Proteome-Wide Structural Biology: An Emerging Field for the Structural Analysis of Proteins on the Proteomic Scale

A peptide-centric local stability assay enables proteome-scale identification of the protein targets and binding regions of diverse ligands

By using a limited-proteolysis strategy that employs a large amount of trypsin to generate peptides directly from native proteins, we found that ligand-induced protein local stability shifts can be sensitively detected on a proteome-wide scale. This enabled us to develop the peptide-centric local stability assay, a modification-free approach that achieves unprecedented sensitivity in proteome-wide target identification and binding-region determination. We demonstrate the broad applications of the peptide-centric local stability assay by investigating interactions across various biological contexts.

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

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

Factors affecting protein recovery during Hsp40 affinity profiling

The identification and quantification of misfolded proteins from complex mixtures is important for biological characterization and disease diagnosis, but remains a major bioanalytical challenge. We have developed Hsp40 Affinity Profiling as a bioanalytical approach to profile protein stability in response to cellular stress. In this assay, we ectopically introduce the Hsp40 FlagDNAJB8H31Q into cells and use quantitative proteomics to determine how protein affinity for DNAJB8 changes in the presence of cellular stress, without regard for native clients. Herein, we evaluate potential approaches to improve the performance of this bioanalytical assay. We find that although intracellular crosslinking increases recovery of protein interactors, this is not enough to overcome the relative drop in DNAJB8 recovery. While the J-domain promotes Hsp70 association, it does not affect the yield of protein association with DNAJB8 under basal conditions. By contrast, crosslinking and J-domain ablation both substantially increase relative protein interactor recovery with the structurally distinct Class B Hsp40 DNAJB1 but are completely compensated by poorer yield of DNAJB1 itself. Cellular thermal stress promotes increased affinity between DNAJB8H31Q and interacting proteins, as expected for interactions driven by recognition of misfolded proteins. DNAJB8WT does not demonstrate such a property, suggesting that under stress misfolded proteins are handed off to Hsp70. Hence, we find that DNAJB8H31Q is still our most effective recognition element for the recovery of destabilized client proteins following cellular stress.

FLiPPR: A Processor for Limited Proteolysis (LiP) Mass Spectrometry Data Sets Built on FragPipe

Here, we present FLiPPR, or FragPipe LiP (limited proteolysis) Processor, a tool that facilitates the analysis of data from limited proteolysis mass spectrometry (LiP-MS) experiments following primary search and quantification in FragPipe. LiP-MS has emerged as a method that can provide proteome-wide information on protein structure and has been applied to a range of biological and biophysical questions. Although LiP-MS can be carried out with standard laboratory reagents and mass spectrometers, analyzing the data can be slow and poses unique challenges compared to typical quantitative proteomics workflows. To address this, we leverage FragPipe and then process its output in FLiPPR. FLiPPR formalizes a specific data imputation heuristic that carefully uses missing data in LiP-MS experiments to report on the most significant structural changes. Moreover, FLiPPR introduces a data merging scheme and a protein-centric multiple hypothesis correction scheme, enabling processed LiP-MS data sets to be more robust and less redundant. These improvements strengthen statistical trends when previously published data are reanalyzed with the FragPipe/FLiPPR workflow. We hope that FLiPPR will lower the barrier for more users to adopt LiP-MS, standardize statistical procedures for LiP-MS data analysis, and systematize output to facilitate eventual larger-scale integration of LiP-MS data.

The profile of genome-wide DNA methylation, transcriptome, and proteome in streptomycin-resistant Mycobacterium tuberculosis

Streptomycin-resistant (SM-resistant) Mycobacterium tuberculosis (M. tuberculosis) is a major concern in tuberculosis (TB) treatment. However, the mechanisms underlying streptomycin resistance remain unclear. This study primarily aimed to perform preliminary screening of genes associated with streptomycin resistance through conjoint analysis of multiple genomics. Genome-wide methylation, transcriptome, and proteome analyses were used to elucidate the associations between specific genes and streptomycin resistance in M. tuberculosis H37Rv. Methylation analysis revealed that 188 genes were differentially methylated between the SM-resistant and normal groups, with 89 and 99 genes being hypermethylated and hypomethylated, respectively. Furthermore, functional analysis revealed that these 188 differentially methylated genes were enriched in 74 pathways, with most of them being enriched in metabolic pathways. Transcriptome analysis revealed that 516 genes were differentially expressed between the drug-resistant and normal groups, with 263 and 253 genes being significantly upregulated and downregulated, respectively. KEGG analysis indicated that these 516 genes were enriched in 79 pathways, with most of them being enriched in histidine metabolism. The methylation level was negatively related to mRNA abundance. Proteome analysis revealed 56 differentially expressed proteins, including 14 upregulated and 42 downregulated proteins. Moreover, three hub genes (coaE, fadE5, and mprA) were obtained using synthetic analysis. The findings of this study suggest that an integrated DNA methylation, transcriptome, and proteome analysis can provide important resources for epigenetic studies in SM-resistant M. tuberculosis H37Rv.

