Assembling the pieces of macromolecular complexes: Hybrid structural biology approaches.

Proteomics 2015, 00, 1–12

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DOI 10.1002/pmic.201400507

REVIEW

Assembling the pieces of macromolecular complexes: Hybrid structural biology approaches Argyris Politis and Antoni J. Borysik Department of Chemistry, King’s College London, London, UK

Hybrid approaches in structural biology have gained considerable interest for uncovering the molecular architectures of large and transient biological systems. In particular, MS-based methods and structural electron microscopy can complement conventional tools, such as Xray crystallography and NMR spectroscopy. However, bringing together the data derived from diverse sources requires sophisticated methods that can efficiently deal with intrinsic ambiguities and heterogeneities of the vast amount of data available. Here, we highlight hybrid approaches for studying dynamic assemblies, such as transient soluble and integral membrane protein complexes. In this review, we emphasize the integration of the wide range of emerging MS-based methods, such as ion mobility, native MS, hydrogen–deuterium exchange MS and chemical cross-linking MS, with data acquired from cryo electron microscopy and X-ray crystallography and further provide a future outlook of hybrid structural biology approaches.

Received: October 31, 2014 Revised: January 26, 2015 Accepted: February 24, 2015

Keywords: Hybrid MS / Integrative modeling / Ion mobility MS / Systems biology

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Introduction

Most functional modules within the living cell consist of multimeric protein complexes organized into transient interaction networks [1]. Uncovering the structure and dynamics of proteins forming such networks is of critical importance for human health and disease [2]. However, the study of the 3D architectures and the dynamic interactions of many heterogeneous assemblies of proteins remain elusive by traditional structural biology methods [2]. Over the last decade hybrid approaches in structural biology, which combine information from multiple sources, have enabled insights into the structure of macromolecular assemblies with increasing size and complexity [3–6]. The high resolution structure of the nuclear pore complex [7, 8], the 26S proteasome [9–11], and the visualization of the dynamics of Gprotein-coupled receptors (GPCRs) [12] are some of the most impressive examples from hybrid approaches. Furthermore, sophisticated computational tools have been developed,

Correspondence: Dr. Argyris Politis, Department of Chemistry, King’s College London, 7 Trinity Street, London SE1 1DB, UK E-mail: [email protected] Abbreviations: ATD, arrival time distribution; CCS, collision cross-section; GPCR, G-protein-coupled receptor; HDX, hydrogen–deuterium exchange; IM, ion mobility; SAXS, smallangle X-ray scattering

C 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

allowing the integration of different types of data for structural interrogation of protein assembly structures [13–15]. MS has underpinned proteomics for many years, but recent advances in instrumentation and technology have placed it to act at the center of hybrid structural biology approaches [2, 4, 16–19]. MS is well-suited to study low abundance, heterogeneous, and transient protein complexes [4,20]. Aided by methodological developments, native MS can now be used to generate low-resolution structural information of macromolecular assemblies [21, 22]. Coupling ion mobility (IM) to MS provides additional topological information in the form of an orientationally averaged collision cross-section (CCS) [23–25]. Recently, IM-MS has been employed to establish the stability and topology of membrane-embedded proteins [24, 26, 27], to elucidate the subunit connectivity of the regularly interspaced short palindromic repeat (CRISPR) associated proteins complexes [28], to reveal a low resolution model of the 11-subunit clamp loader-SSB4 complex [29], and to assess the structural flexibility of intrinsically disordered proteins and proteins with inherent conformational flexibility [30–32]. While IM-MS has been used previously to propose structural models of proteins [18, 33, 34], it has only recently been assessed quantitatively as a tool for interrogating multisubunit architectures [11, 35]. Here, we summarize recent advances in hybrid approaches toward elucidating the structural dynamics of large protein Colour Online: See the article online to view Figs. 1–4 in colour.

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A. Politis and A. J. Borysik

complexes. We provide an overview of MS-based techniques commonly used for generation of structural information and highlight their integration into the hybrid structural biology toolkit. We further discuss advantages, pitfalls, and future directions of the hybrid approaches centered on the structural MS methods.

