Modeling Protein Complexes Using Restraints from Crosslinking Mass Spectrometry

Modeling Flexible Protein Structure With AlphaFold2 and Crosslinking Mass Spectrometry

We propose a pipeline that combines AlphaFold2 (AF2) and crosslinking mass spectrometry (XL-MS) to model the structure of proteins with multiple conformations. The pipeline consists of two main steps: ensemble generation using AF2 and conformer selection using XL-MS data. For conformer selection, we developed two scores-the monolink probability score (MP) and the crosslink probability score (XLP)-both of which are based on residue depth from the protein surface. We benchmarked MP and XLP on a large dataset of decoy protein structures and showed that our scores outperform previously developed scores. We then tested our methodology on three proteins having an open and closed conformation in the Protein Data Bank: Complement component 3 (C3), luciferase, and glutamine-binding periplasmic protein, first generating ensembles using AF2, which were then screened for the open and closed conformations using experimental XL-MS data. In five out of six cases, the most accurate model within the AF2 ensembles-or a conformation within 1 Å of this model-was identified using crosslinks, as assessed through the XLP score. In the remaining case, only the monolinks (assessed through the MP score) successfully identified the open conformation of glutamine-binding periplasmic protein, and these results were further improved by including the "occupancy" of the monolinks. This serves as a compelling proof-of-concept for the effectiveness of monolinks. In contrast, the AF2 assessment score was only able to identify the most accurate conformation in two out of six cases. Our results highlight the complementarity of AF2 with experimental methods like XL-MS, with the MP and XLP scores providing reliable metrics to assess the quality of the predicted models. The MP and XLP scoring functions mentioned above are available at https://gitlab.com/topf-lab/xlms-tools.

Assessment of Two Restraint Potentials for Coarse-Grained Chemical-Cross-Link-Assisted Modeling of Protein Structures

The influence of distance restraints from chemical cross-link mass spectroscopy (XL-MS) on the quality of protein structures modeled with the coarse-grained UNRES force field was assessed by using a protocol based on multiplexed replica exchange molecular dynamics, in which both simulated and experimental cross-link restraints were employed, for 23 small proteins. Six cross-links with upper distance boundaries from 4 Å to 12 Å (azido benzoic acid succinimide (ABAS), triazidotriazine (TATA), succinimidyldiazirine (SDA), disuccinimidyl adipate (DSA), disuccinimidyl glutarate (DSG), and disuccinimidyl suberate (BS3)) and two types of restraining potentials ((i) simple flat-bottom Lorentz-like potentials dependent on side chain distance (all cross-links) and (ii) distance- and orientation-dependent potentials determined based on molecular dynamics simulations of model systems (DSA, DSG, BS3, and SDA)) were considered. The Lorentz-like potentials with properly set parameters were found to produce a greater number of higher-quality models compared to unrestrained simulations than the MD-based potentials, because the latter can force too long distances between side chains. Therefore, the flat-bottom Lorentz-like potentials are recommended to represent cross-link restraints. It was also found that significant improvement of model quality upon the introduction of cross-link restraints is obtained when the sum of differences of indices of cross-linked residues exceeds 150.

Mapping interactions of calmodulin and neuronal NO synthase by crosslinking and mass spectrometry

Neuronal nitric oxide synthase (nNOS) is a homodimeric cytochrome P450-like enzyme that catalyzes the conversion of L-arginine to nitric oxide in the presence of NADPH and molecular oxygen. The binding of calmodulin (CaM) to a linker region between the FAD/FMN-containing reductase domain, and the heme-containing oxygenase domain is needed for electron transfer reactions, reduction of the heme, and NO synthesis. Due to the dynamic nature of the reductase domain and low resolution of available full-length structures, the exact conformation of the CaM-bound active complex during heme reduction is still unresolved. Interestingly, hydrogen-deuterium exchange and mass spectrometry studies revealed interactions of the FMN domain and CaM with the oxygenase domain for iNOS, but not nNOS. This finding prompted us to utilize covalent crosslinking and mass spectrometry to clarify interactions of CaM with nNOS. Specifically, MS-cleavable bifunctional crosslinker disuccinimidyl dibutyric urea was used to identify thirteen unique crosslinks between CaM and nNOS as well as 61 crosslinks within the nNOS. The crosslinks provided evidence for CaM interaction with the oxygenase and reductase domain residues as well as interactions of the FMN domain with the oxygenase dimer. Cryo-EM studies, which gave a high-resolution model of the oxygenase domain, along with crosslink-guided docking provided a model of nNOS that brings the FMN within 15 Å of the heme in support for a more compact conformation than previously observed. These studies also point to the utility of covalent crosslinking and mass spectrometry in capturing transient dynamic conformations that may not be captured by hydrogen-deuterium exchange and mass spectrometry experiments.

