Solving protein structures using short-distance cross-linking constraints as a guide for discrete molecular dynamics simulations

Computational Investigation of Coaggregation and Cross-Seeding between Aβ and hIAPP Underpinning the Cross-Talk in Alzheimer's Disease and Type 2 Diabetes

The coexistence of amyloid-β (Aβ) and human islet amyloid polypeptide (hIAPP) in the brain and pancreas is associated with an increased risk of Alzheimer's disease (AD) and type 2 diabetes (T2D) due to their coaggregation and cross-seeding. Despite this, the molecular mechanisms underlying their interaction remain elusive. Here, we systematically investigated the cross-talk between Aβ and hIAPP using atomistic discrete molecular dynamics (DMD) simulations. Our results revealed that the amyloidogenic core regions of both Aβ (Aβ10-21 and Aβ30-41) and hIAPP (hIAPP8-20 and hIAPP22-29), driving their self-aggregation, also exhibited a strong tendency for cross-interaction. This propensity led to the formation of β-sheet-rich heterocomplexes, including potentially toxic β-barrel oligomers. The formation of Aβ and hIAPP heteroaggregates did not impede the recruitment of additional peptides to grow into larger aggregates. Our cross-seeding simulations demonstrated that both Aβ and hIAPP fibrils could mutually act as seeds, assisting each other's monomers in converting into β-sheets at the exposed fibril elongation ends. The amyloidogenic core regions of Aβ and hIAPP, in both oligomeric and fibrillar states, exhibited the ability to recruit isolated peptides, thereby extending the β-sheet edges, with limited sensitivity to the amino acid sequence. These findings suggest that targeting these regions by capping them with amyloid-resistant peptide drugs may hold potential as a therapeutic approach for addressing AD, T2D, and their copathologies.

Molecular Insights into the Effects of F16L and F19L Substitutions on the Conformation and Aggregation Dynamics of Human Calcitonin

Human calcitonin (hCT) regulates calcium-phosphorus metabolism, but its amyloid aggregation disrupts physiological activity, increases thyroid carcinoma risk, and hampers its clinical use for bone-related diseases like osteoporosis and Paget's disease. Improving hCT with targeted modifications to mitigate amyloid formation while maintaining its function holds promise as a strategy. Understanding how each residue in hCT's amyloidogenic core affects its structure and aggregation dynamics is crucial for designing effective analogues. Mutants F16L-hCT and F19L-hCT, where Phe residues in the core are replaced with Leu as in nonamyloidogenic salmon calcitonin, showed different aggregation kinetics. However, the molecular effects of these substitutions in hCT are still unclear. Here, we systematically investigated the folding and self-assembly conformational dynamics of hCT, F16L-hCT, and F19L-hCT through multiple long-time scale independent atomistic discrete molecular dynamics (DMD) simulations. Our results indicated that the hCT monomer primarily assumed unstructured conformations with dynamic helices around residues 4-12 and 14-21. During self-assembly, the amyloidogenic core of hCT14-21 converted from dynamic helices to β-sheets. However, substituting F16L did not induce significant conformational changes, as F16L-hCT exhibited characteristics similar to those of wild-type hCT in both monomeric and oligomeric states. In contrast, F19L-hCT exhibited substantially more helices and fewer β-sheets than did hCT, irrespective of their monomers or oligomers. The substitution of F19L significantly enhanced the stability of the helical conformation for hCT14-21, thereby suppressing the helix-to-β-sheet conformational conversion. Overall, our findings elucidate the molecular mechanisms underlying hCT aggregation and the effects of F16L and F19L substitutions on the conformational dynamics of hCT, highlighting the critical role of F19 as an important target in the design of amyloid-resistant hCT analogs for future clinical applications.

Modeling Flexible Protein Structure With AlphaFold2 and Crosslinking Mass Spectrometry

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

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

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

Computational insights into the cross-talk between medin and Aβ: implications for age-related vascular risk factors in Alzheimer's disease

The aggregation of medin forming aortic medial amyloid is linked to arterial wall degeneration and cerebrovascular dysfunction. Elevated levels of arteriolar medin are correlated with an increased presence of vascular amyloid-β (Aβ) aggregates, a hallmark of Alzheimer's disease (AD) and vascular dementia. The cross-interaction between medin and Aβ results in the formation of heterologous fibrils through co-aggregation and cross-seeding processes both in vitro and in vivo. However, a comprehensive molecular understanding of the cross-interaction between medin and Aβ-two intrinsically disordered proteins-is critically lacking. Here, we employed atomistic discrete molecular dynamics simulations to systematically investigate the self-association, co-aggregation and also the phenomenon of cross-seeding between these two proteins. Our results demonstrated that both Aβ and medin were aggregation prone and their mixture tended to form β-sheet-rich hetero-aggregates. The formation of Aβ-medin hetero-aggregates did not hinder Aβ and medin from recruiting additional Aβ and medin peptides to grow into larger β-sheet-rich aggregates. The β-barrel oligomer intermediates observed in the self-aggregations of Aβ and medin were also present during their co-aggregation. In cross-seeding simulations, preformed Aβ fibrils could recruit isolated medin monomers to form elongated β-sheets. Overall, our comprehensive simulations suggested that the cross-interaction between Aβ and medin may contribute to their pathological aggregation, given the inherent amyloidogenic tendencies of both medin and Aβ. Targeting medin, therefore, could offer a novel therapeutic approach to preserving brain function during aging and AD by improving vascular health.

