Protein Conformational States Research Articles

Response of Foldable Protein Conformations to Non-physiological Perturbations: Interplay of Thermal Factors and Confinement.

Technological advances frequently interface biomolecules with nanomaterials at non-physiological conditions, necessitating response characterization of key processes. Similar encounters are expected in cellular contexts. We report in silico investigations of the response of diverse protein conformational states to lowering of temperature and imposition of spatial constraints. Conformational states are represented by folded form of the Albumin binding domain (ABD) protein, its compact denatured form, and structurally disordered nascent folding elements. Data from extensive simulations are evaluated to elicit structural, thermodynamic and dynamic responses of the states and their associated environment. Analyses reveal alterations to folding propensity with reduced thermal energy and confinement, with signatures of trend reversal in highly disordered states. Across temperatures, confinement has restrictive effects on volume and energetic fluctuations, leading to narrowing of differences in isothermal compressibility (κ) and heat capacities (Cp). While excess (over ideal gas) entropy of the hydration layer marks dependence on the conformational state at bulk, confinement triggers erasure of differences. These observations are largely consistent with timescales of protein-water hydrogen bonding dynamics. The results implicate multi-factorial associations within a simple bio-nano complex. We expect the current study to motivate investigations of more biologically relevant interfaces towards mechanistic understanding and potential applications.

L-serine deficiency: on the properties of the Asn133Ser variant of human phosphoserine phosphatase

The non-essential amino acid L-serine is involved in a number of metabolic pathways and in the brain its level is largely due to the biosynthesis from the glycolytic intermediate D-3-phosphoglycerate by the phosphorylated pathway (PP). This cytosolic pathway is made by three enzymes proposed to generate a reversible metabolon named the “serinosome”. Phosphoserine phosphatase (PSP) catalyses the last and irreversible step, representing the driving force pushing L-serine synthesis. Genetic defects of the PP enzymes result in strong neurological phenotypes. Recently, we identified the homozygous missense variant [NM_004577.4: c.398A > G p.(Asn133Ser)] in the PSPH, the PSP encoding gene, in two siblings with a neurodevelopmental syndrome and a myelopathy. The recombinant Asn133Ser enzyme does not show significant alterations in protein conformation and dimeric oligomerization state, as well as in enzymatic activity and functionality of the reconstructed PP. However, the Asn133Ser variant is less stable than wild-type PSP, a feature also apparent at cellular level. Studies on patients’ fibroblasts also highlight a strong decrease in the level of the enzymes of the PP, a partial nuclear and perinuclear localization of variant PSP and a stronger perinuclear aggregates formation. We propose that these alterations contribute to the formation of a dysfunctional serinosome and thus to the observed reduction of L-serine, glycine and D-serine levels (the latter playing a crucial role in modulating NMDA receptors). The characterization of patients harbouring the Asn133Ser PSP substitution allows to go deep into the molecular mechanisms related to L-serine deficit and to suggest treatments to cope with the observed amino acids alterations.

Molecular dynamics simulations of lipid-protein interactions in SLC4 proteins

The SLC4 family of secondary bicarbonate transporters is responsible for the transport of HCO3−, CO32−, Cl−, Na+, K+, NH3, and H+, which are necessary for regulation of pH and ion homeostasis. They are widely expressed in numerous tissues throughout the body and function in different cell types with different membrane properties. Potential lipid roles in SLC4 function have been reported in experimental studies, focusing mostly on two members of the family: AE1 (Cl−/HCO3− exchanger) and NBCe1 (Na+-CO32−cotransporter). Previous computational studies of the outward-facing state of AE1 with model lipid membranes revealed enhanced protein-lipid interactions between cholesterol (CHOL) and phosphatidylinositol bisphosphate (PIP2). However, the protein-lipid interactions in other members of the family and other conformation states are still poorly understood and this precludes the detailed studies of a potential regulatory role for lipids in the SLC4 family. In this work, we performed coarse-grained and atomistic molecular dynamics simulations on three members of the SLC4 family with different transport modes: AE1, NBCe1, and NDCBE (an Na+-CO32−/Cl− exchanger), in model HEK293 membranes consisting of CHOL, PIP2, phosphatidylcholine, phosphatidylethanolamine, phosphatidylserine, and sphingomyelin. The recently resolved inward-facing state of AE1 was also included in the simulations. Lipid-protein contact analysis of the simulated trajectories was performed with the ProLint server, which provides a multitude of visualization tools for illustration of areas of enhanced lipid-protein contact and identification of putative lipid binding sites within the protein matrix. We observed enrichment of CHOL and PIP2 around all proteins with subtle differences in their distribution depending on the protein type and conformation state. Putative binding sites were identified for CHOL, PIP2, phosphatidylcholine, and sphingomyelin in the three studied proteins, and their potential roles in the SLC4 transport function, conformational transition, and protein dimerization are discussed.

