Accommodating Protein Dynamics in the Modeling of Chemical Crosslinks

Energy Resolved Mass Spectrometry Data from Surfaced Induced Dissociation Improves Prediction of Protein Complex Structure

Native Mass Spectrometry (nMS) is a versatile technique for elucidating protein structure. Surface-Induced Dissociation (SID) is an activation method in tandem MS predominantly employed for determining protein complex stoichiometry alongside information about interface strengths. SID-nMS data can be collected over a range of acceleration energies, yielding Energy Resolved Mass Spectrometry (ERMS) data. Previous work demonstrated that the onset and appearance energy from SID-nMS can be used in integrative computational and experimental modeling to guide multimeric structure determination in some cases. However, the appearance energy is a single data point, while the ERMS data provide a full pattern of interface breakage. We hypothesized that incorporation of ERMS data into multimeric protein structure prediction would significantly outperform appearance energy. To test this hypothesis, we generated models of 20 protein complexes with RosettaDock using subunits generated from AlphaFold2. We simulated the ERMS data for each predicted model and rescored based on its agreement to experimental ERMS data. We demonstrated that more accurately predicted models exhibited simulated ERMS data in better agreement with the experimental data. As part of our ERMS-based rescoring, we matched or improved the RMSD of the best scoring model compared to Rosetta in 16 out of 20 cases, with 4 out of 20 cases improving to become a highly accurate (below 5 Å) structure. Finally, we benchmarked our method against our previously published appearance energy-based rescoring and showed improvement in 14 out of 20 cases, with 6 out of 20 becoming a highly accurate (below 5 Å) model. Our method is freely available through Rosetta Commons, with a usage tutorial and test files provided in the Supporting Information.

Mass Spectrometry Structural Proteomics Enabled by Limited Proteolysis and Cross-Linking

The exploration of protein structure and function stands at the forefront of life science and represents an ever-expanding focus in the development of proteomics. As mass spectrometry (MS) offers readout of protein conformational changes at both the protein and peptide levels, MS-based structural proteomics is making significant strides in the realms of structural and molecular biology, complementing traditional structural biology techniques. This review focuses on two powerful MS-based techniques for peptide-level readout, namely limited proteolysis-mass spectrometry (LiP-MS) and cross-linking mass spectrometry (XL-MS). First, we discuss the principles, features, and different workflows of these two methods. Subsequently, we delve into the bioinformatics strategies and software tools used for interpreting data associated with these protein conformation readouts and how the data can be integrated with other computational tools. Furthermore, we provide a comprehensive summary of the noteworthy applications of LiP-MS and XL-MS in diverse areas including neurodegenerative diseases, interactome studies, membrane proteins, and artificial intelligence-based structural analysis. Finally, we discuss the factors that modulate protein conformational changes. We also highlight the remaining challenges in understanding the intricacies of protein conformational changes by LiP-MS and XL-MS technologies.

A Tutorial Review of Labeling Methods in Mass Spectrometry-Based Quantitative Proteomics

Recent advancements in mass spectrometry (MS) have revolutionized quantitative proteomics, with multiplex isotope labeling emerging as a key strategy for enhancing accuracy, precision, and throughput. This tutorial review offers a comprehensive overview of multiplex isotope labeling techniques, including precursor-based, mass defect-based, reporter ion-based, and hybrid labeling methods. It details their fundamental principles, advantages, and inherent limitations along with strategies to mitigate the limitation of ratio-distortion. This review will also cover the applications and latest progress in these labeling techniques across various domains, including cancer biomarker discovery, neuroproteomics, post-translational modification analysis, cross-linking MS, and single-cell proteomics. This Review aims to provide guidance for researchers on selecting appropriate methods for their specific goals while also highlighting the potential future directions in this rapidly evolving field.

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.

