Serum Albumin Domain Structures in Human Blood Serum by Mass Spectrometry and Computational Biology

Transient Cross-linking Mass Spectrometry: Taking Conformational Snapshots of Proteins

The dynamic nature of protein conformations is central to their biological functions. Conventional structural biology techniques provide static snapshots, whereas a comprehensive understanding requires an analysis of the dynamic conformations. In this study, we develop a transient cross-linking mass spectrometry method using a photo-cross-linker DCD. This cross-linker can be transiently activated to accomplish cross-linking, and with sample freezing, transient conformations are preserved, allowing temporal control and on-demand cross-linking. Its cross-linking site covers all amino acids, exhibiting diversity and providing rich structural information. Additionally, we develop a data-processing strategy by integrating a DCD-specific reporter ion and a defined ambiguous site annotation criterion, thereby ensuring the confidence in identification and cross-link site annotation. Thus, the developed transient cross-linking mass spectrometry, leveraging the distinctive features of DCD, has enabled us to analyze protein conformations and protein complexes with high resolution, take conformational snapshots, discern the coexistence of conformational intermediates, and decipher conformational fluctuations, shedding light on how proteins conformationally respond to biological signals and engage with interacting partners. Our results highlight DCD's potential for probing protein conformational changes, facilitating the elucidation of their pivotal roles within biological systems.

Utilizing Platinum(II)-Based Cross-Linker and Two-Stage Data Analysis Strategy to Investigate the Allosteric in Glycogen Phosphorylase

Cross-linking mass spectrometry (XL-MS) is widely used in the analysis of protein structure and protein-protein interactions (PPIs). Throughout the entire workflow, the utilization of cross-linkers and the interpretation of cross-linking data are the core steps. Cisplatin, as a well-known anticancer drug, has been previously demonstrated for its capability and advantages as a cross-linker. However, the complexity of platinum(II) cross-linked products and the lack of suitable software for data interpretation have hindered its further application. In this work, a two-stage data analysis strategy for platinum(II) cross-linked peptides has been developed and demonstrated on a pair of phosphorylation-induced allosteric systems, glycogen phosphorylase (GP) b and a. This two-stage data analysis strategy takes into account the identification of various types of Pt(II)-containing fragment ions and incorporates the unique isotope distribution properties of Pt(II)-based cross-linkers to eliminate false-positive data and achieve accurate identification of Pt(II)-based cross-linked peptides. The Pt(II)-based cross-linking results allow the capture of structural differences between GPb and GPa at the N-terminus and the tower-tower helices interface, which is consistent with the X-ray crystallography structure as well as our previous HDX-MS results. In addition, it also complements the structure of noncrystallizable regions. Finally, through discussion of existing data search engines and issues in spectral analysis of Pt(II)-based cross-linked peptides, we put forward proposals for follow-up software design, cross-linker developments, and guidance for the application of platinum(II)-based drugs. Overall, Pt(II)-based XL-MS can be a useful tool to complement both experimental and computational structural biology.

Advances in crosslinking chemistry and proximity-enabled strategies: deciphering protein complexes and interactions

Mass spectrometry, coupled with innovative crosslinking techniques to decode protein conformations and interactions through uninterrupted signal connections, has undergone remarkable progress in recent years. It is crucial to develop selective crosslinking reagents that minimally disrupt protein structure and dynamics, providing insights into protein network regulation and biological functions. Compared to traditional crosslinkers, new bifunctional chemical crosslinkers exhibit high selectivity and specificity in connecting proximal amino acid residues, resulting in stable molecular crosslinked products. The conjugation with specific amino acid residues like lysine, cysteine, arginine and tyrosine expands the XL-MS toolbox, enabling more precise modeling of target substrates and leading to improved data quality and reliability. Another emerging crosslinking method utilizes unnatural amino acids (UAAs) derived from proximity-enabled reactivity with specific amino acids or sulfur-fluoride exchange (SuFEx) reactions with nucleophilic residues. These UAAs are genetically encoded into proteins for the formation of specific covalent bonds. This technique combines the benefits of genetic encoding for live cell compatibility with chemical crosslinking, providing a valuable method for capturing transient and weak protein-protein interactions (PPIs) for mapping PPI coordinates and improving the pharmacological properties of proteins. With continued advancements in technology and applications, crosslinking mass spectrometry is poised to play an increasingly significant role in guiding our understanding of protein dynamics and function in the future.

Modelling protein complexes with crosslinking mass spectrometry and deep learning

Scarcity of structural and evolutionary information on protein complexes poses a challenge to deep learning-based structure modelling. We integrate experimental distance restraints obtained by crosslinking mass spectrometry (MS) into AlphaFold-Multimer, by extending AlphaLink to protein complexes. Integrating crosslinking MS data substantially improves modelling performance on challenging targets, by helping to identify interfaces, focusing sampling, and improving model selection. This extends to single crosslinks from whole-cell crosslinking MS, opening the possibility of whole-cell structural investigations driven by experimental data. We demonstrate this by revealing the molecular basis of iron homoeostasis in Bacillus subtilis.