Identifying protein conformational states in the Protein Data Bank: Toward unlocking the potential of integrative dynamics studies

Studying protein dynamics and conformational heterogeneity is crucial for understanding biomolecular systems and treating disease. Despite the deposition of over 215 000 macromolecular structures in the Protein Data Bank and the advent of AI-based structure prediction tools such as AlphaFold2, RoseTTAFold, and ESMFold, static representations are typically produced, which fail to fully capture macromolecular motion. Here, we discuss the importance of integrating experimental structures with computational clustering to explore the conformational landscapes that manifest protein function. We describe the method developed by the Protein Data Bank in Europe – Knowledge Base to identify distinct conformational states, demonstrate the resource's primary use cases, through examples, and discuss the need for further efforts to annotate protein conformations with functional information. Such initiatives will be crucial in unlocking the potential of protein dynamics data, expediting drug discovery research, and deepening our understanding of macromolecular mechanisms.

Correlations of dynamic changes in lipid and protein of salted large yellow croaker during storage

Protein and lipid are two major components that undergo significant changes during processing of aquatic products. This study focused on the protein oxidation, protein conformational states, lipid oxidation and lipid molecule profiling of salted large yellow croaker during storage, and their correlations were investigated. The degree of oxidation of protein and lipid was time-dependent, leading to an increase in carbonyl content and surface hydrophobicity, a decrease in sulfhydryl groups, and an increase in conjugated diene, peroxide value and thiobarbituric acid reactive substances value. Oxidation caused protein structure denaturation and aggregation during storage. Lipid composition and content changed dynamically, with polyunsaturated phosphatidylcholine (PC) was preferentially oxidized compared to polyunsaturated triacylglycerol. Correlation analysis showed that the degradation of polyunsaturated key differential lipids (PC 18:2_20:5, PC 16:0_22:6, PC 16:0_20:5, etc.) was closely related to the oxidation of protein and lipid. The changes in protein conformation and the peroxidation of polyunsaturated lipids mutually promote each other’s oxidation process.

Investigating direct current potentials that affect native protein conformation during trapped ion mobility spectrometry-mass spectrometry.

Trapped ion mobility spectrometry-time-of-flight mass spectrometry (TIMS-TOFMS) has emerged as a tool to study protein conformational states. In TIMS, gas-phase ions are guided across the IM stages by applying direct current (DC) potentials (D1-6), which, however, might induce changes in protein structures through collisional activation. To define conditions for native protein analysis, we evaluated the influence of these DC potentials using the metalloenzyme bovine carbonic anhydrase (BCA) as primary test compound. The variation of DC potentials did not change BCA-ion charge and heme content but affected (relative) charge-state intensities and adduct retention. Constructed extracted-ion mobilograms and corresponding collisional cross-section (CCS) profiles gave useful insights in (alterations of) protein conformational state. For BCA, the D3 and D6 potential (which are applied between the deflection transfer and funnel 1 [F1] and the accumulation exit and the start of the ramp, respectively) had most profound effects, showing multimodal CCS distributions at higher potentials indicating gradual unfolding. The other DC potentials only marginally altered the CCS profiles of BCA. To allow for more general conclusions, five additional proteins of diverse molecular weight and conformational stability were analyzed, and for the main protein charge states, CCS profiles were constructed. Principal component analysis (PCA) of the obtained data showed that D1 and D3 exhibit the highest degree of correlation with the ratio of folded and unfolded protein (F/U) as extracted from the mobilograms obtained per set D potential. The correlation of D6 with F/U and protein charge were similar, and D2, D4, and D5 showed an inverse correlation with F/U but were correlated with protein charge. Although DC boundary values for induced conformational changes appeared protein dependent, a set of DC values could be determined, which assured native analysis of most proteins.

PopShift: A Thermodynamically Sound Approach to Estimate Binding Free Energies by Accounting for Ligand-Induced Population Shifts from a Ligand-Free Markov State Model.