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Hybrid structural biology approach

Even though X-ray crystallography is the gold standard for solving the 3D structure of large complexes at atomic resolution, its application remains challenging for dynamic protein assemblies, where the component subunits can adopt numerous conformations or stoichiometries that give rise to modulations in protein function [2]. To bridge this gap, hybrid approaches in structural biology have recently emerged as an alternative method for characterizing such dynamic systems [11]. Underpinned by computational developments, these approaches can now be applied as a powerful tool for determining model-built structures of macromolecular complexes. One of the most exciting aspects of hybrid approaches is their ability to predict structural models for the most challenging of systems, such as protein complexes associated with cellular membranes [2]. The hybrid strategy begins with the acquisition of data (e.g., from experiments, databases, or physical and chemical laws) and their subsequent conversion into structural restraints for use by a scoring function. The scoring function, which should be weighted to reflect the relative confidence and contribution of the individual restraints, guides the model-building process. Finally, an evaluation process and subsequent analysis of the ensemble of models built, typically using statistical tools, determine the final solutions (Fig. 1) [7]. Structural representations of the individual proteins, determined either experimentally or modeled by homology, are used as an input for sampling the conformational space of the complexes. Results using an integrative strategy showed that by combining structural data from electron microscopy (EM), chemical cross-linking coupled to MS (CX-MS), X-ray crystallography, and proteomics, a static snapshot of the molecular architecture of the 26S proteasome could be obtained [10]. This study provided critical insights into the steps preceding the degradation of ubiquitylated substrates. However, it had not assessed the intrinsic flexibility governing the assembly and function of the proteasome complex [36]. Gaining information into the dynamic interactions between proteins within a protein assembly requires alternative experimental tools and methods.

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A hybrid MS-based strategy

Methods using structural MS to study protein–protein interactions include proteomic analyses, native MS, IM-MS, CXMS, and chemical-labeling approaches, such as hydrogen– C 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim


deuterium exchange (HDX) and hydroxyl radical footprinting. A recent excellent review summarizes the principles of the various methods as well as the expected outcomes [37]. Here, we are focused on the structural information derived by the various MS methods and how these data can be further combined with the molecular envelopes obtained from EM, or with atomic models of subdomains from X-ray crystallography and homology modelling. MS methods have recently gained much interest for hybrid structural biology approaches as they generally require low sample amounts (microgram) and exhibit high measuring speeds and tolerance for heterogeneous sample environments [11,20]. The synergy of various MS methods performed on the same sample allowed highly challenging biological systems to be visualized. This was exemplified in a recent study where four types of MS data, proteomics, native MS, IM-MS, and CX-MS were utilized as restraints to compute the structures of protein assemblies [11]. By developing a novel hybrid method, structural insights into the assembly mechanism of the proteasomal base complex were gained, demonstrating the ability of hybrid MS strategies to target transient protein complexes. The first and most crucial step of the MS-restrained structural method is the preparation of the sample and the subsequent performance of various MS experiments. Ideally these experiments should be performed on the same sample. This is important in order to eliminate ambiguities involved with heterogeneous samples and different expression environments. However, if this is not possible, advanced statistical analyses [38] (e.g., Bayesian analysis) may offer a way to take into account the different states of the sample [39]. Next, the MS data are encoded into modeling restraints offering complementary structural information spanning various levels of resolution and accuracy and are subsequently used by a scoring function. Assessing how to weight and optimally combine different experimental data within the scoring function is a critical step for maximizing the precision and accuracy of the structural predictions [39]. A weighted scoring function can then be used to build an ensemble of “good” scoring models that are further refined and analyzed using molecular simulations and statistical tools. A computational tool for modeling large protein complexes using data from hybrid MS-based methods is freely available online (https://github.com/apolitis/hybrid_ms_method).

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Structural restraints from MS-based data

The data derived from different MS-based methods can be encoded into structural restraints for subsequent modeling analysis. Here, we focus on the different kinds of structural information that can be offered by each method along with their respective strengths and limitations. www.proteomics-journal.com

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Figure 1. Workflow of the hybrid method for modeling the 3D architectures of protein complexes. The input information from various experiments are collected and subsequently encoded into structural restraints. These restraints in turn are utilized by a weighted scoring function for sampling the conformational space of protein complexes. The sampling algorithm brings together representations of the individual subunits to generate candidate solutions of the complex guided by the scoring function and a refinement step (e.g., molecular simulations). Ensemble analysis (e.g., clustering) determines the final solution(s).