FLiPPR: A Processor for Limited Proteolysis (LiP) Mass Spectrometry Datasets Built on FragPipe

Here, we present FLiPPR, or FragPipe LiP (limited proteolysis) Processor, a tool that facilitates the analysis of data from limited proteolysis mass spectrometry (LiP-MS) experiments following primary search and quantification in FragPipe. LiP-MS has emerged as a method that can provide proteome-wide information on protein structure and has been applied to a range of biological and biophysical questions. Although LiP-MS can be carried out with standard laboratory reagents and mass spectrometers, analyzing the data can be slow and poses unique challenges compared to typical quantitative proteomics workflows. To address this, we leverage the fast, sensitive, and accurate search and label-free quantification algorithms in FragPipe and then process its output in FLiPPR. FLiPPR formalizes a specific data imputation heuristic that carefully uses missing data in LiP-MS experiments to report on the most significant structural changes. Moreover, FLiPPR introduces a new data merging scheme (from ions to cut-sites) and a protein-centric multiple hypothesis correction scheme, collectively enabling processed LiP-MS datasets to be more robust and less redundant. These improvements substantially strengthen statistical trends when previously published data are reanalyzed with the FragPipe/FLiPPR workflow. As a final feature, FLiPPR facilitates the collection of structural metadata to identify correlations between experiments and structural features. We hope that FLiPPR will lower the barrier for more users to adopt LiP-MS, standardize statistical procedures for LiP-MS data analysis, and systematize output to facilitate eventual larger-scale integration of LiP-MS data.

Identification of α-amanitin effector proteins in hepatocytes by limited proteolysis-coupled mass spectrometry

The misuse of poisonous mushrooms containing amatoxins causes acute liver failure (ALF) in patients and is a cause of significant mortality. Although the toxic mechanisms of α-amanitin (α-AMA) and its interactions with RNA polymerase II (RNAP II) have been studied, α-AMA effector proteins that can interact with α-AMA in hepatocytes have not been systematically studied. Limited proteolysis-coupled mass spectrometry (LiP-MS) is an advanced technology that can quickly identify protein-ligand interactions based on global comparative proteomics. This study identified the α-AMA effector proteins found in human hepatocytes, following the detection of conformotypic peptides using LiP-MS coupled with tandem mass tag (TMT) technology. Proteins that are classified into protein processing in the endoplasmic reticulum and the ribosome during the KEGG pathway can be identified through affinity evaluation, according to α-AMA concentration-dependent LiP-MS and LiP-MS in hepatocytes derived from humans and mice, respectively. The possibility of interaction between α-AMA and proteins containing conformotypic peptides was evaluated through molecular docking studies. The results of this study suggest a novel path for α-AMA to induce hepatotoxicity through interactions with various proteins involved in protein synthesis, as well as with RNAP II.

Target identification of small molecules: an overview of the current applications in drug discovery

Target identification is an essential part of the drug discovery and development process, and its efficacy plays a crucial role in the success of any given therapy. Although protein target identification research can be challenging, two main approaches can help researchers make significant discoveries: affinity-based pull-down and label-free methods. Affinity-based pull-down methods use small molecules conjugated with tags to selectively isolate target proteins, while label-free methods utilize small molecules in their natural state to identify targets. Target identification strategy selection is essential to the success of any drug discovery process and must be carefully considered when determining how to best pursue a specific project. This paper provides an overview of the current target identification approaches in drug discovery related to experimental biological assays, focusing primarily on affinity-based pull-down and label-free approaches, and discusses their main limitations and advantages.