Obtaining accurate binding free energies from in silico screens has been a long-standing goal for the computational chemistry community. However, accuracy and computational cost are at odds with one another, limiting the utility of methods that perform this type of calculation. Many methods achieve massive scale by explicitly or implicitly assuming that the target protein adopts a single structure, or undergoes limited fluctuations around that structure, to minimize computational cost. Others simulate each protein-ligand complex of interest, accepting lower throughput in exchange for better predictions of binding affinities. Here, we present the PopShift framework for accounting for the ensemble of structures a protein adopts and their relative probabilities. Protein degrees of freedom are enumerated once, and then arbitrarily many molecules can be screened against this ensemble. Specifically, we use Markov state models (MSMs) as a compressed representation of a protein's thermodynamic ensemble. We start with a ligand-free MSM and then calculate how addition of a ligand shifts the populations of each protein conformational state based on the strength of the interaction between that protein conformation and the ligand. In this work we use docking to estimate the affinity between a given protein structure and ligand, but any estimator of binding affinities could be used in the PopShift framework. We test PopShift on the classic benchmark pocket T4 Lysozyme L99A. We find that PopShift is more accurate than common strategies, such as docking to a single structure and traditional ensemble docking─producing results that compare favorably with alchemical binding free energy calculations in terms of RMSE but not correlation─and may have a more favorable computational cost profile in some applications. In addition to predicting binding free energies and ligand poses, PopShift also provides insight into how the probability of different protein structures is shifted upon addition of various concentrations of ligand, providing a platform for predicting affinities and allosteric effects of ligand binding. Therefore, we expect PopShift will be valuable for hit finding and for providing insight into phenomena like allostery.

Enhancing Hit Discovery in Virtual Screening through Absolute Protein-Ligand Binding Free-Energy Calculations.

In the hit identification stage of drug discovery, a diverse chemical space needs to be explored to identify initial hits. Contrary to empirical scoring functions, absolute protein-ligand binding free-energy perturbation (ABFEP) provides a theoretically more rigorous and accurate description of protein-ligand binding thermodynamics and could, in principle, greatly improve the hit rates in virtual screening. In this work, we describe an implementation of an accurate and reliable ABFEP method in FEP+. We validated the ABFEP method on eight congeneric compound series binding to eight protein receptors including both neutral and charged ligands. For ligands with net charges, the alchemical ion approach is adopted to avoid artifacts in electrostatic potential energy calculations. The calculated binding free energies correlate with experimental results with a weighted average of R2 = 0.55 for the entire dataset. We also observe an overall root-mean-square error (RMSE) of 1.1 kcal/mol after shifting the zero-point of the simulation data to match the average experimental values. Through ABFEP calculations using apo versus holo protein structures, we demonstrated that the protein conformational and protonation state changes between the apo and holo proteins are the main physical factors contributing to the protein reorganization free energy manifested by the overestimation of raw ABFEP calculated binding free energies using the holo structures of the proteins. Furthermore, we performed ABFEP calculations in three virtual screening applications for hit enrichment. ABFEP greatly improves the hit rates as compared to docking scores or other methods like metadynamics. The good performance of ABFEP in rank ordering compounds demonstrated in this work confirms it as a useful tool to improve the hit rates in virtual screening, thus facilitating hit discovery.

Amyloid Formation of Stefin B Protein Studied by Infrared Spectroscopy.

Stefin B, an established model protein for studying the stability and mechanism of protein folding, was used for monitoring protein aggregation and formation of amyloid structure by infrared spectroscopy. The analyses of the integral intensities of the low frequency part of the Amide I band, which is directly connected to the appearance of the cross-β structure reveals the temperature but not pH dependence of stefin B structure. We show that pH value has significant role in the monomer stability of stefin B. Protein is less stable in acidic environment and becomes more stable in neutral or basic conditions. While in the case of the Amide I band area analysis we apply only spectral regions characteristic for only part of the protein in cross-β structure, the temperature study using multivariate curve resolution (MCR) analysis contains also information about the protein conformation states which do not correspond to native protein nor protein in cross-β structure. These facts results in the slightly different shapes of fitted sigmoid functions fitted to the weighted amount of the second basic spectrum (sc2), which is the closed approximation of the protein spectra with cross-β structure. Nevertheless, the applied method detects the initial change of the protein structure. Upon the analysis of infrared data a model for stefin B aggregation is proposed.

Dependence of protein-induced lipid bilayer deformations on protein shape.