Rational Prediction of PROTAC-Compatible Protein-Protein Interfaces by Molecular Docking

Proteolysis targeting chimeras (PROTACs) are heterobifunctional ligands that mediate the interaction between a protein target and an E3 ligase, resulting in a ternary complex, whose interaction with the ubiquitination machinery leads to target degradation. This technology is emerging as an exciting new avenue for therapeutic development, with several PROTACs currently undergoing clinical trials targeting cancer. Here, we describe a general and computationally efficient methodology combining restraint-based docking, energy-based rescoring, and a filter based on the minimal solvent-accessible surface distance to produce PROTAC-compatible PPIs suitable for when there is no a priori known PROTAC ligand. In a benchmark employing a manually curated data set of 13 ternary complex crystals, we achieved an accuracy of 92% when starting from bound structures and 77% when starting from unbound structures, respectively. Our method only requires that the ligand-bound structures of the monomeric forms of the E3 ligase and target proteins be given to run, making it general, accurate, and highly efficient, with the ability to impact early-stage PROTAC-based drug design campaigns where no structural information about the ternary complex structure is available.

Higher-Order Structural Organization of the Mitochondrial Proteome Charted by In Situ Cross-Linking Mass Spectrometry

Mitochondria are densely packed with proteins, of which most are involved physically or more transiently in protein-protein interactions (PPIs). Mitochondria host among others all enzymes of the Krebs cycle and the oxidative phosphorylation pathway and are foremost associated with cellular bioenergetics. However, mitochondria are also important contributors to apoptotic cell death and contain their own genome indicating that they play additionally an eminent role in processes beyond bioenergetics. Despite intense efforts in identifying and characterizing mitochondrial protein complexes by structural biology and proteomics techniques, many PPIs have remained elusive. Several of these (membrane embedded) PPIs are less stable in vitro hampering their characterization by most contemporary methods in structural biology. Particularly in these cases, cross-linking mass spectrometry (XL-MS) has proven valuable for the in-depth characterization of mitochondrial protein complexes in situ. Here, we highlight experimental strategies for the analysis of proteome-wide PPIs in mitochondria using XL-MS. We showcase the ability of in situ XL-MS as a tool to map suborganelle interactions and topologies and aid in refining structural models of protein complexes. We describe some of the most recent technological advances in XL-MS that may benefit the in situ characterization of PPIs even further, especially when combined with electron microscopy and structural modeling.

Cross-validation of distance measurements in proteins by PELDOR/DEER and single-molecule FRET

Pulsed electron-electron double resonance spectroscopy (PELDOR/DEER) and single-molecule Förster resonance energy transfer spectroscopy (smFRET) are frequently used to determine conformational changes, structural heterogeneity, and inter probe distances in biological macromolecules. They provide qualitative information that facilitates mechanistic understanding of biochemical processes and quantitative data for structural modelling. To provide a comprehensive comparison of the accuracy of PELDOR/DEER and smFRET, we use a library of double cysteine variants of four proteins that undergo large-scale conformational changes upon ligand binding. With either method, we use established standard experimental protocols and data analysis routines to determine inter-probe distances in the presence and absence of ligands. The results are compared to distance predictions from structural models. Despite an overall satisfying and similar distance accuracy, some inconsistencies are identified, which we attribute to the use of cryoprotectants for PELDOR/DEER and label-protein interactions for smFRET. This large-scale cross-validation of PELDOR/DEER and smFRET highlights the strengths, weaknesses, and synergies of these two important and complementary tools in integrative structural biology.

Characterization of protein complexes in extracellular vesicles by intact extracellular vesicle crosslinking mass spectrometry (iEVXL)

Extracellular vesicles (EVs) are blood‐borne messengers that coordinate signalling between different tissues and organs in the body. The specificity of such crosstalk is determined by preferential EV docking to target sites, as mediated through protein‐protein interactions. As such, the need to structurally characterize the EV surface precedes further understanding of docking selectivity and recipient‐cell uptake mechanisms. Here, we describe an intact extracellular vesicle crosslinking mass spectrometry (iEVXL) method that can be applied for structural characterization of protein complexes in EVs. By using a partially membrane‐permeable disuccinimidyl suberate crosslinker, proteins on the EV outer‐surface and inside EVs can be immobilized together with their interacting partners. This not only provides covalent stabilization of protein complexes before extraction from the membrane‐enclosed environment, but also generates a set of crosslinking distance restraints that can be used for structural modelling and comparative screening of changes in EV protein assemblies. Here we demonstrate iEVXL as a powerful approach to reveal high‐resolution information, about protein determinants that govern EV docking and signalling, and as a crucial aid in modelling docking interactions.