Application of Multiple Length Cross-linkers to the Characterization of Gaseous Protein Structure

The speed, sensitivity, and tolerance of heterogeneity, as well as the kinetic trapping of solution-like states during electrospray, make native mass spectrometry an attractive method to study protein structure. Increases in the resolution of ion mobility measurements and in mass resolving power and range are leading to the increase of the information content of intact protein measurements and an expanded role of mass spectrometry in structural biology. Herein, a suite of different length noncovalent (sulfonate to positively charged side chain) cross-linkers was introduced via gas-phase ion/ion chemistry and used to determine distance restraints of kinetically trapped gas-phase structures of native-like cytochrome c ions. Electron capture dissociation allowed for the identification of cross-linked sites. Different length linkers resulted in distinct pairs of side chains being linked, supporting the ability of gas-phase cross-linking to be structurally specific. The gas-phase lengths of the cross-linkers were determined by conformational searches and density functional theory, allowing for the interpretation of the cross-links as distance restraints. These distance restraints were used to model gas-phase structures with molecular dynamics simulations, revealing a mixture of structures with similar overall shape/size but distinct features, thereby illustrating the kinetic trapping of multiple native-like solution structures in the gas phase.

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.

Biobox: a toolbox for biomolecular modelling

MOTIVATION

The implementation of biomolecular modelling methods and analyses can be cumbersome, often carried out with in-house software reimplementing common tasks, and requiring the integration of diverse software libraries.

RESULTS

We present Biobox, a Python-based toolbox facilitating the implementation of biomolecular modelling methods.

AVAILABILITY AND IMPLEMENTATION

Biobox is freely available on https://github.com/degiacom/biobox, along with its API and interactive Jupyter notebook tutorials.

Protein Structure Prediction with Mass Spectrometry Data

Knowledge of protein structure is crucial to our understanding of biological function and is routinely used in drug discovery. High-resolution techniques to determine the three-dimensional atomic coordinates of proteins are available. However, such methods are frequently limited by experimental challenges such as sample quantity, target size, and efficiency. Structural mass spectrometry (MS) is a technique in which structural features of proteins are elucidated quickly and relatively easily. Computational techniques that convert sparse MS data into protein models that demonstrate agreement with the data are needed. This review features cutting-edge computational methods that predict protein structure from MS data such as chemical cross-linking, hydrogen-deuterium exchange, hydroxyl radical protein footprinting, limited proteolysis, ion mobility, and surface-induced dissociation. Additionally, we address future directions for protein structure prediction with sparse MS data. Expected final online publication date for the Annual Review of Physical Chemistry, Volume 73 is April 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Reconstruction of Three-Dimensional Conformations of Bacterial ClpB from High-Speed Atomic-Force-Microscopy Images

ClpB belongs to the cellular disaggretase machinery involved in rescuing misfolded or aggregated proteins during heat or other cellular shocks. The function of this protein relies on the interconversion between different conformations in its native condition. A recent high-speed-atomic-force-microscopy (HS-AFM) experiment on ClpB from Thermus thermophilus shows four predominant conformational classes, namely, open, closed, spiral, and half-spiral. Analyses of AFM images provide only partial structural information regarding the molecular surface, and thus computational modeling of three-dimensional (3D) structures of these conformations should help interpret dynamical events related to ClpB functions. In this study, we reconstruct 3D models of ClpB from HS-AFM images in different conformational classes. We have applied our recently developed computational method based on a low-resolution representation of 3D structure using a Gaussian mixture model, combined with a Monte-Carlo sampling algorithm to optimize the agreement with target AFM images. After conformational sampling, we obtained models that reflect conformational variety embedded within the AFM images. From these reconstructed 3D models, we described, in terms of relative domain arrangement, the different types of ClpB oligomeric conformations observed by HS-AFM experiments. In particular, we highlighted the slippage of the monomeric components around the seam. This study demonstrates that such details of information, necessary for annotating the different conformational states involved in the ClpB function, can be obtained by combining HS-AFM images, even with limited resolution, and computational modeling.

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.

crisscrosslinkeR: identification and visualization of protein–RNA and protein–protein interactions from crosslinking mass spectrometry

Summary

Unbiased detection of protein–protein and protein–RNA interactions within ribonucleoprotein complexes are enabled through crosslinking followed by mass spectrometry. Yet, different methods detect different types of molecular interactions and therefore require the usage of different software packages with limited compatibility. We present crisscrosslinkeR, an R package that maps both protein–protein and protein–RNA interactions detected by different types of approaches for crosslinking with mass spectrometry. crisscrosslinkeR produces output files that are compatible with visualization using popular software packages for the generation of publication-quality figures.