Cellular Exposure to Chloroacetanilide Herbicides Induces Distinct Protein Destabilization Profiles

Herbicides in the widely used chloroacetanilide class harbor a potent electrophilic moiety, which can damage proteins through nucleophilic substitution. In general, damaged proteins are subject to misfolding. Accumulation of misfolded proteins compromises cellular integrity by disrupting cellular proteostasis networks, which can further destabilize the cellular proteome. While direct conjugation targets can be discovered through affinity-based protein profiling, there are few approaches to probe how cellular exposure to toxicants impacts the stability of the proteome. We apply a quantitative proteomics methodology to identify chloroacetanilide-destabilized proteins in HEK293T cells based on their binding to the H31Q mutant of the human Hsp40 chaperone DNAJB8. We find that a brief cellular exposure to the chloroacetanilides acetochlor, alachlor, and propachlor induces misfolding of dozens of cellular proteins. These herbicides feature distinct but overlapping profiles of protein destabilization, highly concentrated in proteins with reactive cysteine residues. Consistent with the recent literature from the pharmacology field, reactivity is driven by neither inherent nucleophilic nor electrophilic reactivity but is idiosyncratic. We discover that propachlor induces a general increase in protein aggregation and selectively targets GAPDH and PARK7, leading to a decrease in their cellular activities. Hsp40 affinity profiling identifies a majority of propachlor targets identified by competitive activity-based protein profiling (ABPP), but ABPP can only identify about 10% of protein targets identified by Hsp40 affinity profiling. GAPDH is primarily modified by the direct conjugation of propachlor at a catalytic cysteine residue, leading to global destabilization of the protein. The Hsp40 affinity strategy is an effective technique to profile cellular proteins that are destabilized by cellular toxin exposure. Raw proteomics data is available through the PRIDE Archive at PXD030635.

Toward the analysis of functional proteoforms using mass spectrometry-based stability proteomics

Functional proteomics aims to elucidate biological functions, mechanisms, and pathways of proteins and proteoforms at the molecular level to examine complex cellular systems and disease states. A series of stability proteomics methods have been developed to examine protein functionality by measuring the resistance of a protein to chemical or thermal denaturation or proteolysis. These methods can be applied to measure the thermal stability of thousands of proteins in complex biological samples such as cell lysate, intact cells, tissues, and other biological fluids to measure proteome stability. Stability proteomics methods have been popularly applied to observe stability shifts upon ligand binding for drug target identification. More recently, these methods have been applied to characterize the effect of structural changes in proteins such as those caused by post-translational modifications (PTMs) and mutations, which can affect protein structures or interactions and diversify protein functions. Here, we discussed the current application of a suite of stability proteomics methods, including thermal proteome profiling (TPP), stability of proteomics from rates of oxidation (SPROX), and limited proteolysis (LiP) methods, to observe PTM-induced structural changes on protein stability. We also discuss future perspectives highlighting the integration of top-down mass spectrometry and stability proteomics methods to characterize intact proteoform stability and understand the function of variable protein modifications.

Plasma Protein-Mediated Uptake and Contradictions to the Free Drug Hypothesis: A Critical Review

According to the free drug hypothesis (FDH), only free, unbound drug is available to interact with biological targets. This hypothesis is the fundamental principle that continues to explain the vast majority of all pharmacokinetic and pharmacodynamic processes. Under the FDH, the free drug concentration at the target site is considered the driver of pharmacodynamic activity and pharmacokinetic processes. However, deviations from the FDH are observed in hepatic uptake and clearance predictions, where observed unbound intrinsic hepatic clearance (CL_int,u) is larger than expected. Such deviations are commonly observed when plasma proteins are present and form the basis of the so-called plasma protein-mediated uptake effect (PMUE). This review will discuss the basis of plasma protein binding as it pertains to hepatic clearance based on the FDH, as well as several hypotheses that may explain the underlying mechanisms of PMUE. Notably, some, but not all, potential mechanisms remained aligned with the FDH. Finally, we will outline possible experimental strategies to elucidate PMUE mechanisms. Understanding the mechanisms of PMUE and its potential contribution to clearance underprediction is vital to improving the drug development process.

Antinociceptive Activity of Vanilloids in Caenorhabditis elegans is Mediated by the Desensitization of the TRPV Channel OCR-2 and Specific Signal Transduction Pathways

