Blind testing of cross-linking/mass spectrometry hybrid methods in CASP11

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.

Integrative Modeling of a Sin3/HDAC Complex Sub-structure

Sin3/HDAC complexes function by deacetylating histones, condensing chromatin, and modulating gene expression. Although components used to build these complexes have been well defined, we still have only a limited understanding of the structure of the Sin3/HDAC subunits assembled around the scaffolding protein SIN3A. To characterize the spatial arrangement of Sin3 subunits, we combined Halo affinity capture, chemical crosslinking, and high-resolution mass spectrometry (XL-MS) to determine intersubunit distance constraints, identifying 66 interprotein and 63 self-crosslinks for 13 Sin3 subunits. Having assessed crosslink authenticity by mapping self-crosslinks onto existing structures, we used distance restraints from interprotein crosslinks to guide assembly of a Sin3 complex substructure. We identified the relative positions of subunits SAP30L, HDAC1, SUDS3, HDAC2, and ING1 around the SIN3A scaffold. The architecture of this subassembly suggests that multiple factors have space to assemble to collectively influence the behavior of the catalytic subunit HDAC1.

Banks et al. capture positional information for subunits within Sin3/HDAC complexes by combining crosslinking and high-resolution mass spectrometry. This information is then used to guide docking of Sin3 subunit structures to develop a model of a Sin3/HDAC complex sub-structure.

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.

Olefinic reagents tested for peptide derivatization with switchable properties: Stable upon collision induced dissociation and cleavable by in-source Paternò-Büchi reactions

This contribution is part of our ongoing efforts to develop innovative cross-linking (XL) reagents and protocols for facilitated peptide mixture analysis and efficient assignment of cross-linked peptide products. In this report, we combine in-source Paternò-Büchi (PB) photo-chemistry with a tandem mass spectrometry approach to selectively address the fragmentation of a tailor-made cross-linking reagent. The PB photochemistry, so far exclusively used for the identification of unsaturation sites in lipids and in lipidomics, is now introduced to the field of chemical cross-linking. Based on trans-3-hexenedioic acid, an olefinic homo bifunctional amine reactive XL reagent was designed and synthesized for this proof-of-principle study. Condensation products of the olefinic reagent with a set of exemplary peptides are used to test the feasibility of the concept. Benzophenone is photochemically reacted in the nano-electrospray ion source and forms oxetane PB reaction products. Subsequent CID-MS triggered retro-PB reaction of the respective isobaric oxetane molecular ions and delivers reliably and predictably two sets of characteristic fragment ions of the cross-linker. Based on these signature ion sets, a straightforward identification of covalently interconnected peptides in complex digests is proposed. Furthermore, CID-MSⁿ experiments of the retro-PB reaction products deliver peptide backbone characteristic fragment ions. Additionally, the olefinic XL reagents exhibit a pronounced robustness upon CID-activation, without previous UV-excitation. These experiments document that a complete backbone fragmentation is possible, while the linker-moiety remains intact. This feature renders the new olefinic linkers switchable between a stable, noncleavable cross-linking mode and an in-source PB cleavable mode.

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.

Role of integrative structural biology in understanding transcriptional initiation

Integrative structural biology combines data from multiple experimental techniques to generate complete structural models for the biological system of interest. Most commonly cross-linking data sets are employed alongside electron microscopy maps, crystallographic structures, and other data by computational methods that integrate all known information and produce structural models at a level of resolution that is appropriate to the input data. The precision of these modelled solutions is limited by the sparseness of cross-links observed, the length of the cross-linking reagent, the ambiguity arisen from the presence of multiple copies of the same protein, and structural and compositional heterogeneity. In recent years integrative structural biology approaches have been successfully applied to a range of RNA polymerase II complexes. Here we will provide a general background to integrative structural biology, a description of how it should be practically implemented and how it has furthered our understanding of the biology of large transcriptional assemblies. Finally, in the context of recent breakthroughs in microscope and direct electron detector technology, where increasingly EM is capable of resolving structural features directly without the aid of other structural techniques, we will discuss the future role of integrative structural techniques.

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.

The First MS-Cleavable, Photo-Thiol-Reactive Cross-Linker for Protein Structural Studies

Cleavable cross-linkers are gaining increasing importance for chemical cross-linking/mass spectrometry (MS) as they permit a reliable and automated data analysis in structural studies of proteins and protein assemblies. Here, we introduce 1,3-diallylurea (DAU) as the first CID-MS/MS-cleavable, photo-thiol-reactive cross-linker. DAU is a commercially available, inexpensive reagent that efficiently undergoes an anti-Markovnikov hydrothiolation with cysteine residues in the presence of a radical initiator upon UV-A irradiation. Radical cysteine cross-linking proceeds via an orthogonal "click reaction" and yields stable alkyl sulfide products. DAU reacts at physiological pH and cross-linking reactions with peptides, and proteins can be performed at temperatures as low as 4 °C. The central urea bond is efficiently cleaved upon collisional activation during tandem MS experiments generating characteristic product ions. This improves the reliability of automated cross-link identification. Different radical initiators have been screened for the cross-linking reaction of DAU using the thiol-containing compounds cysteine and glutathione. Our concept has also been exemplified for the biologically relevant proteins bMunc13-2 and retinal guanylyl cyclase-activating protein-2. Graphical abstract ᅟ.