Molecular mechanism of IKK catalytic dimer docking to NF-κB substrates

The inhibitor of κB (IκB) kinase (IKK) is a central regulator of NF-κB signaling. All IKK complexes contain hetero- or homodimers of the catalytic IKKβ and/or IKKα subunits. Here, we identify a YDDΦxΦ motif, which is conserved in substrates of canonical (IκBα, IκBβ) and alternative (p100) NF-κB pathways, and which mediates docking to catalytic IKK dimers. We demonstrate a quantitative correlation between docking affinity and IKK activity related to IκBα phosphorylation/degradation. Furthermore, we show that phosphorylation of the motif's conserved tyrosine, an event previously reported to promote IκBα accumulation and inhibition of NF-κB gene expression, suppresses the docking interaction. Results from integrated structural analyzes indicate that the motif binds to a groove at the IKK dimer interface. Consistently, suppression of IKK dimerization also abolishes IκBα substrate binding. Finally, we show that an optimized bivalent motif peptide inhibits NF-κB signaling. This work unveils a function for IKKα/β dimerization in substrate motif recognition.

Dissecting diazirine photo-reaction mechanism for protein residue-specific cross-linking and distance mapping

While photo-cross-linking (PXL) with alkyl diazirines can provide stringent distance restraints and offer insights into protein structures, unambiguous identification of cross-linked residues hinders data interpretation to the same level that has been achieved with chemical cross-linking (CXL). We address this challenge by developing an in-line system with systematic modulation of light intensity and irradiation time, which allows for a quantitative evaluation of diazirine photolysis and photo-reaction mechanism. Our results reveal a two-step pathway with mainly sequential generation of diazo and carbene intermediates. Diazo intermediate preferentially targets buried polar residues, many of which are inaccessible with known CXL probes for their limited reactivity. Moreover, we demonstrate that tuning light intensity and duration enhances selectivity towards polar residues by biasing diazo-mediated cross-linking reactions over carbene ones. This mechanistic dissection unlocks the full potential of PXL, paving the way for accurate distance mapping against protein structures and ultimately, unveiling protein dynamic behaviors.

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.

Protein structure prediction with in-cell photo-crosslinking mass spectrometry and deep learning

While AlphaFold2 can predict accurate protein structures from the primary sequence, challenges remain for proteins that undergo conformational changes or for which few homologous sequences are known. Here we introduce AlphaLink, a modified version of the AlphaFold2 algorithm that incorporates experimental distance restraint information into its network architecture. By employing sparse experimental contacts as anchor points, AlphaLink improves on the performance of AlphaFold2 in predicting challenging targets. We confirm this experimentally by using the noncanonical amino acid photo-leucine to obtain information on residue-residue contacts inside cells by crosslinking mass spectrometry. The program can predict distinct conformations of proteins on the basis of the distance restraints provided, demonstrating the value of experimental data in driving protein structure prediction. The noise-tolerant framework for integrating data in protein structure prediction presented here opens a path to accurate characterization of protein structures from in-cell data.

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.

A deep learning model for predicting optimal distance range in crosslinking mass spectrometry data

Macromolecular assemblies play an important role in all cellular processes. While there has recently been significant progress in protein structure prediction based on deep learning, large protein complexes cannot be predicted with these approaches. The integrative structure modeling approach characterizes multi-subunit complexes by computational integration of data from fast and accessible experimental techniques. Crosslinking mass spectrometry is one such technique that provides spatial information about the proximity of crosslinked residues. One of the challenges in interpreting crosslinking datasets is designing a scoring function that, given a structure, can quantify how well it fits the data. Most approaches set an upper bound on the distance between Cα atoms of crosslinked residues and calculate a fraction of satisfied crosslinks. However, the distance spanned by the crosslinker greatly depends on the neighborhood of the crosslinked residues. Here, we design a deep learning model for predicting the optimal distance range for a crosslinked residue pair based on the structures of their neighborhoods. We find that our model can predict the distance range with the area under the receiver-operator curve of 0.86 and 0.7 for intra- and inter-protein crosslinks, respectively. Our deep scoring function can be used in a range of structure modeling applications.

Improved Cross-Linking Coverage for Protein Complexes Containing Low Levels of Lysine by Using an Enrichable Photo-Cross-Linker

Chemical cross-linking coupled with mass spectrometry (XL-MS) is an important technique for the structural analysis of protein complexes where the coverage of amino acids and the identification of cross-linked sites are crucial. Photo-cross-linking has multisite reactivity and is valuable for the structural analysis of chemical cross-linking. However, a high degree of heterogeneity results from this multisite reactivity, which results in samples with higher complexity and lower abundance. Additionally, the applicability of photo-cross-linking is limited to purified protein complexes. In this work, we demonstrate a photo-cross-linker, alkynyl-succinimidyl-diazirine (ASD) with the reactive groups of N-hydroxysuccinimide ester and diazirine, as well as the click-enrichable alkyne group. Photo-cross-linkers can provide higher site reactivity for proteins that contain only a small number of lysine residues, thereby complementing the more commonly used lysine-targeting cross-linkers. By systematically analyzing proteins with differing lysine contents and differing flexibilities, we demonstrated clear enhancement in structure elucidation for proteins containing less lysine and with high flexibility. In addition, enrichment approaches of alkynyl-azide click chemistry conjugated with biotin-streptavidin purification (coinciding with parallel orthogonal digestion) improved the identification coverage of cross-links. We show that this photo-cross-linking approach can be used for membrane proteome-wide complex analysis. This method led to the identification of a total of 14066 lysine-X cross-linked site pairs from a total of 2784 proteins. Thus, this cross-linker is a valuable addition to a photo-cross-linking toolkit and improves the identification coverage of XL-MS in functional structure analysis.

