility (IM). In these tandem IM experiments, ions of interest are mobility-selected after a first dimension of IM and trapped for up to ∼14 s. Time-dependent, collision cross section distributions are then determined from separations in a second dimension of IM. In these experiments, monomeric protein ions exhibited structural changes specific to both protein and charge state, whereas large protein complexes did not undergo resolvable structural changes on the timescales of these experiments. We also performed energy-dependent experiments, i.e., collision-induced unfolding, as a comparison for time-dependent experiments to understand the extent of unfolding. Collision cross section values observed in energy-dependent experiments using high collision energies were significantly larger than those observed in time-dependent experiments, indicating that the structures observed in time-dependent experiments remain kinetically trapped and retain some memory of their solution-phase structure. Although structural evolution should be considered for highly charged, monomeric protein ions, these experiments demonstrate that higher-mass protein ions can have remarkable kinetic stability in the gas phase.

Development of a Chemically Modified Sensor Based on a Pentapeptide and Its Application for Sensitive Detection of Verbascoside in Extra Virgin Olive Oil

In addition to their antioxidant and antimicrobial action in functional foods, beverages, and in some dermato-cosmetic products, olive phenolic compounds are also recognized for their role in the prevention of diabetes and inflammation, treatment of heart disease and, consequently, of the numerous chronic diseases mediated by the free radicals. In recent years, attention has increased, in particular, regarding one of the most important compound in extra virgin olive oil (EVOO) having glycosidic structure, namely verbocoside, due to the existence in the literature of numerous studies demonstrating its remarkable contribution to the prophylaxis and treatment of various disorders of the human body. The purpose of this study was the qualitative and quantitative determination of verbascoside in commercial EVOOs from different regions by means of a newly developed sensor based on a screen-printed carbon electrode (SPCE) modified with graphene oxide (GPHOX), on the surface of which a pentapeptide was immobilized by means of glutaraldehyde as cross-linking agent. The modified electrode surface was investigated using both Fourier-transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM) methods. This newly developed sensor has shown a high sensibility compared to the unmodified electrode, a low detection limit (LOD) of up to 9.38 × 10^-8 M, and a wide linearity range between 0.1 µM and 10.55 µM. The applicability of the modified sensor was confirmed by detecting verbascoside in ten different EVOOs samples using the cyclic voltammetry (CV) method, with very good results. The validation of the electroanalytical method was performed by using the standard addition method with very good recoveries in the range of 97.48-103.77%.

Peptide-Protein Interactions: From Drug Design to Supramolecular Biomaterials

The self-recognition and self-assembly of biomolecules are spontaneous processes that occur in Nature and allow the formation of ordered structures, at the nanoscale or even at the macroscale, under thermodynamic and kinetic equilibrium as a consequence of specific and local interactions. In particular, peptides and peptidomimetics play an elected role, as they may allow a rational approach to elucidate biological mechanisms to develop new drugs, biomaterials, catalysts, or semiconductors. The forces that rule self-recognition and self-assembly processes are weak interactions, such as hydrogen bonding, electrostatic attractions, and van der Waals forces, and they underlie the formation of the secondary structure (e.g., α-helix, β-sheet, polyproline II helix), which plays a key role in all biological processes. Here, we present recent and significant examples whereby design was successfully applied to attain the desired structural motifs toward function. These studies are important to understand the main interactions ruling the biological processes and the onset of many pathologies. The types of secondary structure adopted by peptides during self-assembly have a fundamental importance not only on the type of nano- or macro-structure formed but also on the properties of biomaterials, such as the types of interaction, encapsulation, non-covalent interaction, or covalent interaction, which are ultimately useful for applications in drug delivery.

Mass spectrometry of membrane protein complexes

Membrane proteins are key players in the cell. Due to their hydrophobic nature they require solubilising agents such as detergents or membrane mimetics during purification and, consequently, are challenging targets in structural biology. In addition, their natural lipid environment is crucial for their structure and function further hampering their analysis. Alternative approaches are therefore required when the analysis by conventional techniques proves difficult. In this review, we highlight the broad application of mass spectrometry (MS) for the characterisation of membrane proteins and their interactions with lipids. We show that MS unambiguously identifies the protein and lipid components of membrane protein complexes, unravels their three-dimensional arrangements and further provides clues of protein-lipid interactions.