Deciphering the influence of Y12L and N17H substitutions on the conformation and oligomerization of human calcitonin

The abnormal aggregation of human calcitonin (hCT) hormone peptides impairs their physiological function, leading to harmful immune responses and cytotoxicity, which limits their clinical utility. Interestingly, a representative hCT analog incorporating Y12L and N17H substitutions (DM-hCT) has shown reduced aggregation tendencies while maintaining bioactivity. But the molecular mechanism of Y12L and N17H substitutions on the conformational dynamics of hCT remains unclear. Here, we systematically investigated the folding and self-assembly dynamics of hCT and DM-hCT using atomistic discrete molecular dynamics (DMD) simulations. Our findings revealed that hCT monomers predominantly adopted unstructured conformations with dynamic helices. Oligomerization of hCT resulted in the formation of β-sheet-rich aggregates and β-barrel intermediates. The Y12L and N17H substitutions enhanced helical conformations and suppressed β-sheet formation in both monomers and oligomers. These substitutions stabilized the dynamic helices and disrupted aromatic interactions responsible for β-sheet formation at residue 12. Notably, DM-hCT assemblies still exhibited β-sheets in phenylalanine-rich and C-terminal hydrophobic regions, suggesting that future optimizations should focus on these areas. Our simulations provide insights into the molecular mechanisms underlying hCT aggregation and the amyloid-resistant effects of Y12L and N17H substitutions. These findings have valuable implications for the development of clinical hCT analogs.

Unveiling Medin Folding and Dimerization Dynamics and Conformations via Atomistic Discrete Molecular Dynamics Simulations

Medin is a principal component of localized amyloid found in the vasculature of individuals over 50 years old. Its amyloid aggregation has been linked to endothelial dysfunction and vascular inflammation, contributing to the pathogenesis of various vascular diseases. Despite its significance, the structures of the medin monomer, oligomer, and fibril remain elusive, and the dynamic processes of medin aggregation are not fully understood. In this study, we comprehensively investigated the medin folding and dimerization dynamics and conformations using atomistic discrete molecular dynamics simulations. Our simulation results suggested that the folding initiation of the medin involved the formation of β-sheets around medin30-41 and medin42-50, with subsequent capping of other segments to their β-sheet edges. Medin monomers typically consisted of three or four β-strands, along with a dynamic N-terminal helix. Two isolated medin peptides readily aggregated into a β-sheet-rich dimer, displaying a strong aggregation propensity. Dimerization of medin not only enhanced the β-sheet conformations but also led to the formation of β-barrel oligomers. The aggregation tendencies of medin1-18 and medin19-29 were relatively weak. However, the segments of medin30-41 and medin42-50 played a crucial role as they primarily formed a β-sheet core and facilitated medin1-18 and medin19-29 to form intra- and interpeptide β-sheets. The findings highlight the critical role of the medin30-41 and medin42-50 regions in stabilizing the monomer structure and driving the medin amyloid aggregation. These regions could potentially serve as promising targets for designing antiamyloid inhibitors against amyloid aggregation of medin. Additionally, our study provides a full picture of the monomer conformations and dimerization dynamics for medin, which will help better understand the pathology of medin aggregation.

Direct Observation of Seeded Conformational Conversion of hIAPP In Silico Reveals the Mechanisms for Morphological Dependence and Asymmetry of Fibril Growth

Rapid growth of amyloid fibrils via a seeded conformational conversion of monomers is a critical step of fibrillization and important for disease transmission and progression. Amyloid fibrils often display diverse morphologies with distinct populations, and yet the molecular mechanisms of fibril elongation and their corresponding morphological dependence remain poorly understood. Here, we computationally investigated the single-molecular growth of two experimentally resolved human islet amyloid polypeptide fibrils of different morphologies. In both cases, the incorporation of monomers into preformed fibrils was observed. The conformational conversion dynamics was characterized by a small number of fibril growth intermediates. Fibril morphology affected monomer binding at fibril elongation and lateral surfaces as well as the seeded conformational conversion dynamics at the fibril ends, resulting in different fibril elongation rates and populations. We also observed an asymmetric fibril growth as in our prior experiments, attributing to differences of two fibril ends in terms of their local surface curvatures and exposed hydrogen-bond donors and acceptors. Together, our mechanistic findings afforded a theoretical basis for delineating different amyloid strains-entailed divergent disease progression.

Determination of Protein Monoclonal-Antibody Epitopes by a Combination of Structural Proteomics Methods

Structural proteomics techniques are useful for the determination of protein interaction interfaces. Each technique provides orthogonal structural information on the structure and the location of protein interaction sites. Here, we have characterized a monoclonal antibody epitope for a protein antigen by a combination of differential photoreactive surface modification (SM), cross-linking (CL), differential hydrogen-deuterium exchange (HDX), and epitope extraction/excision. We found that experimental data from different approaches agree with each other in determining the epitope of the monoclonal antibody on the protein antigens using the HIV-1 p24-mAb E complex as an illustrative example. A combination of these multiple structural proteomics approaches results in a detailed picture of the interaction of the proteins and increases confidence in the determination of the final structure of the protein interaction interface. Data are available via ProteomeXchange with identifier PXD040902.

SEVI Inhibits Aβ Amyloid Aggregation by Capping the β-Sheet Elongation Edges

Inhibiting the aggregation of amyloid peptides with endogenous peptides has broad interest due to their intrinsically high biocompatibility and low immunogenicity. Here, we investigated the inhibition mechanism of the prostatic acidic phosphatase fragment SEVI (semen-derived enhancer of viral infection) against Aβ42 fibrillization using atomistic discrete molecular dynamic simulations. Our result revealed that SEVI was intrinsically disordered with dynamic formation of residual helices. With a high positive net charge, the self-aggregation tendency of SEVI was weak. Aβ42 had a strong aggregation propensity by readily self-assembling into β-sheet-rich aggregates. SEVI preferred to interact with Aβ42, rather than SEVI themselves. In the heteroaggregates, Aβ42 mainly adopted β-sheets buried inside and capped by SEVI in the outer layer. SEVI could bind to various Aβ aggregation species─including monomers, dimers, and proto-fibrils─by capping the exposed β-sheet elongation edges. The aggregation processes Aβ42 from the formation of oligomers to conformational nucleation into fibrils and fibril growth should be inhibited as their β-sheet elongation edges are being occupied by the highly charged SEVI. Overall, our computational study uncovered the molecular mechanism of experimentally observed inhibition of SEVI against Aβ42 aggregation, providing novel insights into the development of therapeutic strategies against Alzheimer's disease.