Membrane proteins typically deform the surrounding lipid bilayer membrane, which can play an important role in the function, regulation, and organization of membrane proteins. Membrane elasticity theory provides a beautiful description of protein-induced lipid bilayer deformations, in which all physical parameters can be directly determined from experiments. While analytic solutions of protein-induced elastic bilayer deformations are most easily developed for proteins with approximately circular cross sections, structural biology has shown that membrane proteins come in a variety of distinct shapes, with often considerable deviations from a circular cross section. We develop here a boundary value method (BVM) that permits the construction of analytic solutions of protein-induced elastic bilayer deformations for protein shapes with arbitrarily large deviations from a circular cross section, for constant as well as variable boundary conditions along the bilayer-protein interface. We apply this BVM to protein-induced lipid bilayer thickness deformations. Our BVM reproduces available analytic solutions for proteins with circular cross sectionand yields, for proteins with noncircular cross section, excellent agreement with numerical, finite element solutions. On this basis, we formulate a simple analytic approximation of the bilayer thickness deformation energy associated with general protein shapes and show that, for modest deviations from rotational symmetry, this analytic approximation is in good agreement with BVM solutions. Using the BVM, we survey the dependence of protein-induced elastic bilayer thickness deformations on protein shape, and thus explore how the coupling of protein shape and bilayer thickness deformations affects protein oligomerization and transitions in protein conformational state.

Machine learning guided sampling of protein transition pathways.

Capturing a protein conformational transition pathway is an important yet difficult task in biophysics. For example, X-ray-crystallography/cryo-EM techniques have captured open/closed states or inward/outward-facing conformations of many ion-channels/transporters; yet, it remains a challenge to experimentally capture transitioning pathways between these ground states due to their rather short-spanned nature. Multiple advanced techniques based on molecular dynamics (MD) simulations have provided great insights to fill such gaps by predicting hypothetical transition states and pathways. Such MD-based techniques, including both long equilibrium simulations and enhanced sampling ones, have provided insights to better understand how putative transition state conformations and pathways would look like. However, MD-based techniques generally take a long time; therefore, it would be of great utility to sample putative transition states along putative transition pathways more efficiently. We present a machine learning model, developed using variational autoencoder (VAE), with the goal of sampling the transition pathway between different protein's conformational states. Using VAE, which takes in protein raw trajectory coordinates generated by equilibrium MD simulations as input, the model is able to reconstruct a structurally close output. Such a VAE can therefore reduce the high-dimensional protein description in the full space into a meaningful low-dimensional representation. In this low-dimensional space, we can interpolate between the two states of interest. The interpolated pathway represents a putative transition-pathway in the higher-dimensional space, learned by VAE. After reconstruction of the sampled transition pathway into the full protein space, secondary structures, RMSDs, and other quality-control properties are used and compared with the functional mechanism of the protein. The reconstructed putative transition pathway can be used in further MD simulations. This machine learning guided MD approach will accelerate studying the full transition pathways of protein conformations by seeding good starting points generated by VAE for iterative MD simulations.

The Impact of Nε-Acryloyllysine Piperazides on the Conformational Dynamics of Transglutaminase 2

In addition to the classic functions of proteins, such as acting as a biocatalyst or binding partner, the conformational states of proteins and their remodeling upon stimulation need to be considered. A prominent example of a protein that undergoes comprehensive conformational remodeling is transglutaminase 2 (TGase 2), the distinct conformational states of which are closely related to particular functions. Its involvement in various pathophysiological processes, including fibrosis and cancer, motivates the development of theranostic agents, particularly based on inhibitors that are directed toward the transamidase activity. In this context, the ability of such inhibitors to control the conformational dynamics of TGase 2 emerges as an important parameter, and methods to assess this property are in great demand. Herein, we describe the application of the switchSENSE® principle to detect conformational changes caused by three irreversibly binding Nε-acryloyllysine piperazides, which are suitable radiotracer candidates of TGase 2. The switchSENSE® technique is based on DNA levers actuated by alternating electric fields. These levers are immobilized on gold electrodes with one end, and at the other end of the lever, the TGase 2 is covalently bound. A novel computational method is introduced for describing the resulting lever motion to quantify the extent of stimulated conformational TGase 2 changes. Moreover, as a complementary biophysical method, native polyacrylamide gel electrophoresis was performed under similar conditions to validate the results. Both methods prove the occurrence of an irreversible shift in the conformational equilibrium of TGase 2, caused by the binding of the three studied Nε-acryloyllysine piperazides.