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.

Synthesis of CID-cleavable protein crosslinking agents containing quaternary amines for structural mass spectrometry

Two novel cyclic quaternary amine crosslinking probes are synthesized for structural mass spectrometry of protein complexes in solution and for analysis of protein interactions in organellar and whole cell extracts. Each exhibits high aqueous solubility, excellent protein crosslinking efficiencies, low collision induced dissociation (CID) energy fragmentation efficiencies, high stoichiometries of reaction, increased charges of crosslinked peptide ions, and maintenance of overall surface charge balance of crosslinked proteins.

Critical assessment of methods of protein structure prediction (CASP)-Round XII

This article reports the outcome of the 12th round of Critical Assessment of Structure Prediction (CASP12), held in 2016. CASP is a community experiment to determine the state of the art in modeling protein structure from amino acid sequence. Participants are provided sequence information and in turn provide protein structure models and related information. Analysis of the submitted structures by independent assessors provides a comprehensive picture of the capabilities of current methods, and allows progress to be identified. This was again an exciting round of CASP, with significant advances in 4 areas: (i) The use of new methods for predicting three-dimensional contacts led to a two-fold improvement in contact accuracy. (ii) As a consequence, model accuracy for proteins where no template was available improved dramatically. (iii) Models based on a structural template showed overall improvement in accuracy. (iv) Methods for estimating the accuracy of a model continued to improve. CASP continued to develop new areas: (i) Assessing methods for building quaternary structure models, including an expansion of the collaboration between CASP and CAPRI. (ii) Modeling with the aid of experimental data was extended to include SAXS data, as well as again using chemical cross-linking information. (iii) A team of assessors evaluated the suitability of models for a range of applications, including mutation interpretation, analysis of ligand binding properties, and identification of interfaces. This article describes the experiment and summarizes the results. The rest of this special issue of PROTEINS contains papers describing CASP12 results and assessments in more detail.

Small angle X-ray scattering and cross-linking for data assisted protein structure prediction in CASP 12 with prospects for improved accuracy

Experimental data offers empowering constraints for structure prediction. These constraints can be used to filter equivalently scored models or more powerfully within optimization functions toward prediction. In CASP12, Small Angle X-ray Scattering (SAXS) and Cross-Linking Mass Spectrometry (CLMS) data, measured on an exemplary set of novel fold targets, were provided to the CASP community of protein structure predictors. As solution-based techniques, SAXS and CLMS can efficiently measure states of the full-length sequence in its native solution conformation and assembly. However, this experimental data did not substantially improve prediction accuracy judged by fits to crystallographic models. One issue, beyond intrinsic limitations of the algorithms, was a disconnect between crystal structures and solution-based measurements. Our analyses show that many targets had substantial percentages of disordered regions (up to 40%) or were multimeric or both. Thus, solution measurements of flexibility and assembly support variations that may confound prediction algorithms trained on crystallographic data and expecting globular fully-folded monomeric proteins. Here, we consider the CLMS and SAXS data collected, the information in these solution measurements, and the challenges in incorporating them into computational prediction. As improvement opportunities were only partly realized in CASP12, we provide guidance on how data from the full-length biological unit and the solution state can better aid prediction of the folded monomer or subunit. We furthermore describe strategic integrations of solution measurements with computational prediction programs with the aim of substantially improving foundational knowledge and the accuracy of computational algorithms for biologically-relevant structure predictions for proteins in solution.

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.

Novel Concepts of MS-Cleavable Cross-linkers for Improved Peptide Structure Analysis

The chemical cross-linking/mass spectrometry (MS) approach is gaining increasing importance as an alternative method for studying protein conformation and for deciphering protein interaction networks. This study is part of our ongoing efforts to develop innovative cross-linking principles for a facile and efficient assignment of cross-linked products. We evaluate two homobifunctional, amine-reactive, and MS-cleavable cross-linkers regarding their potential for automated analysis of cross-linked products. We introduce the bromine phenylurea (BrPU) linker that possesses a unique structure yielding a distinctive fragmentation pattern on collisional activation. Moreover, BrPU delivers the characteristic bromine isotope pattern and mass defect for all cross-linker-decorated fragments. We compare the fragmentation behavior of the BrPU linker with that of our previously described MS-cleavable TEMPO-Bz linker (which consists of a 2,2,6,6-tetramethylpiperidine-1-oxy moiety connected to a benzyl group) that was developed to perform free-radical-initiated peptide sequencing. Comparative collisional activation experiments (collision-induced dissociation and higher-energy collision-induced dissociation) with both cross-linkers were conducted in negative electrospray ionization mode with an Orbitrap Fusion mass spectrometer using five model peptides. As hypothesized in a previous study, the presence of a cross-linked N-terminal aspartic acid residue seems to be the prerequisite for the loss of an intact peptide from the cross-linked products. As the BrPU linker combines a characteristic mass shift with an isotope signature, it presents a more favorable combination for automated assignment of cross-linked products compared with the TEMPO-Bz linker. ᅟ.