Dissecting the Self-assembly Dynamics of Imperfect Repeats in α-Synuclein

The pathological aggregation of α-synuclein (αS) into amyloid fibrils is the hallmark of Parkinson's disease (PD). The self-assembly and membrane interactions of αS are mainly governed by the seven imperfect 11-residue repeats of the XKTKEGVXXXX motif around residues 1-95. However, the particular role of each repeat in αS fibrillization remains unclear. To answer this question, we studied the aggregation dynamics of each repeat with up to 10 peptides in silico by conducting multiple independent micro-second atomistic discrete molecular dynamics simulations. Our simulations revealed that only repeats R3 and R6 readily self-assembled into β-sheet-rich oligomers, while the other repeats remained as unstructured monomers with weak self-assembly and β-sheet propensities. The self-assembly process of R3 featured frequent conformational changes with β-sheet formation mainly in the non-conserved hydrophobic tail, whereas R6 spontaneously self-assembled into extended and stable cross-β structures. These results of seven repeats are consistent with their structures and organization in recently solved αS fibrils. As the primary amyloidogenic core, R6 was buried inside the central cross-β core of all αS fibrils, attracting the hydrophobic tails of adjacent R4, R5, and R7 repeats forming β-sheets around R6 in the core. Further away from R6 in the sequence but with a moderate amyloid aggregation propensity, the R3 tail could serve as a secondary amyloidogenic core and form independent β-sheets in the fibril. Overall, our results demonstrate the critical role of R3 and R6 repeats in αS amyloid aggregation and suggest their potential as targets for the peptide-based and small-molecule amyloid inhibitors.

Determining the gas-phase structures of α-helical peptides from shape, microsolvation, and intramolecular distance data

Mass spectrometry is a powerful technique for the structural and functional characterization of biomolecules. However, it remains challenging to accurately gauge the gas-phase structure of biomolecular ions and assess to what extent native-like structures are maintained. Here we propose a synergistic approach which utilizes Förster resonance energy transfer and two types of ion mobility spectrometry (i.e., traveling wave and differential) to provide multiple constraints (i.e., shape and intramolecular distance) for structure-refinement of gas-phase ions. We add microsolvation calculations to assess the interaction sites and energies between the biomolecular ions and gaseous additives. This combined strategy is employed to distinguish conformers and understand the gas-phase structures of two isomeric α-helical peptides that might differ in helicity. Our work allows more stringent structural characterization of biologically relevant molecules (e.g., peptide drugs) and large biomolecular ions than using only a single structural methodology in the gas phase.

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.

Does AlphaFold2 model proteins' intracellular conformations? An experimental test using cross-linking mass spectrometry of endogenous ciliary proteins

A major goal in structural biology is to understand protein assemblies in their biologically relevant states. Here, we investigate whether AlphaFold2 structure predictions match native protein conformations. We chemically cross-linked proteins in situ within intact Tetrahymena thermophila cilia and native ciliary extracts, identifying 1,225 intramolecular cross-links within the 100 best-sampled proteins, providing a benchmark of distance restraints obeyed by proteins in their native assemblies. The corresponding structure predictions were highly concordant, positioning 86.2% of cross-linked residues within Cɑ-to-Cɑ distances of 30 Å, consistent with the cross-linker length. 43% of proteins showed no violations. Most inconsistencies occurred in low-confidence regions or between domains. Overall, AlphaFold2 predictions with lower predicted aligned error corresponded to more correct native structures. However, we observe cases where rigid body domains are oriented incorrectly, as for ciliary protein BBC118, suggesting that combining structure prediction with experimental information will better reveal biologically relevant conformations.

Structural and dynamic insights into α-synuclein dimer conformations

Parkinson disease is associated with the aggregation of the protein α-synuclein. While α-synuclein can exist in multiple oligomeric states, the dimer has been a subject of extensive debates. Here, using an array of biophysical approaches, we demonstrate that α-synuclein in vitro exhibits primarily a monomer-dimer equilibrium in nanomolar concentrations and up to a few micromolars. We then use spatial information from hetero-isotopic cross-linking mass spectrometry experiments as restrains in discrete molecular dynamics simulations to obtain the ensemble structure of dimeric species. Out of eight structural sub-populations of dimers, we identify one that is compact, stable, abundant, and exhibits partially exposed β-sheet structures. This compact dimer is the only one where the hydroxyls of tyrosine 39 are in proximity that may promote dityrosine covalent linkage upon hydroxyl radicalization, which is implicated in α-synuclein amyloid fibrils. We propose that this α-synuclein dimer features etiological relevance to Parkinson disease.

Zinc-Epigallocatechin-3-gallate Network-Coated Nanocomposites against the Pathogenesis of Amyloid-Beta

The aggregation of amyloid beta (Aβ) is a hallmark of Alzheimer's disease (AD), a major cause of dementia and an unmet challenge in modern medicine. In this study, we constructed a biocompatible metal-phenolic network (MPN) comprising a polyphenol epigallocatechin gallate (EGCG) scaffold coordinated by physiological Zn(II). Upon adsorption onto gold nanoparticles, the MPN@AuNP nanoconstruct elicited a remarkable potency against the amyloid aggregation and toxicity of Aβ in vitro. The superior performance of MPN@AuNP over EGCG@AuNP was attributed to the porosity and hence larger surface area of the MPN in comparison with that of EGCG alone. The atomic detail of Zn(II)-EGCG coordination was unraveled by density functional theory calculations and the structure and dynamics of Aβ aggregation modulated by the MPN were further examined by discrete molecular dynamics simulations. As MPN@AuNP also displayed a robust capacity to cross a blood-brain barrier model through the paracellular pathway, and given the EGCG's function as an anti-amyloidosis and antioxidation agent, this MPN-based strategy may find application in regulating the broad AD pathology beyond protein aggregation inhibition.