The role of heat shock proteins in preventing amyloid toxicity.

The oligomerization of monomeric proteins into large, elongated, β-sheet-rich fibril structures (amyloid), which results in toxicity to impacted cells, is highly correlated to increased age. The concomitant decrease of the quality control system, composed of chaperones, ubiquitin-proteasome system and autophagy-lysosomal pathway, has been shown to play an important role in disease development. In the last years an increasing number of studies has been published which focus on chaperones, modulators of protein conformational states, and their effects on preventing amyloid toxicity. Here, we give a comprehensive overview of the current understanding of chaperones and amyloidogenic proteins and summarize the advances made in elucidating the impact of these two classes of proteins on each other, whilst also highlighting challenges and remaining open questions. The focus of this review is on structural and mechanistic studies and its aim is to bring novices of this field "up to speed" by providing insight into all the relevant processes and presenting seminal structural and functional investigations.

Amide Proton Transfer-Weighted Imaging Detects Hippocampal Proteostasis Disturbance Induced by Sleep Deprivation at 7.0 T MRI.

Sleep deprivation leads to hippocampal injury. Proteostasis disturbance is an important mechanism linking sleep deprivation and hippocampal injury. However, identifying noninvasive imaging biomarkers for hippocampal proteostasis disturbance remains challenging. Amide proton transfer-weighted (APTw) imaging is a chemical exchange saturation transfer technique based on the amide protons in proteins and peptides. We aimed to explore the ability of APTw imaging in detecting sleep deprivation-induced hippocampal proteostasis disturbance and its biological significance, as well as its biological basis. In vitro, the feasibility of APTw imaging in detecting changes of the protein state was evaluated, demonstrating that APTw imaging can detect alterations in the protein concentration, conformation, and aggregation state. In vivo, the hippocampal APTw signal declined with increased sleep deprivation time and was significantly lower in sleep-deprived rats than that in normal rats. This signal was positively correlated with the number of surviving neurons counted in Nissl staining and negatively correlated with the expression of glucose-regulated protein 78 evaluated in immunohistochemistry. Differentially expressed proteins in proteostasis network pathways were identified in the hippocampi of normal rats and sleep-deprived rats via mass spectrometry proteomics analysis, providing the biological basis for the change of the hippocampal APTw signal in sleep-deprived rats. These findings demonstrate that APTw imaging can detect hippocampal proteostasis disturbance induced by sleep deprivation and reflect the extent of neuronal injury and endoplasmic reticulum stress.

Evaluation of a Raman Chemometric Method for Detecting Protein Structural Conformational Changes in Solution

Raman scattering shows promise as a powerful routine tool, to determine both secondary and the smaller tertiary structural changes that precede aggregation in both solutions and solids. A method was developed utilizing principal component analysis (PCA) of Raman spectra for detection of small, but meaningful, pH induced changes in tertiary protein structure linked to aggregate formation using α-lactalbumin solutions as a model. The sample preparation and spectral parameters, were optimized for a bulk Raman probe. Analysis of large regions (600–1850 cm−1) yielded principal component (PC) scores useful for semi-quantitative comparison of protein conformation between formulations. PC loadings corresponded to specific structural peaks known to change with solution pH. PCA of circular dichroism (CD) spectra of dilute solutions yielded similar results. Sucrose is a common formulation excipient with a Raman spectrum that overlaps many protein peaks. With sucrose in the protein solution, the ability of PCA to discern protein structural changes from the Raman spectra was somewhat reduced. Analysis of a more limited spectral region (1530–1780 cm−1) with negligible sucrose spectral contribution improved the discrimination of protein conformational states. The new Raman method accurately distinguished differences in protein structure in concentrated solutions. The long-term goal is to explore Raman characterization as a routine monitoring tool of protein stability in both solution and solid states.