Proteomic Approaches to Unravel Mechanisms of Antibiotic Resistance and Immune Evasion of Bacterial Pathogens

The profound effects of and distress caused by the global COVID-19 pandemic highlighted what has been known in the health sciences a long time ago: that bacteria, fungi, viruses, and parasites continue to present a major threat to human health. Infectious diseases remain the leading cause of death worldwide, with antibiotic resistance increasing exponentially due to a lack of new treatments. In addition to this, many pathogens share the common trait of having the ability to modulate, and escape from, the host immune response. The challenge in medical microbiology is to develop and apply new experimental approaches that allow for the identification of both the microbe and its drug susceptibility profile in a time-sensitive manner, as well as to elucidate their molecular mechanisms of survival and immunomodulation. Over the last three decades, proteomics has contributed to a better understanding of the underlying molecular mechanisms responsible for microbial drug resistance and pathogenicity. Proteomics has gained new momentum as a result of recent advances in mass spectrometry. Indeed, mass spectrometry-based biomedical research has been made possible thanks to technological advances in instrumentation capability and the continuous improvement of sample processing and workflows. For example, high-throughput applications such as SWATH or Trapped ion mobility enable the identification of thousands of proteins in a matter of minutes. This type of rapid, in-depth analysis, combined with other advanced, supportive applications such as data processing and artificial intelligence, presents a unique opportunity to translate knowledge-based findings into measurable impacts like new antimicrobial biomarkers and drug targets. In relation to the Research Topic “Proteomic Approaches to Unravel Mechanisms of Resistance and Immune Evasion of Bacterial Pathogens,” this review specifically seeks to highlight the synergies between the powerful fields of modern proteomics and microbiology, as well as bridging translational opportunities from biomedical research to clinical practice.

Shape shifting: The multiple conformational substates of the PTEN N-terminal PIP2 -binding domain

The Phosphatase and TENsin homolog deleted on chromosome 10 (PTEN) is a chief regulator of a variety of cellular processes including cell proliferation, migration, growth, and death. It is also a major tumor suppressor gene that is frequently mutated or lost under cancerous conditions. PTEN encodes a dual-specificity (lipid and protein) phosphatase that negatively regulates the PI3K/AKT/mTOR signaling pathway where the PIP2 -binding domain (PBD) regulates the lipid phosphatase function. Unfortunately, despite two decades of research, a full-length structure of PTEN remains elusive, leaving open questions regarding PTEN's disordered regions that mediate protein stability, post-translational modifications, protein-protein interactions, while also hindering the design of small molecules that can regulate PTEN's function. Here, we utilized a combination of crosslinking mass spectrometry, in silico predicted structural modeling (including AlphaFold2), molecular docking, molecular dynamics simulations, and residue interaction network modeling to obtain structural details and molecular insight into the behavior of the PBD of PTEN. Our study shows that the PBD exists in multiple conformations which suggests its ability to regulate PTEN's variety of functions. Studying how these specific conformational substates contribute to PTEN function is imperative to defining its function in disease pathogenesis, and to delineate ways to modulate its tumor suppressor activity.

Label-free visual proteomics: Coupling MS- and EM-based approaches in structural biology

Combining diverse experimental structural and interactomic methods allows for the construction of comprehensible molecular encyclopedias of biological systems. Typically, this involves merging several independent approaches that provide complementary structural and functional information from multiple perspectives and at different resolution ranges. A particularly potent combination lies in coupling structural information from cryoelectron microscopy or tomography (cryo-EM or cryo-ET) with interactomic and structural information from mass spectrometry (MS)-based structural proteomics. Cryo-EM/ET allows for sub-nanometer visualization of biological specimens in purified and near-native states, while MS provides bioanalytical information for proteins and protein complexes without introducing additional labels. Here we highlight recent achievements in protein structure and interactome determination using cryo-EM/ET that benefit from additional MS analysis. We also give our perspective on how combining cryo-EM/ET and MS will continue bridging gaps between molecular and cellular studies by capturing and describing 3D snapshots of proteomes and interactomes.

Leveraging crosslinking mass spectrometry in structural and cell biology

Crosslinking mass spectrometry (crosslinking-MS) is a versatile tool providing structural insights into protein conformation and protein-protein interactions. Its medium-resolution residue-residue distance restraints have been used to validate protein structures proposed by other methods and have helped derive models of protein complexes by integrative structural biology approaches. The use of crosslinking-MS in integrative approaches is underpinned by progress in estimating error rates in crosslinking-MS data and in combining these data with other information. The flexible and high-throughput nature of crosslinking-MS has allowed it to complement the ongoing resolution revolution in electron microscopy by providing system-wide residue-residue distance restraints, especially for flexible regions or systems. Here, we review how crosslinking-MS information has been leveraged in structural model validation and integrative modeling. Crosslinking-MS has also been a key technology for cell biology studies and structural systems biology where, in conjunction with cryoelectron tomography, it can provide structural and mechanistic insights directly in situ.