Availability and implementation

crisscrosslinkeR is a free and open-source package, available through GitHub: github.com/egmg726/crisscrosslinker.

Supplementary information

Supplementary data are available at Bioinformatics online.

Structural Proteomics Methods to Interrogate the Conformations and Dynamics of Intrinsically Disordered Proteins

Intrinsically disordered proteins (IDPs) and regions of intrinsic disorder (IDRs) are abundant in proteomes and are essential for many biological processes. Thus, they are often implicated in disease mechanisms, including neurodegeneration and cancer. The flexible nature of IDPs and IDRs provides many advantages, including (but not limited to) overcoming steric restrictions in binding, facilitating posttranslational modifications, and achieving high binding specificity with low affinity. IDPs adopt a heterogeneous structural ensemble, in contrast to typical folded proteins, making it challenging to interrogate their structure using conventional tools. Structural mass spectrometry (MS) methods are playing an increasingly important role in characterizing the structure and function of IDPs and IDRs, enabled by advances in the design of instrumentation and the development of new workflows, including in native MS, ion mobility MS, top-down MS, hydrogen-deuterium exchange MS, crosslinking MS, and covalent labeling. Here, we describe the advantages of these methods that make them ideal to study IDPs and highlight recent applications where these tools have underpinned new insights into IDP structure and function that would be difficult to elucidate using other methods.

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.

Cleavable Cross-Linkers and Mass Spectrometry for the Ultimate Task of Profiling Protein-Protein Interaction Networks in Vivo

Cross-linking mass spectrometry (XL-MS) has matured into a potent tool to identify protein-protein interactions or to uncover protein structures in living cells, tissues, or organelles. The unique ability to investigate the interplay of proteins within their native environment delivers valuable complementary information to other advanced structural biology techniques. This Review gives a comprehensive overview of the current possible applications as well as the remaining limitations of the technique, focusing on cross-linking in highly complex biological systems like cells, organelles, or tissues. Thanks to the commercial availability of most reagents and advances in user-friendly data analysis, validation, and visualization tools, studies using XL-MS can, in theory, now also be utilized by nonexpert laboratories.

A hydrophobic ratchet entrenches molecular complexes

Most proteins assemble into multisubunit complexes1. The persistence of these complexes across evolutionary time is usually explained as the result of natural selection for functional properties that depend on multimerization, such as intersubunit allostery or the capacity to do mechanical work2. In many complexes, however, multimerization does not enable any known function3. An alternative explanation is that multimers could become entrenched if substitutions accumulate that are neutral in multimers but deleterious in monomers; purifying selection would then prevent reversion to the unassembled form, even if assembly per se does not enhance biological function3-7. Here we show that a hydrophobic mutational ratchet systematically entrenches molecular complexes. By applying ancestral protein reconstruction and biochemical assays to the evolution of steroid hormone receptors, we show that an ancient hydrophobic interface, conserved for hundreds of millions of years, is entrenched because exposure of this interface to solvent reduces protein stability and causes aggregation, even though the interface makes no detectable contribution to function. Using structural bioinformatics, we show that a universal mutational propensity drives sites that are buried in multimeric interfaces to accumulate hydrophobic substitutions to levels that are not tolerated in monomers. In a database of hundreds of families of multimers, most show signatures of long-term hydrophobic entrenchment. It is therefore likely that many protein complexes persist because a simple ratchet-like mechanism entrenches them across evolutionary time, even when they are functionally gratuitous.

The CroCo cross-link converter: a user-centred tool to convert results from cross-linking mass spectrometry experiments

MOTIVATION

A variety of search engines exists for the identification of peptide spectrum matches after cross-linking mass spectrometry experiments. The resulting diversity in output formats complicates data validation and visualization as well as exchange with collaborators, particularly from other research areas.

RESULTS

Here, we present CroCo, a user-friendly standalone executable to convert cross-linking results to a comprehensive spreadsheet format. Using this format, CroCo can be employed to generate input files for a selection of the commonly utilized validation and visualization tools.

AVAILABILITY AND IMPLEMENTATION

The source-code is freely available under a GNU general public license at https://github.com/cschmidtlab/croco. The standalone executable is available and documented at https://cschmidtlab.github.io/CroCo.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

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.