4.1 Proteomics Structural proteomics deals with the large-scale characterization of proteome function and structure. Typical MS-based proteomics workflows involve the identification of protein subunits that comprise a particular protein complex. This usually involves affinity tagged purification followed by protein digestion and identification [5, 15, 45]. The aim of these workflows is not typically geared toward analysis of proteins complexes in the native state. Although, information on subunit copy number or overall structure is not normally revealed, recent advances in quantitative proteomics have directed significant efforts toward uncovering this information. However, the identity of protein complexes, their composition, and how this information is related to expression levels and external cues has revealed useful insights into the role of protein assemblies in biological processes [40, 41]. Top-down proteomics approaches are also gaining in popularity as a tool to probe the structures of proteins and macromolecular protein complexes [42–44]. As opposed to slow


heating methods, such as CID, namely electron transfer dissociation result in protein fragmentation rather than unfolding. These fragmentation patterns are showing promise in mapping the surfaces of protein complexes [42]. Although more work is required before these restraints can be incorporated into hybrid workflows.

4.2 Native MS Native MS is a cutting-edge method for measuring the molecular weight of multisubunit protein complexes obtained from samples in their native state. Recently, it has emerged as a key-technique for structural biology allowing large MegaDalton protein complexes to “fly” through the gas phase of a mass spectrometer. It provides greater structural insight than typical proteomics workflows by offering information of the copy number of individual protein subunits within complexes [4]. Native MS experiments yield the composition and stoichiometry of protein complexes, as well as identifying stable


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subcomplexes using gas or solution-phase disruption techniques [18,20,22,35]. In either scenario, the results can define pathways of subcomplexes, starting from the intact complex [12]. These disassembly pathways can be used as restraints for generating model-built that can be used to provide testable hypotheses of protein-structure relationship [29].

4.3 IM-MS IM is an emerging technique that is used to assess the size and shape of proteins. IM is frequently coupled with MS, allowing the separation of proteins based on the ability of ions to traverse a gas-filled chamber under the influence of a weak electric field. The mobility (K) of ions is inversely related to their CCS [45] that is directly related to the shape of an ion and can therefore be used to provide topological information on protein complexes [46–49]. IM-MS is gaining in popularity as a tool to assess the overall shape of protein complexes partly due to its recent commercialization through traveling wave ion mobility spectrometry TWIMS. The use of IM-MS restraints to interrogate structural models generated by computational methods has been recently emerged as a useful tool for structural modeling of protein complexes [25, 29,35]. IM-MS is therefore well-placed to play a central role in hybrid approaches since it benefits from the same advantages as native MS with regard to protein yield and complexity.

4.4 CX-MS CX-MS is a well-established biochemical method where two or more reactive amino acid residues (e.g., lysines) are linked covalently via a cross-linking reagent. Underpinned by significant advances in MS, both in instrumentation and methodology, these approaches are increasingly used to address important structural biology questions [50]. Data from CX-MS are used to specify distance restraints at resolutions ranging from residue to subunit levels [51]. This approach however is unable to offer quantitative information concerning the conformational flexibility and transient protein–protein interactions. Recently, a novel strategy termed as comparative crosslinking has been applied to probe conformational changes of proteins in response to stimuli [52, 53]. This strategy probes the relative intensities of peptides obtained from complexes in various states using isotopically labeled cross-linkers [53].

4.5 HDX-MS The exchange of labile protons for bulk deuterium is intimately coupled to protein dynamics. Amide proton HDX operates on experimentally tractable timescales of millisecond to days due to hydrogen bonding or solvent accessibility. The uptake of deuterium has an associated mass shift that can be measured accurately by MS. Through HDX the mass is C 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim


directly coupled to protein motion without the need for specialized linkers or other derivatization. Continuous labeling workflows are most commonly employed where proteins are saturated in excess deuterium following acidic quenching and digestion. Mass-shifted peptides can be interpreted as solvent exposed or dynamic regions. Unlike NMR, HDX-MS can easily tolerate protein masses of many hundreds of kilodalton. However, resolution is routinely limited to enzyme coverage against a backdrop of increasing back exchange. Overall, HDX-MS yields information about the structural flexibility of protein complexes [54] and as such can offer additional restraints that are orthogonal to those obtained by IM-MS or CX-MS. To date, valuable structural insights have been gained using HDX-MS as exemplified by the ATP-binding cassette transporter (BmrA) with the presence of a ligand, the HIV virus capsid [55], and by monitoring the recruitment of ␤-arrestin-1 by a GPCR [12].