Cross-Linking Mass Spectrometry for Investigating Protein Conformations and Protein-Protein Interactions─A Method for All Seasons

Mass spectrometry (MS) has become one of the key technologies of structural biology. In this review, the contributions of chemical cross-linking combined with mass spectrometry (XL-MS) for studying three-dimensional structures of proteins and for investigating protein-protein interactions are outlined. We summarize the most important cross-linking reagents, software tools, and XL-MS workflows and highlight prominent examples for characterizing proteins, their assemblies, and interaction networks in vitro and in vivo. Computational modeling plays a crucial role in deriving 3D-structural information from XL-MS data. Integrating XL-MS with other techniques of structural biology, such as cryo-electron microscopy, has been successful in addressing biological questions that to date could not be answered. XL-MS is therefore expected to play an increasingly important role in structural biology in the future.

Integration of Mass Spectrometry Data for Structural Biology

Mass spectrometry (MS) is increasingly being used to probe the structure and dynamics of proteins and the complexes they form with other macromolecules. There are now several specialized MS methods, each with unique sample preparation, data acquisition, and data processing protocols. Collectively, these methods are referred to as structural MS and include cross-linking, hydrogen-deuterium exchange, hydroxyl radical footprinting, native, ion mobility, and top-down MS. Each of these provides a unique type of structural information, ranging from composition and stoichiometry through to residue level proximity and solvent accessibility. Structural MS has proved particularly beneficial in studying protein classes for which analysis by classic structural biology techniques proves challenging such as glycosylated or intrinsically disordered proteins. To capture the structural details for a particular system, especially larger multiprotein complexes, more than one structural MS method with other structural and biophysical techniques is often required. Key to integrating these diverse data are computational strategies and software solutions to facilitate this process. We provide a background to the structural MS methods and briefly summarize other structural methods and how these are combined with MS. We then describe current state of the art approaches for the integration of structural MS data for structural biology. We quantify how often these methods are used together and provide examples where such combinations have been fruitful. To illustrate the power of integrative approaches, we discuss progress in solving the structures of the proteasome and the nuclear pore complex. We also discuss how information from structural MS, particularly pertaining to protein dynamics, is not currently utilized in integrative workflows and how such information can provide a more accurate picture of the systems studied. We conclude by discussing new developments in the MS and computational fields that will further enable in-cell structural studies.

IMProv: A Resource for Cross-link-Driven Structure Modeling that Accommodates Protein Dynamics

Proteomics methodology has expanded to include protein structural analysis, primarily through cross-linking mass spectrometry (XL-MS) and hydrogen-deuterium exchange mass spectrometry (HX-MS). However, while the structural proteomics community has effective tools for primary data analysis, there is a need for structure modeling pipelines that are accessible to the proteomics specialist. Integrative structural biology requires the aggregation of multiple distinct types of data to generate models that satisfy all inputs. Here, we describe IMProv, an app in the Mass Spec Studio that combines XL-MS data with other structural data, such as cryo-EM densities and crystallographic structures, for integrative structure modeling on high-performance computing platforms. The resource provides an easily deployed bundle that includes the open-source Integrative Modeling Platform program (IMP) and its dependencies. IMProv also provides functionality to adjust cross-link distance restraints according to the underlying dynamics of cross-linked sites, as characterized by HX-MS. A dynamics-driven conditioning of restraint values can improve structure modeling precision, as illustrated by an integrative structure of the five-membered Polycomb Repressive Complex 2. IMProv is extensible to additional types of data.

Pseudopotentials for coarse-grained cross-link-assisted modeling of protein structures

Pseudopotentials for the chemical cross-links comprising the glutamic- and aspartic-acid side chains bridged with adipic- (ADH) or pimelic-acid hydrazide (PDH), and the lysine side chains bridged with glutaric (BS² G) or suberic acid (BS³ ) for coarse-grained cross-link-assisted simulations were determined by canonical molecular dynamics with the Amber14sb force field. The potentials depend on the distance between side-chain ends and on side-chain orientation, this preventing from making cross-link contacts across the globule in simulations. The potentials were implemented in the UNRES coarse-grained force field and their effect on the quality of models was assessed with 11 monomeric and 1 dimeric proteins, using synthetic or experimental cross-link data. Simulations with the new potentials resulted in improvement of the generated models compared to unrestrained simulations in more instances compared to those with the statistical potentials.

Top-Down and Bottom-Up Proteomics Methods to Study RNA Virus Biology

RNA viruses cause a wide range of human diseases that are associated with high mortality and morbidity. In the past decades, the rise of genetic-based screening methods and high-throughput sequencing approaches allowed the uncovering of unique and elusive aspects of RNA virus replication and pathogenesis at an unprecedented scale. However, viruses often hijack critical host functions or trigger pathological dysfunctions, perturbing cellular proteostasis, macromolecular complex organization or stoichiometry, and post-translational modifications. Such effects require the monitoring of proteins and proteoforms both on a global scale and at the structural level. Mass spectrometry (MS) has recently emerged as an important component of the RNA virus biology toolbox, with its potential to shed light on critical aspects of virus-host perturbations and streamline the identification of antiviral targets. Moreover, multiple novel MS tools are available to study the structure of large protein complexes, providing detailed information on the exact stoichiometry of cellular and viral protein complexes and critical mechanistic insights into their functions. Here, we review top-down and bottom-up mass spectrometry-based approaches in RNA virus biology with a special focus on the most recent developments in characterizing host responses, and their translational implications to identify novel tractable antiviral targets.