Cross-linking mass spectrometry discovers, evaluates, and corroborates structures and protein-protein interactions in the human cell

Significant recent advances in structural biology, particularly in the field of cryoelectron microscopy, have dramatically expanded our ability to create structural models of proteins and protein complexes. However, many proteins remain refractory to these approaches because of their low abundance, low stability, or-in the case of complexes-simply not having yet been analyzed. Here, we demonstrate the power of using cross-linking mass spectrometry (XL-MS) for the high-throughput experimental assessment of the structures of proteins and protein complexes. This included those produced by high-resolution but in vitro experimental data, as well as in silico predictions based on amino acid sequence alone. We present the largest XL-MS dataset to date, describing 28,910 unique residue pairs captured across 4,084 unique human proteins and 2,110 unique protein-protein interactions. We show that models of proteins and their complexes predicted by AlphaFold2, and inspired and corroborated by the XL-MS data, offer opportunities to deeply mine the structural proteome and interactome and reveal mechanisms underlying protein structure and function.

Protein structure dynamics by crosslinking mass spectrometry

Crosslinking mass spectrometry captures protein structures in solution. The crosslinks reveal spatial proximities as distance restraints, but do not easily reveal which of these restraints derive from the same protein conformation. This superposition can be reduced by photo-crosslinking, and adding information from protein structure models, or quantitative crosslinking reveals conformation-specific crosslinks. As a consequence, crosslinking MS has proven useful already in the context of multiple dynamic protein systems. We foresee a breakthrough in the resolution and scale of studying protein dynamics when crosslinks are used to guide deep-learning-based protein modelling. Advances in crosslinking MS, such as photoactivatable crosslinking and in-situ crosslinking, will then reveal protein conformation dynamics in the cellular context, at a pseudo-atomic resolution, and plausibly in a time-resolved manner.

Characterizing Endogenous Protein Complexes with Biological Mass Spectrometry

Biological mass spectrometry (MS) encompasses a range of methods for characterizing proteins and other biomolecules. MS is uniquely powerful for the structural analysis of endogenous protein complexes, which are often heterogeneous, poorly abundant, and refractive to characterization by other methods. Here, we focus on how biological MS can contribute to the study of endogenous protein complexes, which we define as complexes expressed in the physiological host and purified intact, as opposed to reconstituted complexes assembled from heterologously expressed components. Biological MS can yield information on complex stoichiometry, heterogeneity, topology, stability, activity, modes of regulation, and even structural dynamics. We begin with a review of methods for isolating endogenous complexes. We then describe the various biological MS approaches, focusing on the type of information that each method yields. We end with future directions and challenges for these MS-based methods.

Cross-linking and mass spectrometry as a tool for studying the structural biology of ribonucleoproteins

Cross-linking and mass spectrometry (XL-MS) workflows represent an increasingly popular technique for low-resolution structural studies of macromolecular complexes. Cross-linking reactions take place in the solution state, capturing contact sites between components of a complex that represent the native, functionally relevant structure. Protein-protein XL-MS protocols are widely adopted, providing precise localization of cross-linking sites to single amino acid positions within a pair of cross-linked peptides. In contrast, protein-RNA XL-MS workflows are evolving rapidly and differ in their ability to localize interaction regions within the RNA sequence. Here, we review protein-protein and protein-RNA XL-MS workflows, and discuss their applications in studies of protein-RNA complexes. The examples highlight the complementary value of XL-MS in structural studies of protein-RNA complexes, where more established high-resolution techniques might be unable to produce conclusive data.

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.

Protein Chemistry Combined with Mass Spectrometry for Protein Structure Determination

The advent of soft-ionization mass spectrometry for biomolecules has opened up new possibilities for the structural analysis of proteins. Combining protein chemistry methods with modern mass spectrometry has led to the emergence of the distinct field of structural proteomics. Multiple protein chemistry approaches, such as surface modification, limited proteolysis, hydrogen-deuterium exchange, and cross-linking, provide diverse and often orthogonal structural information on the protein systems studied. Combining experimental data from these various structural proteomics techniques provides a more comprehensive examination of the protein structure and increases confidence in the ultimate findings. Here, we review various types of experimental data from structural proteomics approaches with an emphasis on the use of multiple complementary mass spectrometric approaches to provide experimental constraints for the solving of protein structures.