PyXlinkViewer: A flexible tool for visualization of protein chemical crosslinking data within the PyMOL molecular graphics system

Chemical crosslinking‐mass spectrometry (XL‐MS) is a valuable technique for gaining insights into protein structure and the organization of macromolecular complexes. XL‐MS data yield inter‐residue restraints that can be compared with high‐resolution structural data. Distances greater than the crosslinker spacer‐arm can reveal lowly populated “excited” states of proteins/protein assemblies, or crosslinks can be used as restraints to generate structural models in the absence of structural data. Despite increasing uptake of XL‐MS, there are few tools to enable rapid and facile mapping of XL‐MS data onto high‐resolution structures or structural models. PyXlinkViewer is a user‐friendly plugin for PyMOL v2 that maps intra‐protein, inter‐protein, and dead‐end crosslinks onto protein structures/models and automates the calculation of inter‐residue distances for the detected crosslinks. This enables rapid visualization of XL‐MS data, assessment of whether a set of detected crosslinks is congruent with structural data, and easy production of high‐quality images for publication.

The Conformational Preference of Chemical Cross-linkers Determines the Cross-linking Probability of Reactive Protein Residues

Chemical cross-linking mass spectrometry (XLMS) is an emerging technique in structural biology. Providing the cross-linked peptides are identified by mass spectrometry with high confidence, a distance restraint can be applied between the two reactive protein residues, with the upper bound corresponding to the maximal span of the cross-linker. However, as the upper bound is typically over 20 Å, cross-link distance restraints are unrestrictive and provide a marginal improvement in protein structural refinement. Here we analyze the experimental cross-links for lysine or acidic residues and show that the distribution of Cβ-Cβ' distances can be described with two overlapping Gaussian species. In addition to the pairwise occurrence probability of the reactive protein residues, we show that the distribution profile of the cross-link distances is determined by the intrinsic conformational propensity of the cross-linker. The cross-linker prefers either a compact or extended conformation and, once attached to a reactive protein residue, predominantly an extended conformation. Consequently, the long-distance Gaussian species occurs at a much higher probability than the short-distance species in the observed cross-links. Together, the probabilistic distribution of the cross-link distance allows the construction of a more restrictive restraint for structural modeling and better use of the XLMS data.

Inter-domain dynamics in the chaperone SurA and multi-site binding to its outer membrane protein clients

The periplasmic chaperone SurA plays a key role in outer membrane protein (OMP) biogenesis. E. coli SurA comprises a core domain and two peptidylprolyl isomerase domains (P1 and P2), but its mechanisms of client binding and chaperone function have remained unclear. Here, we use chemical cross-linking, hydrogen-deuterium exchange mass spectrometry, single-molecule FRET and molecular dynamics simulations to map the client binding site(s) on SurA and interrogate the role of conformational dynamics in OMP recognition. We demonstrate that SurA samples an array of conformations in solution in which P2 primarily lies closer to the core/P1 domains than suggested in the SurA crystal structure. OMP binding sites are located primarily in the core domain, and OMP binding results in conformational changes between the core/P1 domains. Together, the results suggest that unfolded OMP substrates bind in a cradle formed between the SurA domains, with structural flexibility between domains assisting OMP recognition, binding and release.

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.

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.

Jwalk and MNXL web server: model validation using restraints from crosslinking mass spectrometry

Motivation

Crosslinking Mass Spectrometry generates restraints that can be used to model proteins and protein complexes. Previously, we have developed two methods, to help users achieve better modelling performance from their crosslinking restraints: Jwalk, to estimate solvent accessible distances between crosslinked residues and MNXL, to assess the quality of the models based on these distances.

Results

Here, we present the Jwalk and MNXL webservers, which streamline the process of validating monomeric protein models using restraints from crosslinks. We demonstrate this by using the MNXL server to filter models made of varying quality, selecting the most native-like.

Availability and implementation

The webserver and source code are freely available from jwalk.ismb.lon.ac.uk and mnxl.ismb.lon.ac.uk.

Supplementary information

Supplementary data are available at Bioinformatics online.

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.

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.