Recommendations for reporting ion mobility Mass Spectrometry measurements

Here we present a guide to ion mobility mass spectrometry experiments, which covers both linear and nonlinear methods: what is measured, how the measurements are done, and how to report the results, including the uncertainties of mobility and collision cross section values. The guide aims to clarify some possibly confusing concepts, and the reporting recommendations should help researchers, authors and reviewers to contribute comprehensive reports, so that the ion mobility data can be reused more confidently. Starting from the concept of the definition of the measurand, we emphasize that (i) mobility values (K0 ) depend intrinsically on ion structure, the nature of the bath gas, temperature, and E/N; (ii) ion mobility does not measure molecular surfaces directly, but collision cross section (CCS) values are derived from mobility values using a physical model; (iii) methods relying on calibration are empirical (and thus may provide method-dependent results) only if the gas nature, temperature or E/N cannot match those of the primary method. Our analysis highlights the urgency of a community effort toward establishing primary standards and reference materials for ion mobility, and provides recommendations to do so. © 2019 The Authors. Mass Spectrometry Reviews Published by Wiley Periodicals, Inc.

Modeling Protein Complexes Using Restraints from Crosslinking Mass Spectrometry

Modeling macromolecular assemblies with restraints from crosslinking mass spectrometry (XL-MS) tends to focus solely on distance violation. Recently, we identified three different modeling features inherent in crosslink data: (1) expected distance between crosslinked residues; (2) violation of the crosslinker's maximum bound; and (3) solvent accessibility of crosslinked residues. Here, we implement these features in a scoring function. cMNXL, and demonstrate that it outperforms the commonlyused crosslink distance violation. We compare the different methods of calculating the distance between crosslinked residues, which shows no significant change in performance when using Euclidean distance compared with the solvent-accessible surface distance. Finally, we create a combined score that incorporates information from 3D electron microscopy maps as well as crosslinking. This achieves, on average, better results than either information type alone and demonstrates the potential of integrative modeling with XL-MS and low-resolution cryoelectron microscopy.

Mass spectrometry beyond the native state

Native mass spectrometry allows the study of proteins by probing in vacuum the interactions they form in solution. It is a uniquely useful approach for structural biology and biophysics due to the high resolution of separation it affords, allowing the concomitant interrogation of multiple protein components with high mass accuracy. At its most basic, native mass spectrometry reports the mass of intact proteins and the assemblies they form in solution. However, the opportunities for more detailed characterisation are extensive, enabled by the exquisite control of ion motion that is possible in vacuum. Here we describe recent developments in mass spectrometry approaches to the structural interrogation of proteins both in, and beyond, their native state.

Integrative modelling of cellular assemblies

A wide variety of experimental techniques can be used for understanding the precise molecular mechanisms underlying the activities of cellular assemblies. The inherent limitations of a single experimental technique often requires integration of data from complementary approaches to gain sufficient insights into the assembly structure and function. Here, we review popular computational approaches for integrative modelling of cellular assemblies, including protein complexes and genomic assemblies. We provide recent examples of integrative models generated for such assemblies by different experimental techniques, especially including data from 3D electron microscopy (3D-EM) and chromosome conformation capture experiments, respectively. We highlight general concepts in integrative modelling and discuss the need for careful formulation and merging of different types of information.

Use of evolutionary information in the fitting of atomic level protein models in low resolution cryo-EM map of a protein assembly improves the accuracy of the fitting

Protein-protein interface residues, especially those at the core of the interface, exhibit higher conservation than residues in solvent exposed regions. Here, we explore the ability of this differential conservation to evaluate fittings of atomic models in low-resolution cryo-EM maps and select models from the ensemble of solutions that are often proposed by different model fitting techniques. As a prelude, using a non-redundant and high-resolution structural dataset involving 125 permanent and 95 transient complexes, we confirm that core interface residues are conserved significantly better than nearby non-interface residues and this result is used in the cryo-EM map analysis. From the analysis of inter-component interfaces in a set of fitted models associated with low-resolution cryo-EM maps of ribosomes, chaperones and proteasomes we note that a few poorly conserved residues occur at interfaces. Interestingly a few conserved residues are not in the interface, though they are close to the interface. These observations raise the potential requirement of refitting the models in the cryo-EM maps. We show that sampling an ensemble of models and selection of models with high residue conservation at the interface and in good agreement with the density helps in improving the accuracy of the fit. This study indicates that evolutionary information can serve as an additional input to improve and validate fitting of atomic models in cryo-EM density maps.