Structural Perturbation of Monomers Determines the Amyloid Aggregation Propensity of Calcitonin Variants

Human calcitonin (hCT) is a polypeptide hormone that participates in calcium-phosphorus metabolism. Irreversible aggregation of 32-amino acid hCT into β-sheet-rich amyloid fibrils impairs physiological activity and increases the risk of medullary carcinoma of the thyroid. Amyloid-resistant hCT derivatives substituting critical amyloidogenic residues are of particular interest for clinical applications as therapeutic drugs against bone-related diseases. Uncovering the aggregation mechanism of hCT at the molecular level, therefore, is important for the design of amyloid-resistant hCT analogues. Here, we investigated the aggregation dynamics of hCT, non-amyloidogenic salmon calcitonin (sCT), and two hCT analogues with reduced aggregation tendency─TL-hCT and phCT─using long timescale discrete molecular dynamics simulations. Our results showed that hCT monomers mainly adopted unstructured conformations with dynamically formed helices around the central region. hCT self-assembled into helix-rich oligomers first, followed by a conformational conversion into β-sheet-rich oligomers with β-sheets formed by residues 10-30 and stabilized by aromatic and hydrophobic interactions. Our simulations confirmed that TL-hCT and phCT oligomers featured more helices and fewer β-sheets than hCT. Substitution of central aromatic residues with leucine in TL-hCT and replacing C-terminal hydrophobic residue with hydrophilic amino acid in phCT only locally suppressed β-sheet propensities in the central region and C-terminus, respectively. Having mutations in both central and C-terminal regions, sCT monomers and dynamically formed oligomers predominantly adopted helices, confirming that both central aromatic and C-terminal hydrophobic residues played important roles in the fibrillization of hCT. We also observed the formation of β-barrel intermediates, postulated as the toxic oligomers in amyloidosis, for hCT but not for sCT. Our computational study depicts a complete picture of the aggregation dynamics of hCT and the effects of mutations. The design of next-generation amyloid-resistant hCT analogues should consider the impact on both amyloidogenic regions and also take into account the amplification of transient β-sheet population in monomers upon aggregation.

Improvements and new functionalities of UNRES server for coarse-grained modeling of protein structure, dynamics, and interactions

In this paper we report the improvements and extensions of the UNRES server (https://unres-server.chem.ug.edu.pl) for physics-based simulations with the coarse-grained UNRES model of polypeptide chains. The improvements include the replacement of the old code with the recently optimized one and adding the recent scale-consistent variant of the UNRES force field, which performs better in the modeling of proteins with the β and the α+β structures. The scope of applications of the package was extended to data-assisted simulations with restraints from nuclear magnetic resonance (NMR) and chemical crosslink mass-spectroscopy (XL-MS) measurements. NMR restraints can be input in the NMR Exchange Format (NEF), which has become a standard. Ambiguous NMR restraints are handled without expert intervention owing to a specially designed penalty function. The server can be used to run smaller jobs directly or to prepare input data to run larger production jobs by using standalone installations of UNRES.

Dynamic Interactomics by Cross-Linking Mass Spectrometry: Mapping the Daily Cell Life in Postgenomic Era

The majority of processes that occur in daily cell life are modulated by hundreds to thousands of dynamic protein-protein interactions (PPI). The resulting protein complexes constitute a tangled network that, with its continuous remodeling, builds up highly organized functional units. Thus, defining the dynamic interactome of one or more proteins allows determining the full range of biological activities these proteins are capable of. This conceptual approach is poised to gain further traction and significance in the current postgenomic era wherein the treatment of severe diseases needs to be tackled at both genomic and PPI levels. This also holds true for COVID-19, a multisystemic disease affecting biological networks across the biological hierarchy from genome to proteome to metabolome. In this overarching context and the current historical moment of the COVID-19 pandemic where systems biology increasingly comes to the fore, cross-linking mass spectrometry (XL-MS) has become highly relevant, emerging as a powerful tool for PPI discovery and characterization. This expert review highlights the advanced XL-MS approaches that provide in vivo insights into the three-dimensional protein complexes, overcoming the static nature of common interactomics data and embracing the dynamics of the cell proteome landscape. Many XL-MS applications based on the use of diverse cross-linkers, MS detection methods, and predictive bioinformatic tools for single proteins or proteome-wide interactions were shown. We conclude with a future outlook on XL-MS applications in the field of structural proteomics and ways to sustain the remarkable flexibility of XL-MS for dynamic interactomics and structural studies in systems biology and planetary health.

Molecular insights into the oligomerization dynamics and conformations of amyloidogenic and non-amyloidogenic amylin from discrete molecular dynamics simulations

The amyloid aggregation of human islet amyloid polypeptide (hIAPP) is associated with pancreatic β-cell death in type 2 diabetes. The S20G substitution of hIAPP (hIAPP(S20G)), found in Japanese and Chinese people, is more amyloidogenic and cytotoxic than wild-type hIAPP. Rat amylin (rIAPP) does not have aggregation propensity or cytotoxicity. Mounting evidence suggests that soluble low-molecular-weight amyloid oligomers formed during early aggregation are more cytotoxic than mature fibrils. The self-assembly dynamics and oligomeric conformations remain unknown because the oligomers are heterogeneous and transient. The molecular mechanism of sequence-variation rendering dramatically different aggregation propensity and cytotoxicity is also elusive. Here, we investigate the oligomerization dynamics and conformations of amyloidogenic hIAPP, hIAPP(S20G), and non-amyloidogenic rIAPP using atomistic discrete molecular dynamics (DMD) simulations. Our simulation results demonstrated that all three monomeric amylin peptides mainly adopted an unstructured formation with partial dynamical helices near the N-terminus. Relatively transient β-hairpins were more abundant in hIAPP and hIAPP(S20G) than in rIAPP. The S20G-substituting mutant of hIAPP altered the turn region of the β-hairpin motif, resulting in more hydrophobic residue-pairwise contacts within the β-hairpin. Oligomerization dynamic investigation revealed that all three peptides spontaneously accumulated into helix-populated oligomers. The conformational conversion to form β-sheet-rich oligomers was only observed in hIAPP and hIAPP(S20G). The population of high-β-sheet-content oligomers was enhanced by S20G substitution. Interestingly, both hIAPP and hIAPP(S20G) could form β-barrel formations, and the β-barrel propensity of hIAPP(S20G) was three times larger than that of hIAPP. No β-sheet-rich or β-barrel formations were observed in rIAPP. Our direct observation of the correlation between β-barrel oligomer formation and cytotoxicity suggests that β-barrels might play a critically important role in the cytotoxicity of amyloidosis.