Optimization Workflow for the Analysis of Cross-Linked Peptides Using a Quadrupole Time-of-Flight Mass Spectrometer

Cross-linking mass spectrometry is an emerging structural biology technique. Almost exclusively, the analyzer of choice for such an experiment has been the Orbitrap. We present an optimized protocol for the use of a Synapt G2-Si for the analysis of cross-linked peptides. We first tested six different energy ramps and analyzed the fragmentation behavior of cross-linked peptides identified by xQuest. By combining the most successful energy ramps, cross-link yield can be increased by up to 40%. When compared to previously published Orbitrap data, the Synapt G2-Si also offers improved fragmentation of the β peptide. In order to improve cross-link quality control we have also developed ValidateXL, a programmatic solution that works with existing cross-linking software to improve cross-link quality control.

TopoLink: evaluation of structural models using chemical crosslinking distance constraints

Summary

A software was developed to evaluate structural models using chemical crosslinking experiments. The user provides the types of linkers used and their reactivity, and the observed crosslinks and dead-ends. The software computes the minimum length of a physically inspired linker that connects the reactive atoms of interest, and reports the consistency of each distance with the experimental observation. Statistics on model consistency with the links are provided. Tools to evaluate the correlation of crosslinks in ensembles of models were developed. TopoLink was used to evaluate the potential crosslinks of all structures of the CATH database. The number of crosslinks expected as a function of protein size and linker length can be used as guide for experimental design.

Availability and implementation

TopoLink is available as free software at http://m3g.iqm.unicamp.br/topolink, and distributed as source code with a user-friendly graphical interface for Windows. A web server is also provided.

Supplementary information

Supplementary data are available at Bioinformatics online.

Statistical force-field for structural modeling using chemical cross-linking/mass spectrometry distance constraints

Motivation

Chemical cross-linking/mass spectrometry (XLMS) is an experimental method to obtain distance constraints between amino acid residues which can be applied to structural modeling of tertiary and quaternary biomolecular structures. These constraints provide, in principle, only upper limits to the distance between amino acid residues along the surface of the biomolecule. In practice, attempts to use of XLMS constraints for tertiary protein structure determination have not been widely successful. This indicates the need of specifically designed strategies for the representation of these constraints within modeling algorithms.

Results

A force-field designed to represent XLMS-derived constraints is proposed. The potential energy functions are obtained by computing, in the database of known protein structures, the probability of satisfaction of a topological cross-linking distance as a function of the Euclidean distance between amino acid residues. First, the strategy suggests that XL constraints should be set to shorter distances than usually assumed. Second, the complete statistical force-field improves the models obtained and can be easily incorporated into current modeling methods and software. The force-field was implemented and is distributed to be used within the Rosetta ab initio relax protocol.

Availability and implementation

Force-field parameters and usage instructions are freely available online (http://m3g.iqm.unicamp.br/topolink/xlff).

Supplementary information

Supplementary data are available at Bioinformatics online.

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.

Protein Tertiary Structure by Crosslinking/Mass Spectrometry

Observing the structures of proteins within the cell and tracking structural changes under different cellular conditions are the ultimate challenges for structural biology. This, however, requires an experimental technique that can generate sufficient data for structure determination and is applicable in the native environment of proteins. Crosslinking/mass spectrometry (CLMS) and protein structure determination have recently advanced to meet these requirements and crosslinking-driven de novo structure determination in native environments is now possible. In this opinion article, we highlight recent successes in the field of CLMS with protein structure modeling and challenges it still holds.

The earliest structural studies on proteins using crosslinking/mass spectrometry aimed to elucidate their tertiary three-dimensional structure.

Tertiary structure modeling using crosslinking fell out of favor for almost two decades because crosslink data were not informative to aid structure modeling.

Two game-changing trends emerged: using short-range crosslinkers that capture relevant modeling information and high-density crosslinking.

High-density crosslinking uses unspecific crosslinkers to dramatically increase crosslink numbers.

In addition, computational structure modeling methods made significant progress in exploiting CLMS data.

The combination of high-density crosslinking and computational structure modeling enables the elucidation of tertiary protein structure in native environments.

This sidesteps the key limitation of today’s structure determination methods, which are unable (except for a few, specialized methods) to probe the structure of proteins in cell lysates or even intact cells.