Refinement of atomic models in high resolution EM reconstructions using Flex-EM and local assessment

As the resolutions of Three Dimensional Electron Microscopic reconstructions of biological macromolecules are being improved, there is a need for better fitting and refinement methods at high resolutions and robust approaches for model assessment. Flex-EM/MODELLER has been used for flexible fitting of atomic models in intermediate-to-low resolution density maps of different biological systems. Here, we demonstrate the suitability of the method to successfully refine structures at higher resolutions (2.5-4.5Å) using both simulated and experimental data, including a newly processed map of Apo-GroEL. A hierarchical refinement protocol was adopted where the rigid body definitions are relaxed and atom displacement steps are reduced progressively at successive stages of refinement. For the assessment of local fit, we used the SMOC (segment-based Manders' overlap coefficient) score, while the model quality was checked using the Qmean score. Comparison of SMOC profiles at different stages of refinement helped in detecting regions that are poorly fitted. We also show how initial model errors can have significant impact on the goodness-of-fit. Finally, we discuss the implementation of Flex-EM in the CCP-EM software suite.

Visualizing the Ensemble Structures of Protein Complexes Using Chemical Cross-Linking Coupled with Mass Spectrometry

Graphical Abstract

Abstract

Chemical cross-linking coupled with mass spectrometry (CXMS) identifies protein residues that are close in space, and has been increasingly used for modeling the structures of protein complexes. Here we show that a single structure is usually sufficient to account for the intermolecular cross-links identified for a stable complex with sub-µmol/L binding affinity. In contrast, we show that the distance between two cross-linked residues in the different subunits of a transient or fleeting complex may exceed the maximum length of the cross-linker used, and the cross-links cannot be fully accounted for with a unique complex structure. We further show that the seemingly incompatible cross-links identified with high confidence arise from alternative modes of protein-protein interactions. By converting the intermolecular cross-links to ambiguous distance restraints, we established a rigid-body simulated annealing refinement protocol to seek the minimum set of conformers collectively satisfying the CXMS data. Hence we demonstrate that CXMS allows the depiction of the ensemble structures of protein complexes and elucidates the interaction dynamics for transient and fleeting complexes.

Electronic supplementary material

The online version of this article (doi:10.1007/s41048-015-0015-y) contains supplementary material, which is available to authorized users.

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

An integrative approach combining ion mobility mass spectrometry, X-ray crystallography, and nuclear magnetic resonance spectroscopy to study the conformational dynamics of α1 -antitrypsin upon ligand binding

Native mass spectrometry (MS) methods permit the study of multiple protein species within solution equilibria, whereas ion mobility (IM)-MS can report on conformational behavior of specific states. We used IM-MS to study a conformationally labile protein (α1 -antitrypsin) that undergoes pathological polymerization in the context of point mutations. The folded, native state of the Z-variant remains highly polymerogenic in physiological conditions despite only minor thermodynamic destabilization relative to the wild-type variant. Various data implicate kinetic instability (conformational lability within a native state ensemble) as the basis of Z α1 -antitrypsin polymerogenicity. We show the ability of IM-MS to track such disease-relevant conformational behavior in detail by studying the effects of peptide binding on α1 -antitrypsin conformation and dynamics. IM-MS is, therefore, an ideal platform for the screening of compounds that result in therapeutically beneficial kinetic stabilization of native α1 -antitrypsin. Our findings are confirmed with high-resolution X-ray crystallographic and nuclear magnetic resonance spectroscopic studies of the same event, which together dissect structural changes from dynamic effects caused by peptide binding at a residue-specific level. IM-MS methods, therefore, have great potential for further study of biologically relevant thermodynamic and kinetic instability of proteins and provide rapid and multidimensional characterization of ligand interactions of therapeutic interest.

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.

DockStar: a novel ILP-based integrative method for structural modeling of multimolecular protein complexes

MOTIVATION

Atomic resolution modeling of large multimolecular assemblies is a key task in Structural Cell Biology. Experimental techniques can provide atomic resolution structures of single proteins and small complexes, or low resolution data of large multimolecular complexes.