A Novel MS-Cleavable Azo Cross-Linker for Peptide Structure Analysis by Free Radical Initiated Peptide Sequencing (FRIPS)

The chemical cross-linking/mass spectrometry (MS) approach is a growing research field in structural proteomics that allows gaining insights into protein conformations. It relies on creating distance constraints between cross-linked amino acid side chains that can further be used to derive protein structures. Currently, the most urgent task for designing novel cross-linking principles is an unambiguous and automated assignment of the created cross-linked products. Here, we introduce the homobifunctional, amine-reactive, and water soluble cross-linker azobisimidoester (ABI) as a prototype of a novel class of cross-linkers. The ABI-linker possesses an innovative modular scaffold combining the benefits of collisional activation lability with open shell chemistry. This MS-cleavable cross-linker can be efficiently operated via free radical initiated peptide sequencing (FRIPS) in positive ionization mode. Our proof-of-principle study challenges the gas phase behavior of the ABI-linker for the three amino acids, lysine, leucine, and isoleucine, as well as the model peptide thymopentin. The isomeric amino acids leucine and isoleucine could be discriminated by their characteristic side chain fragments. Collisional activation experiments were conducted via positive electrospray ionization (ESI) on two Orbitrap mass spectrometers. The ABI-mediated formation of odd electron product ions in MS/MS and MS³ experiments was evaluated and compared with a previously described azo-based cross-linker. All cross-linked products were amenable to automated analysis by the MeroX software, underlining the future potential of the ABI-linker for structural proteomics studies. Graphical Abstract ᅟ.

Surface Accessibility and Dynamics of Macromolecular Assemblies Probed by Covalent Labeling Mass Spectrometry and Integrative Modeling

Mass spectrometry (MS) has become an indispensable tool for investigating the architectures and dynamics of macromolecular assemblies. Here we show that covalent labeling of solvent accessible residues followed by their MS-based identification yields modeling restraints that allow mapping the location and orientation of subunits within protein assemblies. Together with complementary restraints derived from cross-linking and native MS, we built native-like models of four heterocomplexes with known subunit structures and compared them with available X-ray crystal structures. The results demonstrated that covalent labeling followed by MS markedly increased the predictive power of the integrative modeling strategy enabling more accurate protein assembly models. We applied this strategy to the F-type ATP synthase from spinach chloroplasts (cATPase) providing a structural basis for its function as a nanomotor. By subjecting the models generated by our restraint-based strategy to molecular dynamics (MD) simulations, we revealed the conformational states of the peripheral stalk and assigned flexible regions in the enzyme. Our strategy can readily incorporate complementary chemical labeling strategies and we anticipate that it will be applicable to many other systems providing new insights into the structure and function of protein complexes.

Blind testing cross-linking/mass spectrometry under the auspices of the 11th critical assessment of methods of protein structure prediction (CASP11)

Determining the structure of a protein by any method requires various contributions from experimental and computational sides. In a recent study, high-density cross-linking/mass spectrometry (HD-CLMS) data in combination with ab initio structure prediction determined the structure of human serum albumin (HSA) domains, with an RMSD to X-ray structure of up to 2.5 Å, or 3.4 Å in the context of blood serum. This paper reports the blind test on the readiness of this technology through the help of Critical Assessment of protein Structure Prediction (CASP). We identified between 201-381 unique residue pairs at an estimated 5% FDR (at link level albeit with missing site assignment precision evaluation), for four target proteins. HD-CLMS proved reliable once crystal structures were released. However, improvements in structure prediction using cross-link data were slight. We identified two reasons for this. Spread of cross-links along the protein sequence and the tightness of the spatial constraints must be improved. However, for the selected targets even ideal contact data derived from crystal structures did not allow modellers to arrive at the observed structure. Consequently, the progress of HD-CLMS in conjunction with computational modeling methods as a structure determination method, depends on advances on both arms of this hybrid approach.

Quantitative FRET studies and integrative modeling unravel the structure and dynamics of biomolecular systems

Förster Resonance Energy Transfer (FRET) combined with single-molecule spectroscopy probes macromolecular structure and dynamics and identifies coexisting conformational states. We review recent methodological developments in integrative structural modeling by satisfying spatial restraints on networks of FRET pairs (hybrid-FRET). We discuss procedures to incorporate prior structural knowledge and to obtain optimal distance networks. Finally, a workflow for hybrid-FRET is presented that automates integrative structural modeling and experiment planning to put hybrid-FRET on rails. To test this workflow, we simulate realistic single-molecule experiments and resolve three protein conformers, exchanging at 30μs and 10ms, with accuracies of 1-3Å RMSD versus the target structure. Incorporation of data from other spectroscopies and imaging is also discussed.

Blind Evaluation of Hybrid Protein Structure Analysis Methods based on Cross-Linking

Hybrid methods combine experimental data and computational modeling to analyze protein structures that are elusive to structure determination. To spur the development of hybrid methods, we propose to test them in the context of the CASP experiment and would like to invite experimental groups to participate in this initiative.