Solution Structure and Conformational Flexibility of a Polyketide Synthase Module

Polyketide synthases (PKSs) are versatile C-C bond-forming enzymes that are broadly distributed in bacteria and fungi. The polyketide compound family includes many clinically useful drugs such as the antibiotic erythromycin, the antineoplastic epothilone, and the cholesterol-lowering lovastatin. Harnessing PKSs for custom compound synthesis remains an open challenge, largely because of the lack of knowledge about key structural properties. Particularly, the domains-well characterized on their own-are poorly understood in their arrangement, conformational dynamics, and interplay in the intricate quaternary structure of modular PKSs. Here, we characterize module 2 from the 6-deoxyerythronolide B synthase by small-angle X-ray scattering and cross-linking mass spectrometry with coarse-grained structural modeling. The results of this hybrid approach shed light on the solution structure of a cis-AT type PKS module as well as its inherent conformational dynamics. Supported by a directed evolution approach, we also find that acyl carrier protein (ACP)-mediated substrate shuttling appears to be steered by a nonspecific electrostatic interaction network.

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.

Mass Spectrometric Identification of a Novel Factor XIIIa Cross-Linking Site in Fibrinogen

Transglutaminases are a class of enzymes that catalyze the formation of a protein:protein cross-link between a lysine and a glutamine residue. These cross-links play important roles in diverse biological processes. Analysis of cross-linking sites in target proteins is required to elucidate their molecular action on target protein function and the molecular specificity of different transglutaminase isozymes. Mass-spectrometry using settings designed for linear peptide analysis and software designed for the analysis of disulfide bridges and chemical cross-links have previously been employed to identify transglutaminase cross-linking sites in proteins. As no control peptide with which to assess and improve the mass spectrometric analysis of TG cross-linked proteins was available, we developed a method for the enzymatic synthesis of a well-defined transglutaminase cross-linked peptide pair that mimics a predicted tryptic digestion product of collagen I. We then used this model peptide to determine optimal score thresholds for correct peptide identification from y- and b-ion series of fragments produced by collision-induced dissociation. We employed these settings in an analysis of fibrinogen cross-linked by the transglutaminase Factor XIIIa. This approach resulted in identification of a novel cross-linked peptide in the gamma subunit. We discuss the difference in behavior of ions derived from different cross-linked peptide sequences and the consequent demand for a more tailored mass spectrometry approach for cross-linked peptide identification compared to that routinely used for linear peptide analysis.

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.

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.

Reliable identification of protein-protein interactions by crosslinking mass spectrometry

Protein-protein interactions govern most cellular pathways and processes, and multiple technologies have emerged to systematically map them. Assessing the error of interaction networks has been a challenge. Crosslinking mass spectrometry is currently widening its scope from structural analyses of purified multi-protein complexes towards systems-wide analyses of protein-protein interactions (PPIs). Using a carefully controlled large-scale analysis of Escherichia coli cell lysate, we demonstrate that false-discovery rates (FDR) for PPIs identified by crosslinking mass spectrometry can be reliably estimated. We present an interaction network comprising 590 PPIs at 1% decoy-based PPI-FDR. The structural information included in this network localises the binding site of the hitherto uncharacterised protein YacL to near the DNA exit tunnel on the RNA polymerase.

Enabling Photoactivated Cross-Linking Mass Spectrometric Analysis of Protein Complexes by Novel MS-Cleavable Cross-Linkers

Cross-linking mass spectrometry (XL-MS) is a powerful tool for studying protein-protein interactions and elucidating architectures of protein complexes. While residue-specific XL-MS studies have been very successful, accessibility of interaction regions nontargetable by specific chemistries remain difficult. Photochemistry has shown great potential in capturing those regions because of nonspecific reactivity, but low yields and high complexities of photocross-linked products have hindered their identification, limiting current studies predominantly to single proteins. Here, we describe the development of three novel MS-cleavable heterobifunctional cross-linkers, namely SDASO (Succinimidyl diazirine sulfoxide), to enable fast and accurate identification of photocross-linked peptides by MSⁿ. The MSⁿ-based workflow allowed SDASO XL-MS analysis of the yeast 26S proteasome, demonstrating the feasibility of photocross-linking of large protein complexes for the first time. Comparative analyses have revealed that SDASO cross-linking is robust and captures interactions complementary to residue-specific reagents, providing the foundation for future applications of photocross-linking in complex XL-MS studies.

Analysis of the Dynamic Proteasome Structure by Cross-Linking Mass Spectrometry

The 26S proteasome is a macromolecular complex that degrades proteins maintaining cell homeostasis; thus, determining its structure is a priority to understand its function. Although the 20S proteasome's structure has been known for some years, the highly dynamic nature of the 19S regulatory particle has presented a challenge to structural biologists. Advances in cryo-electron microscopy (cryo-EM) made it possible to determine the structure of the 19S regulatory particle and showed at least seven different conformational states of the proteasome. However, there are still many questions to be answered. Cross-linking mass spectrometry (CLMS) is now routinely used in integrative structural biology studies, and it promises to take integrative structural biology to the next level, answering some of these questions.

Tyrosine-Reactive Cross-Linker for Probing Protein Three-Dimensional Structures

Cross-linking mass spectrometry (XL-MS) has made significant progress in understanding the structure of protein and elucidating architectures of larger protein complexes. Current XL-MS applications are limited to targeting lysine, glutamic acid, aspartic acid, and cysteine residues. There remains a need for the development of novel cross-linkers enabling selective targeting of other amino acid residues in proteins. Here, a novel simple cross-linker, namely, [4,4'-(disulfanediylbis(ethane-2,1-diyl)) bis(1,2,4-triazolidine-3,5-dione)] (DBB), has been designed, synthesized, and characterized. This cross-linker can react selectively with tyrosine residues in protein through the electrochemical click reaction. The DBB cross-links produced the characteristic peptides before and after electrochemical reduction, thus permitting the simplified data analysis and accurate identification for the cross-linked products. This is the first time a cross-linker is developed for targeting tyrosine residues on protein without using photoirradiation or a metal catalyst. This strategy might potentially be used as a complementary tool for XL-MS to probe protein 3D structures, protein complexes, and protein-protein interaction.