RESULTS

We present a novel integrative computational modeling method, which integrates both low and high resolution experimental data. The algorithm accepts as input atomic resolution structures of the individual subunits obtained from X-ray, NMR or homology modeling, and interaction data between the subunits obtained from mass spectrometry. The optimal assembly of the individual subunits is formulated as an Integer Linear Programming task. The method was tested on several representative complexes, both in the bound and unbound cases. It placed correctly most of the subunits of multimolecular complexes of up to 16 subunits and significantly outperformed the CombDock and Haddock multimolecular docking methods.

AVAILABILITY AND IMPLEMENTATION

http://bioinfo3d.cs.tau.ac.il/DockStar

CONTACT

naamaamir@mail.tau.ac.il or wolfson@tau.ac.il

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

The importance of dynamics in integrative modeling of supramolecular assemblies

Revealing the atomistic architecture of supramolecular complexes is a fundamental step toward a deeper understanding of cellular functioning. To date, this formidable task is facilitated by an emerging array of integrative modeling approaches that combine experimental data from different sources. One major challenge these methods have to face is the treatment of the dynamic rearrangements of the individual subunits upon assembly. While this flexibility can be sampled at different levels, integrating native dynamic determinants with available experimental inputs can provide an effective way to reveal the molecular recognition mechanisms at the basis of supramolecular assembly.

Native mass spectrometry: towards high-throughput structural proteomics

Native mass spectrometry (MS) has become a sensitive method for structural proteomics, allowing practitioners to gain insight into protein self-assembly, including stoichiometry and three-dimensional architecture, as well as complementary thermodynamic and kinetic aspects. Although MS is typically performed in vacuum, a body of literature has described how native solution-state structure is largely retained on the timescale of the experiment. Native MS offers the benefit that it requires substantially smaller quantities of a sample than traditional structural techniques such as NMR and X-ray crystallography, and is therefore well suited to high-throughput studies. Here we first describe the native MS approach and outline the structural proteomic data that it can deliver. We then provide practical details of experiments to examine the structural and dynamic properties of protein assemblies, highlighting potential pitfalls as well as principles of best practice.

Mass spec studio for integrative structural biology

The integration of biophysical data from multiple sources is critical for developing accurate structural models of large multiprotein systems and their regulators. Mass spectrometry (MS) can be used to measure the insertion location for a wide range of topographically sensitive chemical probes, and such insertion data provide a rich, but disparate set of modeling restraints. We have developed a software platform that integrates the analysis of label-based MS and tandem MS (MS(2)) data with protein modeling activities (Mass Spec Studio). Analysis packages can mine any labeling data from any mass spectrometer in a proteomics-grade manner, and link labeling methods with data-directed protein interaction modeling using HADDOCK. Support is provided for hydrogen/deuterium exchange (HX) and covalent labeling chemistries, including novel acquisition strategies such as targeted HX-MS(2) and data-independent HX-MS(2). The latter permits the modeling of highly complex systems, which we demonstrate by the analysis of microtubule interactions.

Mass-selective soft-landing of protein assemblies with controlled landing energies

Selection and soft-landing of bionanoparticles in vacuum is potentially a preparative approach to separate heterogeneous mixtures for high-resolution structural study or to deposit homogeneous materials for nanotechnological applications. Soft-landing of intact protein assemblies however remains challenging, due to the difficulties of manipulating these heavy species in mass-selective devices and retaining their structure during the experiment. We have developed a tandem mass spectrometer with the capability for controlled ion soft-landing and ex situ visualization of the soft-landed particles by means of transmission electron microscopy. The deposition conditions can be controlled by adjusting the kinetic energies of the ions by applying accelerating or decelerating voltages to a set of ion-steering optics. To validate this approach, we have examined two cage-like protein complexes, GroEL and ferritin, and studied the effect of soft-landing conditions on the method's throughput and the preservation of protein structure. Separation, based on mass-to-charge ratio, of holo- and apo-ferritin complexes after electrospray ionization enabled us to soft-land independently the separated complexes on a grid suitable for downstream transmission electron microscopy analysis. Following negative staining, images of the soft-landed complexes reveal that their structural integrity is largely conserved, with the characteristic central cavity of apoferritin, and iron core of holoferritin, surviving the phase transition from liquid to gas, soft-landing, and dehydration in vacuum.