Structural Studies of a Stapled Peptide with Native Ion Mobility-Mass Spectrometry and Transition Metal Ion Förster Resonance Energy Transfer in the Gas Phase

Native mass spectrometry has emerged as an important tool for gas-phase structural biology. However, the conformations that a biomolecular ion adopts in the gas phase can differ from those found in solution. Herein, we report a synergistic, native ion mobility-mass spectrometry (IM-MS) and transition metal ion Förster resonance energy transfer (tmFRET)-based approach to probe the gas-phase ion structures of a nonstapled peptide (nsp; Ac-CAARAAHAAAHARARA-NH₂) and a stapled peptide (sp; Ac-CXARAXHAAAHARARA-NH₂). The stapled peptide contains a single hydrocarbon chain connecting the peptide backbone in the i and i + 4 positions via a Grubbs ring-closure metathesis. Fluorescence lifetime measurements indicated that the Cu-bound complexes of carboxyrhodamine 6g (crh6g)-labeled stapled peptide (sp-crh6g) had a shorter donor-acceptor distance (r_DA) than the labeled nonstapled peptide (nsp-crh6g). Experimental collision cross-section (CCS) values were then determined by native IM-MS, which could separate the conformations of Cu-bound complexes of nsp-crh6g and sp-crh6g. Finally, the experimental CCS (i.e., shape) and r_DA (i.e., distance) values were used as constraints for computational studies, which unambiguously revealed how a staple reduces the elongation of the peptide ions in the gas phase. This study demonstrates the superiority of combining native IM-MS, tmFRET, and computational studies to investigate the structure of biomolecular ions.

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.

Graphene quantum dots obstruct the membrane axis of Alzheimer's amyloid beta

Alzheimer's disease (AD) is a primary form of dementia with debilitating consequences, but no effective cure is available. While the pathophysiology of AD remains multifactorial, the aggregation of amyloid beta (Aβ) mediated by the cell membrane is known to be the cause for the neurodegeneration associated with AD. Here we examined the effects of graphene quantum dots (GQDs) on the obstruction of the membrane axis of Aβ in its three representative forms of monomers (Aβ-m), oligomers (Aβ-o), and amyloid fibrils (Aβ-f). Specifically, we determined the membrane fluidity of neuroblastoma SH-SY5Y cells perturbed by the Aβ species, especially by the most toxic Aβ-o, and demonstrated their recovery by GQDs using confocal fluorescence microscopy. Our computational data through discrete molecular dynamics simulations further revealed energetically favorable association of the Aβ species with the GQDs in overcoming peptide-peptide aggregation. Overall, this study positively implicated GQDs as an effective agent in breaking down the membrane axis of Aβ, thereby circumventing adverse downstream events and offering a potential therapeutic solution for AD.

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.

Integrative structural dynamics probing of the conformational heterogeneity in synaptosomal-associated protein 25

SNAP-25 (synaptosomal-associated protein of 25 kDa) is a prototypical intrinsically disordered protein (IDP) that is unstructured by itself but forms coiled-coil helices in the SNARE complex. With high conformational heterogeneity, detailed structural dynamics of unbound SNAP-25 remain elusive. Here, we report an integrative method to probe the structural dynamics of SNAP-25 by combining replica-exchange discrete molecular dynamics (rxDMD) simulations and label-based experiments at ensemble and single-molecule levels. The rxDMD simulations systematically characterize the coil-to-molten globular transition and reconstruct structural ensemble consistent with prior ensemble experiments. Label-based experiments using Förster resonance energy transfer and double electron-electron resonance further probe the conformational dynamics of SNAP-25. Agreements between simulations and experiments under both ensemble and single-molecule conditions allow us to assign specific helix-coil transitions in SNAP-25 that occur in submillisecond timescales and potentially play a vital role in forming the SNARE complex. We expect that this integrative approach may help further our understanding of IDPs.

Structure of prion β-oligomers as determined by short-distance crosslinking constraint-guided discrete molecular dynamics simulations

The conversion of the native monomeric cellular prion protein (PrP^C ) into an aggregated pathological β-oligomeric form (PrP^β ) and an infectious form (PrP^Sc ) is the central element in the development of prion diseases. The structure of the aggregates and the molecular mechanisms of the conformational changes involved in the conversion are still unknown. We applied mass spectrometry combined with chemical crosslinking, hydrogen/deuterium exchange, limited proteolysis, and surface modification for the differential characterization of the native and the urea+acid-converted prion β-oligomer structures to obtain insights into the mechanisms of conversion and aggregation. For the determination of the structure of the monomer and the dimer unit of the β-oligomer, we applied a recently-developed approach for de novo protein structure determination which is based on the incorporation of zero-length and short-distance crosslinking data as intra- and inter-protein constraints in discrete molecular dynamics simulations (CL-DMD). Based on all of the structural-proteomics experimental data and the computationally predicted structures of the monomer units, we propose the potential mode of assembly of the β-oligomer. The proposed β-oligomer assembly provides a clue on the β-sheet nucleation site, and how template-based conversion of the native prion molecule occurs, growth of the prion aggregates, and maturation into fibrils may occur.

The structural heterogeneity of α-synuclein is governed by several distinct subpopulations with interconversion times slower than milliseconds

α-Synuclein plays an important role in synaptic functions by interacting with synaptic vesicle membrane, while its oligomers and fibrils are associated with several neurodegenerative diseases. The specific monomer structures that promote its membrane binding and self-association remain elusive due to its transient nature as an intrinsically disordered protein. Here, we use inter-dye distance distributions from bulk time-resolved Förster resonance energy transfer as restraints in discrete molecular dynamics simulations to map the conformational space of the α-synuclein monomer. We further confirm the generated conformational ensemble in orthogonal experiments utilizing far-UV circular dichroism and cross-linking mass spectrometry. Single-molecule protein-induced fluorescence enhancement measurements show that within this conformational ensemble, some of the conformations of α-synuclein are surprisingly stable, exhibiting conformational transitions slower than milliseconds. Our comprehensive analysis of the conformational ensemble reveals essential structural properties and potential conformations that promote its various functions in membrane interaction or oligomer and fibril formation.