4.6 Hydroxyl radical footprinting An alternative to HDX-MS, hydroxyl radical footprinting relies on the covalent labeling of certain residues in the presence of hydroxyl radicals. Following protein digestion and LC-MS, oxidized amino acids can be identified due to their concurrent mass shifts. Since the degree of oxidation is associated with solvent exposure, evident mass shifts can be interpreted in terms of protein structure. The key strength of hydroxyl radical footprinting is the irreversible nature of the label, as opposed to HDX when back exchange can hinder interpretation. However, in contrast to HDX the precise mechanism of reaction is less well understood. Overall, labeling by radical footprinting yields 10–30% total protein coverage impinging its degree of structural resolution compared with HDX, which provides a structural probe at each residue except proline.

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Integrating MS-based data with EM maps

EM is a well-placed technique for structural characterization of protein assemblies. Many different EM methods, namely electron crystallography, single-particle EM, and electron tomography are available. Single-particle EM, in particular, can be used with negative-stained or cryogenically frozen (cryoEM) samples; the latter is increasingly applied to study large assemblies and theoretically can reach atomic resolution [56]. The keen reader can find more information regarding the various EM strategies and their corresponding applications in many excellent reviews [57–60]. The EM experiments can generate molecular envelopes describing the overall shape of the assemblies. In the past, pseudoatomic models of large assemblies have been proposed by fitting crystal structures or homology models of the individual subunits into the molecular envelope of the assembly defined by EM [10, 61]. Results also showed that by www.proteomics-journal.com

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employing a “multifit” sampling strategy, individual protein subunits were fitted into the EM density map, thus making up the 3D assembly of complexes [10]. The map derived by EM can be used as a volume and/or shape restraint for assessing its goodness-of-fit with the model structures of the assembly. An open question in computational structural biology is the ability to perform flexible sampling. This will enable us to build candidate structures by taking into account the intrinsic motion of the individual proteins as they assemble into functional complexes. Apart from the search for the best fit to the experimental data, such a flexibility step can provide information concerning the stability and the conformational heterogeneity of the assemblies. A flexible fitting method for assessing the quality-of-fit of atomic structures into EM maps using molecular dynamics flexible fitting (MDFF) simulations has been developed and applied in many macromolecular complexes [62]. Various versions of MD simulations, depending on the studied system (membrane or soluble proteins; solution or gas phase) can also provide alternative means of flexibly sampling the conformational space of proteins. Continuing our discussion on dynamics, to date most of the hybrid tools available [14, 63, 64] and in particular those involve MS-based methods lack the capability to fully account for the intrinsic flexibility of proteins, thus constraining the structural predictions to rigid body models. Tools such as molecular simulations, which perform enhanced sampling of systems spanning different range of temperatures (e.g., replica-exchange MD), may offer a much-needed refinement step capable of assessing the flexibility of model structures while simultaneously assessing their structural stability over the course of time (Fig. 1). REMD simulations have been used to study the aggregation and folding growth of intermediate oligomeric species of the amyloidogenic peptide A␤ [65, 66]. In the context of MS methods in particular, this strategy has the potential to directly compare the predicted structural flexibility of a model structure with that observed experimentally by IM-MS and HDX-MS.

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Integrating MS-based data with small-angle X-ray scattering

SAXS measures the intensity of scattered light in a sample as a function of the scattering angle I(q). These measurements yield low-resolution (>1 nm) structural restraints along with additional information regarding sample homogeneity and size. Typical restraints obtained by SAXS are the radius of gyration (Rg), which relates to the mean-squared center of mass distances in a molecule; the paired distance distribution function P(r), which relates to the intensity of different scattering vectors; and the maximum scattering distance (Dmax ) [67]. The multidimensionality of SAXS restraints allows for the generation of more detailed molecular envelopes than those that can be obtained from other low-resolution methods, such as IM-MS, or hydrodynamic methods, such as dy C 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