Interfaces with Structure Dynamics of the Workhorses from Cells Revealed through Cross-Linking Mass Spectrometry (CLMS)

The fundamentals of how protein-protein/RNA/DNA interactions influence the structures and functions of the workhorses from the cells have been well documented in the 20th century. A diverse set of methods exist to determine such interactions between different components, particularly, the mass spectrometry (MS) methods, with its advanced instrumentation, has become a significant approach to analyze a diverse range of biomolecules, as well as bring insights to their biomolecular processes. This review highlights the principal role of chemistry in MS-based structural proteomics approaches, with a particular focus on the chemical cross-linking of protein-protein/DNA/RNA complexes. In addition, we discuss different methods to prepare the cross-linked samples for MS analysis and tools to identify cross-linked peptides. Cross-linking mass spectrometry (CLMS) holds promise to identify interaction sites in larger and more complex biological systems. The typical CLMS workflow allows for the measurement of the proximity in three-dimensional space of amino acids, identifying proteins in direct contact with DNA or RNA, and it provides information on the folds of proteins as well as their topology in the complexes. Principal CLMS applications, its notable successes, as well as common pipelines that bridge proteomics, molecular biology, structural systems biology, and interactomics are outlined.

Anatomy of a crosslinker

Crosslinking mass spectrometry has become a core technology in structural biology and is expanding its reach towards systems biology. Its appeal lies in a rapid workflow, high sensitivity and the ability to provide data on proteins in complex systems, even in whole cells. The technology depends heavily on crosslinking reagents. The anatomy of crosslinkers can be modular, sometimes comprising combinations of functional groups. These groups are defined by concepts including: reaction selectivity to increase information density, enrichability to improve detection, cleavability to enhance the identification process and isotope-labelling for quantification. Here, we argue that both concepts and functional groups need more thorough experimental evaluation, so that we can show exactly how and where they are useful when applied to crosslinkers. Crosslinker design should be driven by data, not only concepts. We focus on two crosslinker concepts with large consequences for the technology, namely reactive group reaction kinetics and enrichment groups.

An acidic residue reactive and disulfide bond-containing cleavable cross-linker for probing protein 3D structures based on electrochemical mass spectrometry

Cross-linking mass spectrometry (XL-MS) has attracted broad attention because of the capability to probe three-dimensional structure of proteins. Up to now, several amine-reactive cross-linkers have been developed for characterization of proteins and protein complexes. However, spatial information retrieved by XL-MS is still limited, partly because the strategies using an acidic residue reactive cross-linker have been rarely reported. In this paper, an acidic residue (e.g. aspartic acid, glutamic acid)-specific, disulfide bond-containing, cleavable cross-linker with a length of 13.1 Å, named 3,3'-dithiobis(propanoic dihydrazide), was presented for the first time. In addition, a novel approach using the cross-linker was proposed for unambiguous characterization of peptides and proteins with disulfide bonds. After cross-linked, the peptides could be electrochemically reduced, then characterized by high performance liquid chromatography mass spectrometry. For demonstration, the approach has been adopted to characterize the emideltide, insulin, and myoglobin, of which four pairs of intrachain cross-links have been successfully identified in myoglobin. The results showed that the cross-links displayed predictable fragmentation pattern upon collision induced dissociation (CID), thus admitting simplifying data analysis. In summary, this work introduces a novel type of cross-linker utilized for cross-linking and a new strategy to XL-MS technology for comprehensively understanding the three-dimensional structure of proteins.

Experimentally-driven protein structure modeling

Revolutions in natural and exact sciences started at the dawn of last century have led to the explosion of theoretical, experimental, and computational approaches to determine structures of molecules, complexes, as well as their rich conformational dynamics. Since different experimental methods produce information that is attributed to specific time and length scales, corresponding computational methods have to be tailored to these scales and experiments. These methods can be then combined and integrated in scales, hence producing a fuller picture of molecular structure and motion from the "puzzle pieces" offered by various experiments. Here, we describe a number of computational approaches to utilize experimental data to glance into structure of proteins and understand their dynamics. We will also discuss the limitations and the resolution of the constraints-based modeling approaches. SIGNIFICANCE: Experimentally-driven computational structure modeling and determination is a rapidly evolving alternative to traditional approaches for molecular structure determination. These new hybrid experimental-computational approaches are proving to be a powerful microscope to glance into the structural features of intrinsically or partially disordered proteins, dynamics of molecules and complexes. In this review, we describe various approaches in the field of experimentally-driven computational structure modeling.