Spontaneous Formation of β-sheet Nano-barrels during the Early Aggregation of Alzheimer's Amyloid Beta

Soluble low-molecular-weight oligomers formed during the early aggregation of amyloid peptides have been hypothesized as a major toxic species of amyloidogenesis. Herein, we performed the first synergic in silico, in vitro and in vivo validations of the structure, dynamics and toxicity of Aβ42 oligomers. Aβ peptides readily assembled into β-rich oligomers comprised of extended β-hairpins and β-strands. Nanosized β-barrels were observed with certainty with simulations, transmission electron microscopy and Fourier transform infrared spectroscopy, corroborated by immunohistochemistry, cell viability, apoptosis, inflammation, autophagy and animal behavior assays. Secondary and tertiary structural proprieties of these oligomers, such as the sequence regions with high β-sheet propensities and inter-residue contact frequency patterns, were similar to the properties known for Aβ fibrils. The unambiguous spontaneous formation of β-barrels in the early aggregation of Aβ42 supports their roles as the common toxic intermediates in Alzheimer's pathobiology and a target for Alzheimer's therapeutics.

Misfolding and Self-Assembly Dynamics of Microtubule-Binding Repeats of the Alzheimer-Related Protein Tau

Pathological aggregation of intrinsically disordered tau protein, driven by the interactions between microtubule-binding (MTB) domains, is associated with Alzheimer's disease. The MTB domain contains either three or four repeats with sequence similarities. Compared to amyloid β, many aspects of the misfolding and aggregation mechanisms of tau are largely unknown. In this study, we systematically investigated the dynamics of monomer misfolding and dimerization of each MTB repeat using atomistic discrete molecular dynamic simulations. Our results revealed that all the four repeat monomers (R1-R4) were very dynamic, featuring frequent conformational conversion and lacking stable conformations. While R1, R2, and R4 monomers occasionally adopted partially helical conformations, R3 monomers frequently formed β-sheets. In dimerization simulations, R3 displayed the strongest aggregation propensity with high β-sheet contents, while R1 was the least prone to aggregation. The R2 and R4 dimers contained both helix and β-sheet structures. The β-sheets in R4 assemblies were dominant with β-hairpin conformation. In R2 and R3 dimers, intermolecular β-sheets were mainly driven by residues around the paired helical filament (PHF) regions. Residues around the PHF6* in R2 and PHF6 in R3 had significantly higher intermolecular contacts than other regions, suggesting that these residues play a key role in the amyloid aggregation of tau. Our results on the structural ensembles and early aggregation dynamics of each tau MTB repeat will help understand the nucleation and fibrillization of tau.

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.

Protein Structure Prediction from NMR Hydrogen-Deuterium Exchange Data

Amide hydrogen-deuterium exchange (HDX) has long been used to determine regional flexibility and binding sites in proteins; however, the data are too sparse for full structural characterization. Experiments that measure HDX rates, such as HDX-NMR, have far higher throughput compared to structure determination via X-ray crystallography, cryo-EM, or a full suite of NMR experiments. Data from HDX-NMR experiments encode information on the protein structure, making HDX a prime candidate to be supplemented by computational algorithms for protein structure prediction. We have developed a methodology to incorporate HDX-NMR data into ab initio protein structure prediction using the Rosetta software framework to predict structures based on experimental agreement. To demonstrate the efficacy of our algorithm, we examined 38 proteins with HDX-NMR data available, comparing the predicted model with and without the incorporation of HDX data into scoring. The root-mean-square deviation (rmsd, a measure of the average atomic distance between superimposed models) of the predicted model improved by 1.42 Å on average after incorporating the HDX-NMR data into scoring. The average rmsd improvement for the proteins where the selected model rmsd changed after incorporating HDX data was 3.63 Å, including one improvement of more than 11 Å and seven proteins improving by greater than 4 Å, with 12/15 proteins improving overall. Additionally, for independent verification, two proteins that were not part of the original benchmark were scored including HDX data, with a dramatic improvement of the selected model rmsd of nearly 9 Å for one of the proteins. Moreover, we have developed a confidence metric allowing us to successfully identify near-native models in the absence of a native structure. Improvement in model selection with a strong confidence measure demonstrates that protein structure prediction with HDX-NMR is a powerful tool which can be performed with minimal additional computational strain and expense.

FRET-based dynamic structural biology: Challenges, perspectives and an appeal for open-science practices

Single-molecule FRET (smFRET) has become a mainstream technique for studying biomolecular structural dynamics. The rapid and wide adoption of smFRET experiments by an ever-increasing number of groups has generated significant progress in sample preparation, measurement procedures, data analysis, algorithms and documentation. Several labs that employ smFRET approaches have joined forces to inform the smFRET community about streamlining how to perform experiments and analyze results for obtaining quantitative information on biomolecular structure and dynamics. The recent efforts include blind tests to assess the accuracy and the precision of smFRET experiments among different labs using various procedures. These multi-lab studies have led to the development of smFRET procedures and documentation, which are important when submitting entries into the archiving system for integrative structure models, PDB-Dev. This position paper describes the current 'state of the art' from different perspectives, points to unresolved methodological issues for quantitative structural studies, provides a set of 'soft recommendations' about which an emerging consensus exists, and lists openly available resources for newcomers and seasoned practitioners. To make further progress, we strongly encourage 'open science' practices.

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.

Amyloid Oligomers: A Joint Experimental/Computational Perspective on Alzheimer's Disease, Parkinson's Disease, Type II Diabetes, and Amyotrophic Lateral Sclerosis

Protein misfolding and aggregation is observed in many amyloidogenic diseases affecting either the central nervous system or a variety of peripheral tissues. Structural and dynamic characterization of all species along the pathways from monomers to fibrils is challenging by experimental and computational means because they involve intrinsically disordered proteins in most diseases. Yet understanding how amyloid species become toxic is the challenge in developing a treatment for these diseases. Here we review what computer, in vitro, in vivo, and pharmacological experiments tell us about the accumulation and deposition of the oligomers of the (Aβ, tau), α-synuclein, IAPP, and superoxide dismutase 1 proteins, which have been the mainstream concept underlying Alzheimer's disease (AD), Parkinson's disease (PD), type II diabetes (T2D), and amyotrophic lateral sclerosis (ALS) research, respectively, for many years.