Selective cross-linking of coinciding protein assemblies by in-gel cross-linking mass spectrometry

Cross-linking mass spectrometry has developed into an important method to study protein structures and interactions. The in-solution cross-linking workflows involve time and sample consuming steps and do not provide sensible solutions for differentiating cross-links obtained from co-occurring protein oligomers, complexes, or conformers. Here we developed a cross-linking workflow combining blue native PAGE with in-gel cross-linking mass spectrometry (IGX-MS). This workflow circumvents steps, such as buffer exchange and cross-linker concentration optimization. Additionally, IGX-MS enables the parallel analysis of co-occurring protein complexes using only small amounts of sample. Another benefit of IGX-MS, demonstrated by experiments on GroEL and purified bovine heart mitochondria, is the substantial reduction of undesired over-length cross-links compared to in-solution cross-linking. We next used IGX-MS to investigate the complement components C5, C6, and their hetero-dimeric C5b6 complex. The obtained cross-links were used to generate a refined structural model of the complement component C6, resembling C6 in its inactivated state. This finding shows that IGX-MS can provide new insights into the initial stages of the terminal complement pathway.

Integrative Mass Spectrometry-Based Approaches for Modeling Macromolecular Assemblies

Mass spectrometry (MS)-based strategies have emerged as key elements for structural modeling of proteins and their assemblies. In particular, merging together complementary MS tools, through the so-called hybrid approaches, has enabled structural characterization of proteins in their near-native states. Here, we describe how different MS techniques, such as native MS, chemical cross-linking MS, and ion mobility MS, are brought together using sophisticated computational algorithms and modeling restraints. We demonstrate the applicability of the strategy by building accurate models of multimeric protein assemblies. These strategies can practically be applied to any protein complex of interest and be readily integrated with other structural approaches such as electron density maps from cryo-electron microscopy.

Tightening the Crosslinking Distance Restraints for Better Resolution of Protein Structure and Dynamics

Chemical crosslinking coupled with mass spectrometry (CXMS) has been increasingly used in structural biology. CXMS distance restraints are usually applied to Cα or Cβ atoms of the crosslinked residues, with upper bounds typically over 20 Å. The incorporation of loose CXMS restraints only marginally improves the resolution of the calculated structures. Here, we present a revised format of CXMS distance restraints, which works by first modifying the crosslinked residue with a rigid extension derived from the crosslinker. With the flexible side chain explicitly represented, the reformatted restraint can be applied to the modification group instead, with an upper bound of 6 Å or less. The short distance restraint can be represented and back-calculated simply with a straight line. The use of tighter restraints not only afford better-resolved structures but also uncover protein dynamics. Together, our approach enables more information extracted from the CXMS data.

Structural predictions of the functions of membrane proteins from HDX-MS

HDX-MS has emerged as a powerful tool to interrogate the structure and dynamics of proteins and their complexes. Recent advances in the methodology and instrumentation have enabled the application of HDX-MS to membrane proteins. Such targets are challenging to investigate with conventional strategies. Developing new tools are therefore pertinent for improving our fundamental knowledge of how membrane proteins function in the cell. Importantly, investigating this central class of biomolecules within their native lipid environment remains a challenge but also a key goal ahead. In this short review, we outline recent progresses in dissecting the conformational mechanisms of membrane proteins using HDX-MS. We further describe how the use of computational strategies can aid the interpretation of experimental data and enable visualisation of otherwise intractable membrane protein states. This unique integration of experiments with computations holds significant potential for future applications.

Probing Protein Interaction Networks by Combining MS-Based Proteomics and Structural Data Integration

Protein-protein interactions play a major role in the molecular machinery of life, and various techniques such as AP-MS are dedicated to their identification. However, those techniques return lists of proteins devoid of organizational structure, not detailing which proteins interact with which others. Proposing a hierarchical view of the interactions between the members of the flat list becomes highly tedious for large data sets when done by hand. To help hierarchize this data, we introduce a new bioinformatics protocol that integrates information of the multimeric protein 3D structures available in the Protein Data Bank using remote homology detection, as well as information related to Short Linear Motifs and interaction data from the BioGRID. We illustrate on two unrelated use-cases of different complexity how our approach can be useful to decipher the network of interactions hidden in the list of input proteins, and how it provides added value compared to state-of-the-art resources such as Interactome3D or STRING. Particularly, we show the added value of using homology detection to distinguish between orthologs and paralogs, and to distinguish between core obligate and more facultative interactions. We also demonstrate the potential of considering interactions occurring through Short Linear Motifs.