namic light scattering, that are limited to providing restraints in a single dimension. This positions SAXS at the forefront of the low-resolution tools with regard to shape recognition [68,69]. Although IM-MS is arguably better suited for the analysis of structures within complex mixtures or polydispersity samples. Currently, there are very few examples of the synergistic use of SAXS and IM-MS [70]. The lack of complementary studies between these techniques probably reflects the current incompatibly of SAXS envelopes with the tools commonly used to predict theoretical CCS values. The combination of MS-based experiments and SAXS could follow conventional hybrid workflows where structures generated by MS are further refined based on their scoring with SAXS structures. SAXS-generated molecular envelopes could also be used to calculate theoretical omega (⍀) allowing for direct comparison with IM-MS data. Gas-phase SAXS has the potential to be a powerful structural tool and could exploit the ability of MS to interrogate complex samples if coupled to ESI [71]. Overall, the systematic integration of SAXS data with MS-based experiments results in another useful combination of techniques; their synergy can offer previously intractable information on structure and dynamics of the assemblies.

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Probing the structure and dynamics of transient protein complexes

Transient complexes are notorious targets for structural characterization typically hampered by low abundance of species, while the presence of heterogeneous populations impedes structural analyses using traditional tools. Native MS combined with computational modeling have so far allowed valuable insights into the structure and dynamics of such dynamic assemblies. The interrogation of virus capsid assembly using IM-MS and modeling is one of the most impressive examples of such efforts [33]. This study allowed the transient assembly intermediates of two human pathogens, namely hepatitis B virus and norovirus, to be structurally characterized. This study further proposed assembly pathways for the formation of virus capsid oligomers, suggesting sheet-like structures of the assembly intermediates. Benesch and coworkers performed an innovative study for determining the oligomeric structures of the polydisperse molecular chaperone ␣B-crystallin using restraints derived from IM-MS and NMR [34]. In this study, the best model structures consistent with the input data revealed a polyhedral architecture of ␣B-crystallin oligomeric species and further provided a rationale for their polydispersity. A further pioneering example of utilizing IM-MS methods for analyzing transient species was performed by Bowers and coworkers, who unraveled the dynamics of amyloid-forming peptide A␤ self-assembly [47]. This effort captured the conformational transition of early peptide oligomers from globular to fibrillar in agreement with steric zipper growth [72]. www.proteomics-journal.com

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The above examples highlighted the advances in MS approaches, aided by computational modeling. Their application offers the unprecedented opportunity to study the structure and dynamics of transient complexes and their assembly intermediates [11]. A generalized approach for interrogating large and transient assemblies was very recently illustrated by integrating MS-based methods with a state of the art modeling tool. This study, which combined multiple MS experiments, allowed structural characterization of the molecular architecture and the assembly pathways of the 19S proteasome [11]. The 26S proteasome lies at the executive end of the ubiquitin-proteasome pathway for the controlled degradation of intracellular proteins, the waste disposal system of the cell [36]. This multiprotein complex is composed of approximately 700 kDa 20S core particle and approximately 900 kDa 19S regulatory particle. The high-resolution structure of the former has been determined crystallographically, while the structure of the 19S remains elusive. Recent studies, based on integrative modeling strategies, have confidently suggested 3D structural models of the 26S proteasome [10, 11]. By exploiting data from native MS, bottom-up proteomics, CX-MS, and IM-MS within a novel computational approach, two intermediate modules preceding the formation of the proteasomal lid were identified (Fig. 2A), shedding novel light into the multistep assembly mechanism of the 19S [36]. Interestingly, experiments from lid affinity pulldowns suggested the presence of multiple proteasome-dedicated chaperones together with 19S subunits. Further MS experiments on pulldowns from Rpn14- and Nas6-tagged cells, enabled the intermediate subcomplexes formed between the identified chaperones and the 19S subunits to be probed. Computational integration of the available data allowed the 3D reconstruction of three intermediate complexes assembled prior to the formation of the proteasomal base (Fig. 2B). Overall this study showed that integrating data from different MS-based techniques into a computational workflow can enable insights into a highly dynamic biological process.