Mass Spectrometry-Based Protein Footprinting for Higher-Order Structure Analysis: Fundamentals and Applications

Proteins adopt different higher-order structures (HOS) to enable their unique biological functions. Understanding the complexities of protein higher-order structures and dynamics requires integrated approaches, where mass spectrometry (MS) is now positioned to play a key role. One of those approaches is protein footprinting. Although the initial demonstration of footprinting was for the HOS determination of protein/nucleic acid binding, the concept was later adapted to MS-based protein HOS analysis, through which different covalent labeling approaches "mark" the solvent accessible surface area (SASA) of proteins to reflect protein HOS. Hydrogen-deuterium exchange (HDX), where deuterium in D2O replaces hydrogen of the backbone amides, is the most common example of footprinting. Its advantage is that the footprint reflects SASA and hydrogen bonding, whereas one drawback is the labeling is reversible. Another example of footprinting is slow irreversible labeling of functional groups on amino acid side chains by targeted reagents with high specificity, probing structural changes at selected sites. A third footprinting approach is by reactions with fast, irreversible labeling species that are highly reactive and footprint broadly several amino acid residue side chains on the time scale of submilliseconds. All of these covalent labeling approaches combine to constitute a problem-solving toolbox that enables mass spectrometry as a valuable tool for HOS elucidation. As there has been a growing need for MS-based protein footprinting in both academia and industry owing to its high throughput capability, prompt availability, and high spatial resolution, we present a summary of the history, descriptions, principles, mechanisms, and applications of these covalent labeling approaches. Moreover, their applications are highlighted according to the biological questions they can answer. This review is intended as a tutorial for MS-based protein HOS elucidation and as a reference for investigators seeking a MS-based tool to address structural questions in protein science.

High-density chemical cross-linking for modeling protein interactions

Detailed mechanistic understanding of protein complex function is greatly enhanced by insights from its 3-dimensional structure. Traditional methods of protein structure elucidation remain expensive and labor-intensive and require highly purified starting material. Chemical cross-linking coupled with mass spectrometry offers an alternative that has seen increased use, especially in combination with other experimental approaches like cryo-electron microscopy. Here we report advances in method development, combining several orthogonal cross-linking chemistries as well as improvements in search algorithms, statistical analysis, and computational cost to achieve coverage of 1 unique cross-linked position pair for every 7 amino acids at a 1% false discovery rate. This is accomplished without any peptide-level fractionation or enrichment. We apply our methods to model the complex between a carbonic anhydrase (CA) and its protein inhibitor, showing that the cross-links are self-consistent and define the interaction interface at high resolution. The resulting model suggests a scaffold for development of a class of protein-based inhibitors of the CA family of enzymes. We next cross-link the yeast proteasome, identifying 3,893 unique cross-linked peptides in 3 mass spectrometry runs. The dataset includes 1,704 unique cross-linked position pairs for the proteasome subunits, more than half of them intersubunit. Using multiple recently solved cryo-EM structures, we show that observed cross-links reflect the conformational dynamics and disorder of some proteasome subunits. We further demonstrate that this level of cross-linking density is sufficient to model the architecture of the 19-subunit regulatory particle de novo.

In Situ Structural Restraints from Cross-Linking Mass Spectrometry in Human Mitochondria

The field of structural biology is increasingly focusing on studying proteins in situ, i.e., in their greater biological context. Cross-linking mass spectrometry (CLMS) is contributing to this effort, typically through the use of mass spectrometry (MS)-cleavable cross-linkers. Here, we apply the popular noncleavable cross-linker disuccinimidyl suberate (DSS) to human mitochondria and identify 5518 distance restraints between protein residues. Each distance restraint on proteins or their interactions provides structural information within mitochondria. Comparing these restraints to protein data bank (PDB)-deposited structures and comparative models reveals novel protein conformations. Our data suggest, among others, substrates and protein flexibility of mitochondrial heat shock proteins. Through this study, we bring forward two central points for the progression of CLMS towards large-scale in situ structural biology: First, clustered conflicts of cross-link data reveal in situ protein conformation states in contrast to error-rich individual conflicts. Second, noncleavable cross-linkers are compatible with proteome-wide studies.

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.

Federating Structural Models and Data: Outcomes from A Workshop on Archiving Integrative Structures

Structures of biomolecular systems are increasingly computed by integrative modeling. In this approach, a structural model is constructed by combining information from multiple sources, including varied experimental methods and prior models. In 2019, a Workshop was held as a Biophysical Society Satellite Meeting to assess progress and discuss further requirements for archiving integrative structures. The primary goal of the Workshop was to build consensus for addressing the challenges involved in creating common data standards, building methods for federated data exchange, and developing mechanisms for validating integrative structures. The summary of the Workshop and the recommendations that emerged are presented here.