Principles for Integrative Structural Biology Studies

Integrative structure determination is a powerful approach to modeling the structures of biological systems based on data produced by multiple experimental and theoretical methods, with implications for our understanding of cellular biology and drug discovery. This Primer introduces the theory and methods of integrative approaches, emphasizing the kinds of data that can be effectively included in developing models and using the nuclear pore complex as an example to illustrate the practice and challenges involved. These guidelines are intended to aid the researcher in understanding and applying integrative structural methods to systems of their interest and thus take advantage of this rapidly evolving field.

Correlation between Labeling Yield and Surface Accessibility in Covalent Labeling Mass Spectrometry

The functional properties of a protein are strongly influenced by its topography, or the solvent-facing contour map of its surface. Together with crosslinking, covalent labeling mass spectrometry (CL-MS) has the potential to contribute topographical data through the measurement of surface accessibility. However, recent efforts to correlate measures of surface accessibility with labeling yield have been met with mixed success. Most applications of CL-MS involve differential analysis of protein interactions (i.e., footprinting experiments) where such inconsistencies have limited effect. Extending CL-MS into structural analysis requires an improved evaluation of the relationship between labeling and surface exposure. In this study, we applied recently developed diazirine reagents to obtain deep coverage of the large motor domain of Eg5 (a mitotic kinesin), and together with computational methods we correlated labeling yields with accessibility data in a number of ways. We observe that correlations can indeed be seen at a local structural level, but these correlations do not extend across the structure. The lack of correlation arises from the influence of protein dynamics and chemical composition on reagent partitioning and, thus, also on labeling yield. We conclude that our use of CL-MS data should be considered in light of "chemical accessibility" rather than "solvent accessibility" and suggest that CL-MS data would be a useful tool in the fundamental study of protein-solute interactions.

Quantitative Structural Interpretation of Protein Crosslinks

Chemical crosslinking, combined with mass spectrometry analysis, is a key source of information for characterizing the structure of large protein assemblies, in the context of molecular modeling. In most approaches, the interpretation is limited to simple spatial restraints, neglecting physico-chemical interactions between the crosslinker and the protein and their flexibility. Here we present a method, named NRGXL (new realistic grid for crosslinks), which models the flexibility of the crosslinker and the linked side-chains, by explicitly sampling many conformations. Also, the method can efficiently deal with overall protein dynamics. This method creates a physical model of the crosslinker and associated energy. A classifier based on it outperforms others, based on Euclidean distance or solvent-accessible distance and its efficiency makes it usable for validating 3D models from crosslinking data. NRGXL is freely available as a web server at: https://nrgxl.pasteur.fr.

Structural insights and activating mutations in diverse pathologies define mechanisms of deregulation for phospholipase C gamma enzymes

BACKGROUND

PLCγ enzymes are key nodes in cellular signal transduction and their mutated and rare variants have been recently implicated in development of a range of diseases with unmet need including cancer, complex immune disorders, inflammation and neurodegenerative diseases. However, molecular nature of activation and the impact and dysregulation mechanisms by mutations, remain unclear; both are critically dependent on comprehensive characterization of the intact PLCγ enzymes.

METHODS

For structural studies we applied cryo-EM, cross-linking mass spectrometry and hydrogen-deuterium exchange mass spectrometry. In parallel, we compiled mutations linked to main pathologies, established their distribution and assessed their impact in cells and in vitro.

FINDINGS

We define structure of a complex containing an intact, autoinhibited PLCγ1 and the intracellular part of FGFR1 and show that the interaction is centred on the nSH2 domain of PLCγ1. We define the architecture of PLCγ1 where an autoinhibitory interface involves the cSH2, spPH, TIM-barrel and C2 domains; this relative orientation occludes PLCγ1 access to its substrate. Based on this framework and functional characterization, the mechanism leading to an increase in PLCγ1 activity for the largest group of mutations is consistent with the major, direct impact on the autoinhibitory interface.

INTERPRETATION

We reveal features of PLCγ enzymes that are important for determining their activation status. Targeting such features, as an alternative to targeting the PLC active site that has so far not been achieved for any PLC, could provide new routes for clinical interventions related to various pathologies driven by PLCγ deregulation. FUND: CR UK, MRC and AstaZeneca.

Assessment of chemical-crosslink-assisted protein structure modeling in CASP13

With the advance of experimental procedures obtaining chemical crosslinking information is becoming a fast and routine practice. Information on crosslinks can greatly enhance the accuracy of protein structure modeling. Here, we review the current state of the art in modeling protein structures with the assistance of experimentally determined chemical crosslinks within the framework of the 13th meeting of Critical Assessment of Structure Prediction approaches. This largest-to-date blind assessment reveals benefits of using data assistance in difficult to model protein structure prediction cases. However, in a broader context, it also suggests that with the unprecedented advance in accuracy to predict contacts in recent years, experimental crosslinks will be useful only if their specificity and accuracy further improved and they are better integrated into computational workflows.