Prefusion spike protein stabilization through computational mutagenesis

A novel severe acute respiratory syndrome (SARS)‐like coronavirus (SARS‐CoV‐2) has emerged as a human pathogen, causing global pandemic and resulting in over 400 000 deaths worldwide. The surface spike protein of SARS‐CoV‐2 mediates the process of coronavirus entry into human cells by binding angiotensin‐converting enzyme 2 (ACE2). Due to the critical role in viral‐host interaction and the exposure of spike protein, it has been a focus of most vaccines' developments. However, the structural and biochemical studies of the spike protein are challenging because it is thermodynamically metastable. Here, we develop a new pipeline that automatically identifies mutants that thermodynamically stabilize the spike protein. Our pipeline integrates bioinformatics analysis of conserved residues, motion dynamics from molecular dynamics simulations, and other structural analysis to identify residues that significantly contribute to the thermodynamic stability of the spike protein. We then utilize our previously developed protein design tool, Eris, to predict thermodynamically stabilizing mutations in proteins. We validate the ability of our pipeline to identify protein stabilization mutants through known prefusion spike protein mutants. We finally utilize the pipeline to identify new prefusion spike protein stabilization mutants.

αB-Crystallin Chaperone Inhibits Aβ Aggregation by Capping the β-Sheet-Rich Oligomers and Fibrils

Inhibiting the cytotoxicity of amyloid aggregation by endogenous proteins is a promising strategy against degenerative amyloid diseases due to their intrinsically high biocompatibility and low immunogenicity. In this study, we investigated the inhibition mechanism of the structured core region of αB-crystallin (αBC) against Aβ fibrillization using discrete molecular dynamics simulations. Our computational results recapitulated the experimentally observed Aβ binding sites in αBC and suggested that αBC could bind to various Aβ aggregate species during the aggregation process-including monomers, dimers, and likely other high molecular weight oligomers, protofibrils, and fibrils-by capping the exposed β-sheet elongation surfaces. Thus, the nucleation of Aβ oligomers into fibrils and the fibril growth could be inhibited. Mechanistic insights obtained from our systematic computational studies may aid in the development of novel therapeutic strategies to modulate the aggregation of pathological, amyloidogenic protein in degenerative diseases.

Combining Experimental Data and Computational Methods for the Non-Computer Specialist

Experimental methods are indispensable for the study of the function of biological macromolecules, not just as static structures, but as dynamic systems that change conformation, bind partners, perform reactions, and respond to different stimulus. However, providing a detailed structural interpretation of the results is often a very challenging task. While experimental and computational methods are often considered as two different and separate approaches, the power and utility of combining both is undeniable. The integration of the experimental data with computational techniques can assist and enrich the interpretation, providing new detailed molecular understanding of the systems. Here, we briefly describe the basic principles of how experimental data can be combined with computational methods to obtain insights into the molecular mechanism and expand the interpretation through the generation of detailed models.

THE USE OF MASS SPECTROMETRY TO STUDY ZN-METALLOPROTEASE-SUBSTRATE INTERACTIONS

Zinc metalloproteases (ZnMPs) participate in diverse biological reactions, encompassing the synthesis and degradation of all the major metabolites in living organisms. In particular, ZnMPs have been recognized to play a very important role in controlling the concentration level of several peptides and/or proteins whose homeostasis has to be finely regulated for the correct physiology of cells. Dyshomeostasis of aggregation-prone proteins causes pathological conditions and the development of several different diseases. For this reason, in recent years, many analytical approaches have been applied for studying the interaction between ZnMPs and their substrates and how environmental factors can affect enzyme activities. In this scenario, mass spectrometric methods occupy a very important role in elucidating different aspects of ZnMPs-substrates interaction. These range from identification of cleavage sites to quantitation of kinetic parameters. In this work, an overview of all the main achievements regarding the application of mass spectrometric methods to investigating ZnMPs-substrates interactions is presented. A general experimental protocol is also described which may prove useful to the study of similar interactions. © 2020 John Wiley & Sons Ltd. Mass Spec Rev.

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.

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.

Evaluating the performance of an ETD-cleavable cross-linking strategy for elucidating protein structures

Chemical cross-linking is a powerful strategy for elucidating the structures of protein or protein complexes. The distance constraints obtained from cross-linked peptides represent the three-dimensional structures of the protein complexes. Unfortunately, structural analysis using cross-linking approach demands a significant amount of data to elucidate protein structures. This requires the development of several cleavable cross-linkers with different range of spacer chains. An Electron Transfer Dissociation (ETD) tandem mass spectrometry cleavable bond hydrazone was reported. Its fragmentation with conjugated peptides showed promise for the development of a new ETD cleavable cross-linker. However, no cross-linker was developed utilizing this ETD cleavable bond. For the first time, we attempted to develop an ETD cleavable cross-linker utilizing a hydrazone bond. We overcome the pitfall for the synthesis of this cross-linker and an easy synthesis scheme is reported. In this report, we evaluated the performance of this cross-linker called Hydrazone Incorporated ETD cleavable cross-linker (HI-ETD-XL) in model peptides and proteins. The characteristic fragmentation behavior of HI-ETD-XL during electron transfer dissociation and subsequent sequence identification of the peptide fragment ions by tandem mass spectrometry allowed the identification of cross-linked peptides unambiguously. We believe the availability of this ETD cleavable cross-linker will advance structural proteomics research significantly. SIGNIFICANCE: Many cellular processes rely on the structural dynamics of protein complexes. The detailed knowledge of the structure and dynamics of protein complexes is crucial for understanding their biological functions and regulations. However, most of the structure of these multiprotein entities remain uncharacterized and sometimes is very challenging to reveal with biophysical techniques alone. Chemical cross-linking combined with mass spectrometry (MS) has proven to be a dependable strategy in structural proteomics field. However, data complexity and false identifications are significant hindrances for unambiguous identification of cross-linked peptides. Confident identifications demand structural studies with cross-linkers with different properties and variable spacer chain lengths. This new ETD cleavable cross-linking workflow will provide additional confidence to overcome these drawbacks and allow us to pinpoint cross-linked peptides confidently.