PhoX: An IMAC-Enrichable Cross-Linking Reagent

Chemical cross-linking mass spectrometry is rapidly emerging as a prominent technique to study protein structures. Structural information is obtained by covalently connecting peptides in close proximity by small reagents and identifying the resulting peptide pairs by mass spectrometry. However, substoichiometric reaction efficiencies render routine detection of cross-linked peptides problematic. Here, we present a new trifunctional cross-linking reagent, termed PhoX, which is decorated with a stable phosphonic acid handle. This makes the cross-linked peptides amenable to the well-established immobilized metal affinity chromatography (IMAC) enrichment. The handle allows for 300× enrichment efficiency and 97% specificity. We exemplify the approach on various model proteins and protein complexes, e.g., resulting in a structural model of the LRP1/RAP complex. Almost completely removing linear peptides allows PhoX, although noncleavable, to be applied to complex lysates. Focusing the database search to the 1400 most abundant proteins, we were able to identify 1156 cross-links in a single 3 h measurement.

xiSPEC: web-based visualization, analysis and sharing of proteomics data

We present xiSPEC, a standard compliant, next-generation web-based spectrum viewer for visualizing, analyzing and sharing mass spectrometry data. Peptide-spectrum matches from standard proteomics and cross-linking experiments are supported. xiSPEC is to date the only browser-based tool supporting the standardized file formats mzML and mzIdentML defined by the proteomics standards initiative. Users can either upload data directly or select files from the PRIDE data repository as input. xiSPEC allows users to save and share their datasets publicly or password protected for providing access to collaborators or readers and reviewers of manuscripts. The identification table features advanced interaction controls and spectra are presented in three interconnected views: (i) annotated mass spectrum, (ii) peptide sequence fragmentation key and (iii) quality control error plots of matched fragments. Highlighting or selecting data points in any view is represented in all other views. Views are interactive scalable vector graphic elements, which can be exported, e.g. for use in publication. xiSPEC allows for re-annotation of spectra for easy hypothesis testing by modifying input data. xiSPEC is freely accessible at http://spectrumviewer.org and the source code is openly available on https://github.com/Rappsilber-Laboratory/xiSPEC.

Quantitative Photo-crosslinking Mass Spectrometry Revealing Protein Structure Response to Environmental Changes

Protein structures respond to changes in their chemical and physical environment. However, studying such conformational changes is notoriously difficult, as many structural biology techniques are also affected by these parameters. Here, the use of photo-crosslinking, coupled with quantitative crosslinking mass spectrometry (QCLMS), offers an opportunity, since the reactivity of photo-crosslinkers is unaffected by changes in environmental parameters. In this study, we introduce a workflow combining photo-crosslinking using sulfosuccinimidyl 4,4'-azipentanoate (sulfo-SDA) with our recently developed data-independent acquisition (DIA)-QCLMS. This novel photo-DIA-QCLMS approach is then used to quantify pH-dependent conformational changes in human serum albumin (HSA) and cytochrome C by monitoring crosslink abundances as a function of pH. Both proteins show pH-dependent conformational changes resulting in acidic and alkaline transitions. 93% and 95% of unique residue pairs (URP) were quantifiable across triplicates for HSA and cytochrome C, respectively. Abundance changes of URPs and hence conformational changes of both proteins were visualized using hierarchical clustering. For HSA we distinguished the N-F and the N-B form from the native conformation. In addition, we observed for cytochrome C acidic and basic conformations. In conclusion, our photo-DIA-QCLMS approach distinguished pH-dependent conformers of both proteins.

Archiving and disseminating integrative structure models

Limitations in the applicability, accuracy, and precision of individual structure characterization methods can sometimes be overcome via an integrative modeling approach that relies on information from all available sources, including all available experimental data and prior models. The open-source Integrative Modeling Platform (IMP) is one piece of software that implements all computational aspects of integrative modeling. To maximize the impact of integrative structures, the coordinates should be made publicly available, as is already the case for structures based on X-ray crystallography, NMR spectroscopy, and electron microscopy. Moreover, the associated experimental data and modeling protocols should also be archived, such that the original results can easily be reproduced. Finally, it is essential that the integrative structures are validated as part of their publication and deposition. A number of research groups have already developed software to implement integrative modeling and have generated a number of structures, prompting the formation of an Integrative/Hybrid Methods Task Force. Following the recommendations of this task force, the existing PDBx/mmCIF data representation used for atomic PDB structures has been extended to address the requirements for archiving integrative structural models. This IHM-dictionary adds a flexible model representation, including coarse graining, models in multiple states and/or related by time or other order, and multiple input experimental information sources. A prototype archiving system called PDB-Dev ( https://pdb-dev.wwpdb.org ) has also been created to archive integrative structural models, together with a Python library to facilitate handling of integrative models in PDBx/mmCIF format.

ThreaDomEx: a unified platform for predicting continuous and discontinuous protein domains by multiple-threading and segment assembly

We develop a hierarchical pipeline, ThreaDomEx, for both continuous domain (CD) and discontinuous domain (DCD) structure predictions. Starting from a query sequence, ThreaDomEx first threads it through the PDB to identify multiple structure templates, where a profile of domain conservation score (DC-score) is derived for domain-segment assignment. To further detect DCDs that consist of separated segments along the sequence, a boundary-clustering algorithm is used to refine the DCD-linker locations. In case that the templates do not contain DCDs, a domain-segment assembly process, guided by symmetry comparison, is applied for further DCD detections. ThreaDomEx was tested a set of 1111 proteins and achieved a normalized domain overlap score of 89.3% compared to experimental data, which is significantly higher than other state-of-the-art methods. It also recalls 26.7% of DCDs with 72.7% precision on the proteins for which threading failed to detect any DCDs. The server provides facilities for users to interactively refine the domain models by adjusting DC-score threshold, deleting and adding domain linkers, and assembling domain segments, which are particularly helpful for the hard targets for which current methods have a low accuracy while human-expert knowledge and experimental insights can be used for refining models. ThreaDomEX server is available at http://zhanglab.ccmb.med.umich.edu/ThreaDomEx.