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Capturing the conformational states of flexible regions by combining ion mobility MS and gas-phase simulations

Protein complexes can occupy a range of conformational states depending on their functionality and nature. Capturing these conformational states has long been considered a bottleneck in structural biology. Recent advances in both experimentation and computation have enabled information on the conformational dynamics of protein complexes to be gained. However, how we proceed from a qualitative description of flexibility in the gas phase to a quantitative picture of the solution structures of flexible proteins by MS will require much work and a greater understanding of protein–ion structure and electrospray processes. C 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim


A recent study employing IM-MS and gas-phase MD simulations enabled assignment of flexible regions within a membrane-embedded rotor [73]. This novel approach allowed new light to be shed into the mechanistic details essential for the cooperativity and the regulation of the rotary ATPase nanomotor. Rotary ATPases are dynamic nanomachines responsible for biological energy conversion [74]. They can operate in two directions, either by producing ATP or to use the energy from ATP hydrolysis to pump protons across the membrane. Structurally they are composed of a transmembrane domain (V0 ) anchored to a membrane-embedded motor (ring) and a water-soluble head domain (V1 ) consisting of a central stator and peripheral stalks. By releasing gaseous ions of V-type ATPase into the drift tube of an IM mass spectrometer, enabled the arrival time distributions (ATDs) to be measured. Interestingly and rather unexpectedly, unimodal mobility distributions of varying widths were recorded for the intact ATPase and its subcomplexes. Within these distributions, sharp peaks indicate a single conformation, while broader peaks are consistent with multiple states. Therefore, IM-MS experiments not only allowed the capturing of conformational dynamics of ATPases within the times scale of these measurements, but also offered, using CCS calculations, a quantized measure of their flexibility. Combining this information with in vacuo MD simulations, which utilized the charge state information derived from MS experiments [75], enabled structural models of the ATPase flexible regions to be suggested (Fig. 3). The proposed models described the motion of the flexible ATPase regions and were consistent with the CCSs obtained from IM-MS experiments. These experiments were thus able to probe the copopulated states of ATPase (sub)complexes, which were subsequently visualized by the gas-phase molecular simulations (Fig. 3). Overall, the integration of IM-MS experiments with gasphase MD simulations, as exemplified with many other excellent studies [76–78], demonstrates the immense potential of combining experiments with computational approaches for better understanding the structural dynamics of protein complexes. In contrast to solution proteins, membrane proteins have many added challenges regarding expression levels, stability, and solubility [79]. These challenges are broad and span all methods, although MS has the advantage over other techniques of being suited to investigate low-yielding complexes [20]. A unique challenge for MS of membrane proteins however regards the higher energies required for analysis and consequently the potential for conformational rearrangements. The magnitude of these effects is variable and systemspecific and requires greater understanding of this fledgling method. A further excellent example of using hybrid MS technology for probing dynamic systems was demonstrated by Barran and coworkers [31]. In this work, the conformational spread of four immunoglobulins was captured by studying the broad ATDs using IM-MS. The results indicated enhanced flexibility of these antibodies when compared with similar-sized www.proteomics-journal.com


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Figure 2. Structural models and assembly pathways of the intact proteasomal lid and base. (A) 3D structural models of the intact lid and two of its subcomplexes were predicted by integrating their mass spectra with CCSs obtained from IM-MS and distance proximities identified from cross-linking experiments. (B) Structural models of the proteasome base and chaperone: base transient intermediates were modeled by combining native MS, IM-MS, and CX-MS experiments. Adapted from [11].

(mass) protein complexes. Interestingly, the ensemble of conformations adopted by such flexible complexes was probed by in vacuo MD simulations once again demonstrating the power of combining IM-MS measurements with molecular simulations.

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Hybrid strategies to study small molecules binding on target proteins

Over the last few years, the study of binding-induced dynamics of small molecules on target proteins has attracted considerable interest. Among the technologies that contribute to structural analyses of protein–ligand complexes, chemicallabeling techniques coupled with MS have enabled the study of conformational dynamics and interactions of both soluble and transmembrane assemblies [32]. These techniques can either target the protein backbone (HDX-MS) or the amino acid side chains (hydroxyl radical footprinting) and can therefore provide structural restraints in the form of solvent accessibility and structural fluctuations of protein complexes. Along with automated acquisition, HDX-MS is becoming C 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

established as a high-throughput method to investigate and quantify dynamic fluctuations in protein structure as a result of drug binding. In the context of hybrid structural biology, HDX-MS data can be incorporated into the scoring function, which measures how well the model structures fit the data, as structural restraints targeting the solvent accessibility of complexes. When restraints derived from labeling methods are combined with those obtained from IM-MS, they can markedly reduce the candidate models of protein–ligand complexes, thus improving the confidence of the corresponding structural predictions. In particular, IM coupled with MS has enabled calculation of CCSs and ATD widths of coexisting states within a sample. The former provides information on the overall assembly architecture [35], while the latter can be used to capture its conformational flexibility or multiple states that are not resolvable [31, 73]. Integrative approaches have recently emerged to play a key role in elucidating the structure and dynamics of protein– ligand complexes. By bringing together diverse information obtained from MS-based methods and molecular simulations, the binding sites and the associated dynamics of small molecules on target proteins can be confidently www.proteomics-journal.com