Proper evaluation of chemical cross-linking-based spatial restraints improves the precision of modeling homo-oligomeric protein complexes

Background

The function of oligomeric proteins is inherently linked to their quaternary structure. In the absence of high-resolution data, low-resolution information in the form of spatial restraints can significantly contribute to the precision and accuracy of structural models obtained using computational approaches. To obtain such restraints, chemical cross-linking coupled with mass spectrometry (XL-MS) is commonly used. However, the use of XL-MS in the modeling of protein complexes comprised of identical subunits (homo-oligomers) is often hindered by the inherent ambiguity of intra- and inter-subunit connection assignment.

Results

We present a comprehensive evaluation of (1) different methods for inter-residue distance calculations, and (2) different approaches for the scoring of spatial restraints. Our results show that using Solvent Accessible Surface distances (SASDs) instead of Euclidean distances (EUCs) greatly reduces the assignation ambiguity and delivers better modeling precision. Furthermore, ambiguous connections should be considered as inter-subunit only when the intra-subunit alternative exceeds the distance threshold. Modeling performance can also be improved if symmetry, characteristic for most homo-oligomers, is explicitly defined in the scoring function.

Conclusions

Our findings provide guidelines for proper evaluation of chemical cross-linking-based spatial restraints in modeling homo-oligomeric protein complexes, which could facilitate structural characterization of this important group of proteins.

Electronic supplementary material

The online version of this article (10.1186/s12859-019-3032-x) contains supplementary material, which is available to authorized users.

The Plasma Factor XIII Heterotetrameric Complex Structure: Unexpected Unequal Pairing within a Symmetric Complex

Factor XIII (FXIII) is a predominant determinant of clot stability, strength, and composition. Plasma FXIII circulates as a pro-transglutaminase with two catalytic A subunits and two carrier-protective B subunits in a heterotetramer (FXIII-A₂B₂). FXIII-A₂ and -B₂ subunits are synthesized separately and then assembled in plasma. Following proteolytic activation by thrombin and calcium-mediated dissociation of the B subunits, activated FXIII (FXIIIa) covalently cross links fibrin, promoting clot stability. The zymogen and active states of the FXIII-A subunits have been structurally characterized; however, the structure of FXIII-B subunits and the FXIII-A₂B₂ complex have remained elusive. Using integrative hybrid approaches including atomic force microscopy, cross-linking mass spectrometry, and computational approaches, we have constructed the first all-atom model of the FXIII-A₂B₂ complex. We also used molecular dynamics simulations in combination with isothermal titration calorimetry to characterize FXIII-A₂B₂ assembly, activation, and dissociation. Our data reveal unequal pairing of individual subunit monomers in an otherwise symmetric complex, and suggest this unusual structure is critical for both assembly and activation of this complex. Our findings enhance understanding of mechanisms associating FXIII-A₂B₂ mutations with disease and have important implications for the rational design of molecules to alter FXIII assembly or activity to reduce bleeding and thrombotic complications.

Development of R7BP inhibitors through cross-linking coupled mass spectrometry and integrated modeling

Protein-protein interaction (PPI) networks are known to be valuable targets for therapeutic intervention; yet the development of PPI modulators as next-generation drugs to target specific vertices, edges, and hubs has been impeded by the lack of structural information of many of the proteins and complexes involved. Building on recent advancements in cross-linking mass spectrometry (XL-MS), we describe an effective approach to obtain relevant structural data on R7BP, a master regulator of itch sensation, and its interfaces with other proteins in its network. This approach integrates XL-MS with a variety of modeling techniques to successfully develop antibody inhibitors of the R7BP and RGS7/Gβ5 duplex interaction. Binding and inhibitory efficiency are studied by surface plasmon resonance spectroscopy and through an R7BP-derived dominant negative construct. This approach may have broader applications as a tool to facilitate the development of PPI modulators in the absence of crystal structures or when structural information is limited.

α-Defensin HD5 Stabilizes Human Papillomavirus 16 Capsid/Core Interactions

Background:

Human papillomavirus (HPV) is linked to nearly all cases of cervical cancer. Despite available vaccines, a deeper understanding of the immune response to HPV is needed. Human α-defensin 5 (HD5), an innate immune effector peptide, blocks infection of multiple sero-types of HPV, including high-risk HPV16. While a common mechanism of α-defensin anti-viral activity against nonenveloped viruses such as HPV has emerged, there is limited understanding of how α-defensins bind to viral capsids to block infection.

Methods:

We have used cryo-electron microscopy (cryoEM), mass spectrometry (MS) crosslinking and differential lysine modification studies, and molecular dynamics (MD) simulations to probe the interaction of HPV16 pseudovirions (PsVs) with HD5.

Results:

CryoEM single particle reconstruction did not reveal HD5 density on the capsid surface. Rather, increased density was observed under the capsid shell in the presence of HD5. MS studies indicate that HD5 binds near the L1 and L2 capsid proteins and specifically near the C-terminal region of L1. MD simulations indicate that favorable electrostatic interactions can be formed between HD5 and the L1 C-terminal tail.