Integrative Structure Modeling: Overview and Assessment

Integrative structure modeling computationally combines data from multiple sources of information with the aim of obtaining structural insights that are not revealed by any single approach alone. In the first part of this review, we survey the commonly used sources of structural information and the computational aspects of model building. Throughout the past decade, integrative modeling was applied to various biological systems, with a focus on large protein complexes. Recent progress in the field of cryo-electron microscopy (cryo-EM) has resolved many of these complexes to near-atomic resolution. In the second part of this review, we compare a range of published integrative models with their higher-resolution counterparts with the aim of critically assessing their accuracy. This comparison gives a favorable view of integrative modeling and demonstrates its ability to yield accurate and informative results. We discuss possible roles of integrative modeling in the new era of cryo-EM and highlight future challenges and directions.

Noncovalently Associated Peptides Observed during Liquid Chromatography-Mass Spectrometry and Their Effect on Cross-Link Analyses

Cross-linking mass spectrometry draws structural information from covalently linked peptide pairs. When these links do not match to previous structural models, they may indicate changes in protein conformation. Unfortunately, such links can also be the result of experimental error or artifacts. Here, we describe the observation of noncovalently associated peptides during liquid chromatography-mass spectrometry analysis, which can easily be misidentified as cross-linked. Strikingly, they often mismatch to the protein structure. Noncovalently associated peptides presumably form during ionization and can be distinguished from cross-linked peptides by observing coelution of the corresponding linear peptides in MS1 spectra, as well as the presence of the individual (intact) peptide fragments in MS2 spectra. To suppress noncovalent peptide formations, increasingly disruptive ionization settings can be used, such as in-source fragmentation.

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.

Cross-linking mass spectrometry: methods and applications in structural, molecular and systems biology

Over the past decade, cross-linking mass spectrometry (CLMS) has developed into a robust and flexible tool that provides medium-resolution structural information. CLMS data provide a measure of the proximity of amino acid residues and thus offer information on the folds of proteins and the topology of their complexes. Here, we highlight notable successes of this technique as well as common pipelines. Novel CLMS applications, such as in-cell cross-linking, probing conformational changes and tertiary-structure determination, are now beginning to make contributions to molecular biology and the emerging fields of structural systems biology and interactomics.

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.

False discovery rate estimation and heterobifunctional cross-linkers

False discovery rate (FDR) estimation is a cornerstone of proteomics that has recently been adapted to cross-linking/mass spectrometry. Here we demonstrate that heterobifunctional cross-linkers, while theoretically different from homobifunctional cross-linkers, need not be considered separately in practice. We develop and then evaluate the impact of applying a correct FDR formula for use of heterobifunctional cross-linkers and conclude that there are minimal practical advantages. Hence a single formula can be applied to data generated from the many different non-cleavable cross-linkers.

XPlex: An Effective, Multiplex Cross-Linking Chemistry for Acidic Residues

Cross-linking/Mass spectrometry (XLMS) is a consolidated technique for structural characterization of proteins and protein complexes. Despite its success, the cross-linking chemistry currently used is mostly based on N-hydroxysuccinimide (NHS) esters, which react primarily with lysine residues. One way to expand the current applicability of XLMS into several new areas is to increase the number of cross-links obtainable for a target protein. We introduce a multiplex chemistry (denoted XPlex) that targets Asp, Glu, Lys, and Ser residues. XPlex can generate significantly more cross-links with reactions occurring at lower temperatures and enables targeting proteins that are not possible with NHS ester-based cross-linkers. We demonstrate the effectiveness of our approach in model proteins as well as a target Lys-poor protein, SalBIII. Identification of XPlex spectra requires a search engine capable of simultaneously considering multiple cross-linkers on the same run; to achieve this, we updated the SIM-XL search algorithm with a search mode tailored toward XPlex. In summary, we present a complete chemistry/computational solution for significantly increasing the number of possible distance constraints by mass spectrometry experiments, and thus, we are convinced that XPlex poses as a real complementary approach for structural proteomics studies.

Development of a Prototype System for Archiving Integrative/Hybrid Structure Models of Biological Macromolecules

Essential processes in biology are carried out by large macromolecular assemblies, whose structures are often difficult to determine by traditional methods. Increasingly, researchers combine measured data and computed information from several complementary methods to obtain "hybrid" or "integrative" structural models of macromolecules and their assemblies. These integrative/hybrid (I/H) models are not archived in the PDB because of the absence of standard data representations and processing mechanisms. Here we present the development of data standards and a prototype system for archiving I/H models. The data standards provide the definitions required for representing I/H models that span multiple spatiotemporal scales and conformational states, as well as spatial restraints derived from different experimental techniques. Based on these data definitions, we have built a prototype system called PDB-Dev, which provides the infrastructure necessary to archive I/H structural models. PDB-Dev is now accepting structures and is open to the community for new submissions.