Threading single proteins through pores to compare their energy landscapes

Translocation of proteins is correlated with structural fluctuations that access conformational states higher in free energy than the folded state. We use electric fields at the solid-state nanopore to control the relative free energy and occupancy of different protein conformational states at the single-molecule level. The change in occupancy of different protein conformations as a function of electric field gives rise to shifts in the measured distributions of ionic current blockades and residence times. We probe the statistics of the ionic current blockades and residence times for three mutants of the [Formula: see text]-repressor family in order to determine the number of accessible conformational states of each mutant and evaluate the ruggedness of their free energy landscapes. Translocation becomes faster at higher electric fields when additional flexible conformations are available for threading through the pore. At the same time, folding rates are not correlated with ease of translocation; a slow-folding mutant with a low-lying intermediate state translocates faster than a faster-folding two-state mutant. Such behavior allows us to distinguish among protein mutants by selecting for the degree of current blockade and residence time at the pore. Based on these findings, we present a simple free energy model that explains the complementary relationship between folding equilibrium constants and translocation rates.

Mechanochemical coupling of lipid organization and protein function through membrane thickness deformations

Cell membranes are composed of a great variety of protein and lipid species with distinct unperturbed hydrophobic thicknesses. To achieve hydrophobic matching, the lipid bilayer tends to deform around membrane proteins so as to match the protein hydrophobic thickness at bilayer-protein interfaces. Such protein-induced distortions of the lipid bilayer hydrophobic thickness incur a substantial energy cost that depends critically on the bilayer-protein hydrophobic mismatch, while distinct conformational states of membrane proteins often show distinct hydrophobic thicknesses. As a result, hydrophobic interactions between membrane proteins and lipids can yield a rich interplay of lipid-protein organization and transitions in protein conformational state. We combine here the membrane elasticity theory of protein-induced lipid bilayer thickness deformations with the Landau-Ginzburg theory of lipid domain formation to systematically explore the coupling between local lipid organization, lipid and protein hydrophobic thickness, and protein-induced lipid bilayer thickness deformations in membranes with heterogeneous lipid composition. We allow for a purely mechanical coupling of lipid and protein composition through the energetics of protein-induced lipid bilayer thickness deformations as well as a chemical coupling driven by preferential interactions between particular lipid and protein species. We find that the resulting lipid-protein organization can endow membrane proteins with diverse and controlled mechanical environments that, via protein-induced lipid bilayer thickness deformations, can strongly influence protein function. The theoretical approach employed here provides a general framework for the quantitative prediction of how membrane thickness deformations influence the joint organization and function of lipids and proteins in cell membranes.

Structural basis for the inhibition of IAPP fibril formation by the co-chaperonin prefoldin

Chaperones, as modulators of protein conformational states, are key cellular actors to prevent the accumulation of fibrillar aggregates. Here, we integrated kinetic investigations with structural studies to elucidate how the ubiquitous co-chaperonin prefoldin inhibits diabetes associated islet amyloid polypeptide (IAPP) fibril formation. We demonstrated that both human and archaeal prefoldin interfere similarly with the IAPP fibril elongation and secondary nucleation pathways. Using archaeal prefoldin model, we combined nuclear magnetic resonance spectroscopy with electron microscopy to establish that the inhibition of fibril formation is mediated by the binding of prefoldin’s coiled-coil helices to the flexible IAPP N-terminal segment accessible on the fibril surface and fibril ends. Atomic force microscopy demonstrates that binding of prefoldin to IAPP leads to the formation of lower amounts of aggregates, composed of shorter fibrils, clustered together. Linking structural models with observed fibrillation inhibition processes opens perspectives for understanding the interference between natural chaperones and formation of disease-associated amyloids.

Optimization of a processing and analysis workflow for proteome-wide structural biology

Fast photochemical oxidation of proteins (FPOP) is a valuable, mass spectrometry (MS)-based, biophysical technique used to probe protein structure, interactions, and conformational states. FPOP has recently been extended to the study of intact cells (IC-FPOP) and has been shown to modify thousands of proteins in a single experiment for proteome-wide structural biology. Although IC-FPOP can reveal critical structural information, the post experimental process requires a multistep sample workflow to prepare for MS analysis and a lengthy data processing workflow post-MS analysis.

Investigating the protein conformational landscape associated with cognitive decline in aging with mass spectrometry

Cognitive decline in aging is becoming a major issue for families and healthcare providers as the population ages. Protein misfolding and aggregation are frequently implicated as driving many neurodegenerative diseases; however, this view is informed by a relatively small number of proteins, such as Aβ, α-synuclein, and tau. Limited proteolysis mass spectrometry (LiP-MS) is an emerging technique which can provide structural information about protein conformational states proteome-wide. In this approach, pulse proteolysis with a non-specific protease enables accessible regions within proteins to be recorded as cleavage sites, which can be subsequently read out with mass spectrometry.