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Figure 3. Conformational flexibility of V-type ATPase from IM-MS experiments and MD simulations. (A) IM-MS spectra of the catalytic soluble head of Thermus thermophilus ATPase reveals conformational heterogeneity. The results were mirrored by MD simulations performed using the charge states observed from MS experiments. (B) Enhanced structural flexibility was assigned to the V0 CL12 transmembrane subcomplex using IM-MS. Normal mode analysis in conjunction with CCS measurements further established the angle of rotation of subunit I. (C) A complete structural model of the V-type ATPase was built by combining MS data with the molecular envelope obtained from EM experiments [83]. Adapted from [64].

predicted (Fig. 4). For instance, the structural dynamics of P-glycoprotein (P-gp), a low-specificity efflux pump, were probed by combining IM-MS and molecular modeling [80]. MS results further enabled monitoring the synergistic effects of binding of small molecules, such as nucleotides, drugs, and lipids, to P-gp. Interestingly, the differences in CCSs further revealed the coexistence of two interconverting conformations upon ligand binding of P-gp (inward and outward facing) [80]. MS-derived information together with MD simulations and molecular modeling analysis allowed the confident location of a cardiolipin in the inner cavity of the outward-facing P-gp conformation. A particularly challenging target for integrative structural biology is to elucidate the structure and conformational dynamics of GPCRs and their signaling assemblies. GPCRs are trimeric, seven transmembrane receptors, and in their inactive state are composed of two main components, the G␣ bound to GDP and the G␤␥. Activation of GPCRs allows the release of GDP and the newly formed G␣-GTP subunit is freed triggering a cascade of signaling events [81]. The GPCRs are responsible for the majority of transmembrane signal transduction and as such play a critical role in many human diseases, namely diabetes, depression, and cardiovascular defects. These receptors are targeted by half of all modern drugs, yet the dynamic structural changes following ligand binding are largely unknown. Despite intense efforts, the number of solved structures represents only approximately 4% of the pharmacologically relevant GPCRs [82]. Therefore, there is a C 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

pressing need to screen model-generated structures (e.g., homology modeling, hybrid models) against different ligands. A recent study that employed EM, HDX-MS, chemical cross-linking, and molecular modeling enabled valuable insights into the architecture of the functional human b2AR in complex with b-arrestin 1 ([12]). This study enabled novel mechanistic details to be gained on the engagement of the GPCR by the arrestin, thus demonstrating how the combination of multiple disciplines can improve our understanding of the functional roles and dynamical interactions of this immensely important class of transmembrane receptors.

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Summary and future outlook

Recent advances in the wide range of structural biology techniques have generated a vast amount of data that hold great promise for characterizing currently unknown protein assemblies. The emergence of hybrid approaches represents a novel tool to bring together this diverse data and therefore to address the structure and flexibility of transient assemblies. Modeling restraints derived from MS-based methods are able to guide the efforts for enriching our structural knowledge toward large and heterogeneous complexes. These efforts are supported by both experimental developments and computational innovations. The former enables increasingly higher accuracy and resolution on the data acquired, while the latter ensures efficient computational data integration. www.proteomics-journal.com


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Figure 4. A workflow for probing the protein-ligand binding sites using a hybrid MS-based strategy. The data obtained from MS experiments and molecular simulations are encoded into restraints, which provide information about the binding dynamics, the flexibility, and structural stabilities of protein-ligand systems. This extracted structural information is then used to guide a sampling algorithm for generating candidate structural solutions through the use of a weighted scoring function. The workflow is exemplified on P-gp protein.

The future outlook of computational structural biology involves the integration of multiple types of data from diverse experiments. Toward this aim, HDX-MS and IM-MS are finding increasing success in applications with highly dynamic protein complexes. In particular, by combining MS-based techniques with cryo-EM and modeling analysis, we can assess structural information at atomic resolution. Embracing these techniques within a single approach will provide an immeasurably valuable tool for understanding the structural diversity of the cell.

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