Conclusions:

A model is presented for how HD5 affects HPV16 structure and cell entry. In this model, HD5 binds to disordered regions of L1 and L2 protruding from the icosahedrally ordered capsid. HD5 acts to cement interactions between L1 and L2 and leads to a closer association of the L2/genome core with the L1 capsid. This model provides a structural rationale for our prior observation that HD5 interferes with the separation of L1 from the L2/genome complex during cell entry.

Graphical Abstract

Structural mass spectrometry goes viral

Over the last 20 years, mass spectrometry (MS), with its ability to analyze small sample amounts with high speed and sensitivity, has more and more entered the field of structural virology, aiming to investigate the structure and dynamics of viral proteins as close to their native environment as possible. The use of non-perturbing labels in hydrogen-deuterium exchange MS allows for the analysis of interactions between viral proteins and host cell factors as well as their dynamic responses to the environment. Cross-linking MS, on the other hand, can analyze interactions in viral protein complexes and identify virus-host interactions in cells. Native MS allows transferring viral proteins, complexes and capsids into the gas phase and has broken boundaries to overcome size limitations, so that now even the analysis of intact virions is possible. Different MS approaches not only inform about size, stability, interactions and dynamics of virus assemblies, but also bridge the gap to other biophysical techniques, providing valuable constraints for integrative structural modeling of viral complex assemblies that are often inaccessible by single technique approaches. In this review, recent advances are highlighted, clearly showing that structural MS approaches in virology are moving towards systems biology and ever more experiments are performed on cellular level.

Computational modeling of RNA 3D structure based on experimental data

RNA molecules are master regulators of cells. They are involved in a variety of molecular processes: they transmit genetic information, sense cellular signals and communicate responses, and even catalyze chemical reactions. As in the case of proteins, RNA function is dictated by its structure and by its ability to adopt different conformations, which in turn is encoded in the sequence. Experimental determination of high-resolution RNA structures is both laborious and difficult, and therefore the majority of known RNAs remain structurally uncharacterized. To address this problem, predictive computational methods were developed based on the accumulated knowledge of RNA structures determined so far, the physical basis of the RNA folding, and taking into account evolutionary considerations, such as conservation of functionally important motifs. However, all theoretical methods suffer from various limitations, and they are generally unable to accurately predict structures for RNA sequences longer than 100-nt residues unless aided by additional experimental data. In this article, we review experimental methods that can generate data usable by computational methods, as well as computational approaches for RNA structure prediction that can utilize data from experimental analyses. We outline methods and data types that can be potentially useful for RNA 3D structure modeling but are not commonly used by the existing software, suggesting directions for future development.

Weighing-up protein dynamics: the combination of native mass spectrometry and molecular dynamics simulations

Structural dynamics underpin biological function at the molecular level, yet many biophysical and structural biology approaches give only a static or averaged view of proteins. Native mass spectrometry yields spectra of the many states and interactions in the structural ensemble, but its spatial resolution is limited. Conversely, molecular dynamics simulations are innately high-resolution, but have a limited capacity for exploring all structural possibilities. The two techniques hence differ fundamentally in the information they provide, returning data that reflect different length scales and time scales, making them natural bedfellows. Here we discuss how the combination of native mass spectrometry with molecular dynamics simulations is enabling unprecedented insights into a range of biological questions by interrogating the motions of proteins, their assemblies, and interactions.

Role of Computational Methods in Going beyond X-ray Crystallography to Explore Protein Structure and Dynamics

Protein structural biology came a long way since the determination of the first three-dimensional structure of myoglobin about six decades ago. Across this period, X-ray crystallography was the most important experimental method for gaining atomic-resolution insight into protein structures. However, as the role of dynamics gained importance in the function of proteins, the limitations of X-ray crystallography in not being able to capture dynamics came to the forefront. Computational methods proved to be immensely successful in understanding protein dynamics in solution, and they continue to improve in terms of both the scale and the types of systems that can be studied. In this review, we briefly discuss the limitations of X-ray crystallography in studying protein dynamics, and then provide an overview of different computational methods that are instrumental in understanding the dynamics of proteins and biomacromolecular complexes.

Chemical cross-linking with mass spectrometry: a tool for systems structural biology

Biological processes supporting life are orchestrated by a highly dynamic array of protein structures and interactions comprising the interactome. Defining the interactome, visualizing how structures and interactions change and function to support life is essential to improved understanding of fundamental molecular processes, but represents a challenge unmet by any single analytical technique. Chemical cross-linking with mass spectrometry provides identification of proximal amino acid residues within proteins and protein complexes, yielding low resolution structural information. This approach has predominantly been employed to provide structural insight on isolated protein complexes, and has been particularly useful for molecules that are recalcitrant to conventional structural biology studies. Here we discuss recent developments in cross-linking and mass spectrometry technologies that are providing large-scale or systems-level interactome data with successful applications to isolated organelles, cell lysates, virus particles, intact bacterial and mammalian cultured cells and tissue samples.