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.

Thermo- and pH-responsive fibrillization of squid suckerin A1H1 peptide

Stimuli-responsive smart materials have attracted considerable attention with numerous applications in nanotechnology, sensing, and biomedicine. Suckerin family proteins found in squid ring teeth represent such a class of peptide-based smart materials with their self-assemblies featuring excellent thermo-plasticity and pH-dependence. Similar to block copolymers, suckerin proteins are comprised of two repeating sequence motifs, where M1 motifs are abundant in alanine and histidine residues and M2 are rich in glycine. Experimental studies of suckerin assemblies suggested that M1 regions mainly formed nano-confined β-sheets within an amorphous matrix made of M2 modules stabilizing these β-rich nano-assemblies. The histidine-containing M1 modules are believed to govern the pH- and temperature-sensitive properties of suckerin assemblies. To better understand the stimuli-responsive properties of suckerin assemblies at the molecular level, we systematically studied the self-assembly dynamics of A1H1 peptides - a representative M1 sequence - at different temperatures and pH conditions with atomistic discrete molecular dynamic simulations. Our simulations with twenty A1H1 peptides demonstrated that below the transition temperature Tagg, they could readily self-assemble from isolated monomers into well-defined β-sheet nanostructures by both primary and secondary nucleation of β-sheets and subsequent aggregation growth via elongation and coagulation. Interestingly, the dissociation of pre-formed A1H1 β-sheet nanostructures featured a melting temperature Tm higher than Tagg, exhibiting the thermal hysteresis that is characteristic of first-order phase transitions with high energy barriers. In acidic environments where all histidine residues were protonated, the stability of the A1H1 β-sheet nano-assemblies was reduced and the β-rich assemblies easily dissociated into unstructured monomers at significantly lower temperatures than in the neutral solution. The computationally derived molecular mechanisms for pH- and temperature-dependent A1H1 self-assembly will help to understand the supramolecular assembly structures and functions of the large suckerin family and aid in the future design of peptide-based stimuli-responsive smart materials.

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.

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.

On the necessity of an integrative approach to understand protein structural dynamics

Proteins are dynamic, fluctuating between multiple conformational states. Protein dynamics, spanning orders of magnitude in time and space, allow proteins to perform specific functions. Moreover, under certain conditions, proteins can morph into a different set of conformations. Thus, a complete understanding of protein structural dynamics can provide mechanistic insights into protein function. Here, we review the latest developments in methods used to determine protein ensemble structures and to characterize protein dynamics. Techniques including X-ray crystallography, cryogenic electron microscopy, and small angle scattering can provide structural information on specific conformational states or on the averaged shape of the protein, whereas techniques including nuclear magnetic resonance, fluorescence resonance energy transfer (FRET), and chemical cross-linking coupled with mass spectrometry provide information on the fluctuation of the distances between protein domains, residues, and atoms for the multiple conformational states of the protein. In particular, FRET measurements at the single-molecule level allow rapid resolution of protein conformational states, where information is otherwise obscured in bulk measurements. Taken together, the different techniques complement each other and their integrated use can offer a clear picture of protein structure and dynamics.

An Integrated Approach for Determining a Protein-Protein Binding Interface in Solution and an Evaluation of Hydrogen-Deuterium Exchange Kinetics for Adjudicating Candidate Docking Models

We describe an integrated approach of using hydrogen-deuterium exchange mass spectrometry (HDX-MS), chemical cross-linking mass spectrometry (XL-MS), and molecular docking to characterize the binding interface and to predict the three-dimensional quaternary structure of a protein-protein complex in solution. Interleukin 7 (IL-7) and its α-receptor, IL-7Rα, serving as essential mediators in the immune system, are the model system. HDX kinetics reports widespread protection on IL-7Rα but shows no differential evidence of binding-induced protection or remote conformational change. Cross-linking with reagents that differ in spacer lengths and targeting residues increases the spatial resolution. Using five cross-links as distance restraints for protein-protein docking, we generated a high-confidence model of the IL-7/IL-7Rα complex. Both the predicted binding interface and regions with direct contacts agree well with those in the solid-state structure, as confirmed by previous X-ray crystallography. An additional binding region was revealed to be the C-terminus of helix B of IL-7, highlighting the value of solution-based characterization. To generalize the integrated approach, protein-protein docking was executed with a different number of cross-links. Combining cluster analysis and HDX kinetics adjudication, we found that two intermolecular cross-link-derived restraints are sufficient to generate a high-confidence model with root-mean-square distance (rmsd) value of all alpha carbons below 2.0 Å relative to the crystal structure. The remarkable results of binding-interface determination and quaternary structure prediction highlight the effectiveness and capability of the integrated approach, which will allow more efficient and comprehensive analysis of interprotein interactions with broad applications in the multiple stages of design, implementation, and evaluation for protein therapeutics.

Structural complementarity of distance constraints obtained from chemical cross-linking and amino acid coevolution

The analysis of amino acid coevolution has emerged as a practical method for protein structural modeling by providing structural contact information from alignments of amino acid sequences. In parallel, chemical cross-linking/mass spectrometry (XLMS) has gained attention as a universally applicable method for obtaining low-resolution distance constraints to model the quaternary arrangements of proteins, and more recently even protein tertiary structures. Here, we show that the structural information obtained by XLMS and coevolutionary analysis are effectively complementary: the distance constraints obtained by each method are almost exclusively associated with non-coincident pairs of residues, and modeling results obtained by the combination of both sets are improved relative to considering the same total number of constraints of a single type. The structural rationale behind the complementarity of the distance constraints is discussed and illustrated for a representative set of proteins with different sizes and folds.