Vanilloids, including capsaicin and eugenol, are ligands of transient receptor potential channel vanilloid subfamily member 1 (TRPV1). Prolonged treatment with vanilloids triggered the desensitization of TRPV1, leading to analgesic or antinociceptive effects. Caenorhabditis elegans (C. elegans) is a model organism expressing vanilloid receptor orthologs (e.g., OSM-9 and OCR-2) that are associated with behavioral and physiological processes, including sensory transduction. We have shown that capsaicin and eugenol hamper the nocifensive response to noxious heat in C. elegans. The objective of this study was to perform proteomics to identify proteins and pathways responsible for the induced phenotype and to identify capsaicin and eugenol targets using a thermal proteome profiling (TPP) strategy. The results indicated hierarchical differences following Reactome Pathway enrichment analyses between capsaicin- and eugenol-treated nematodes. However, both treated groups were associated mainly with signal transduction pathways, energy generation, biosynthesis and structural processes. Wnt signaling, a specific signal transduction pathway, is involved following treatment with both molecules. Wnt signaling pathway is noticeably associated with pain. The TPP results show that capsaicin and eugenol target OCR-2 but not OSM-9. Further protein-protein interaction (PPI) analyses showed other targets associated with enzymatic catalysis and calcium ion binding activity. The resulting data help to better understand the broad-spectrum pharmacological activity of vanilloids.

CHalf: Folding Stability Made Simple

The structure of a protein defines its function and integrity and correlates with the protein folding stability (PFS). Quantifying PFS allows researchers to assess differential stability of proteins in different disease or ligand binding states, providing insight into protein efficacy and potentially serving as a metric of protein quality. There are a number of mass spectrometry (MS)-based methods to assess PFS, such as Thermal Protein Profiling (TPP), Stability of Proteins from Rates of Oxidation (SPROX), and Iodination Protein Stability Assay (IPSA). Despite the critical value that PFS studies add to the understanding of mechanisms of disease and treatment development, proteomics research is still primarily dominated by concentration-based studies. We found that a major reason for the lack of PFS studies is the lack of a user-friendly data processing tool. Here we present the first user-friendly software, CHalf, with a graphical user interface for calculating PFS. Besides calculating site-specific PFS of a given protein from chemical denature folding stability assays, CHalf is also compatible with thermal denature folding stability assays. CHalf also includes a set of data visualization tools to help identify changes in PFS across protein sequences and in between different treatment conditions. We expect the introduction of CHalf to lower the barrier of entry for researchers to investigate PFS, promoting the usage of PFS in studies. In the long run, we expect this increase in PFS research to accelerate our understanding of the pathogenesis and pathophysiology of disease.

Profiling protein targets of cellular toxicant exposure

Environmental agents of exposure can damage proteins, affecting protein function and cellular protein homeostasis. Specific residues are inherently chemically susceptible to damage from individual types of exposure. Amino acid content is not completely predictive of protein susceptibility, as secondary, tertiary, and quaternary structures of proteins strongly influence the reactivity of the proteome to individual exposures. Because we cannot readily predict which proteins will be affected by which chemical exposures, mass spectrometry-based proteomic strategies are necessary to determine the protein targets of environmental toxins and toxicants. This review describes the mechanisms by which environmental exposure to toxins and toxicants can damage proteins and affect their function, and emerging omic methodologies that can be used to identify the protein targets of a given agent. These methods include target identification strategies that have recently revolutionized the drug discovery field, such as activity-based protein profiling, protein footprinting, and protein stability profiling technologies. In particular, we highlight the necessity of multiple, complementary approaches to fully interrogate how protein integrity is challenged by individual exposures.

Quantitative Structural Proteomics Unveils the Conformational Changes of Proteins under the Endoplasmic Reticulum Stress

Protein structures are decisive for their activities and interactions with other molecules. Global analysis of protein structures and conformational changes cannot be achieved by commonly used abundance-based proteomics. Here, we integrated cysteine covalent labeling, selective enrichment, and quantitative proteomics to study protein structures and structural changes on a large scale. This method was applied to globally investigate protein structures in HEK293T cells and protein structural changes in the cells with the tunicamycin (Tm)-induced endoplasmic reticulum (ER) stress. We quantified several thousand cysteine residues, which contain unprecedented and valuable information of protein structures. Combining this method with pulsed stable isotope labeling by amino acids in cell culture, we further analyzed the folding state differences between pre-existing and newly synthesized proteins in cells under the Tm treatment. Besides newly synthesized proteins, unexpectedly, many pre-existing proteins were found to become unfolded upon ER stress, especially those related to gene transcription and protein translation. Furthermore, the current results reveal that N-glycosylation plays a more important role in the folding process of the tertiary and quaternary structures than the secondary structures for newly synthesized proteins. Considering the importance of cysteine in protein structures, this method can be extensively applied in the biological and biomedical research fields.

Metabolization and sequestration of plant specialized metabolites in insect herbivores: Current and emerging approaches

Herbivorous insects encounter diverse plant specialized metabolites (PSMs) in their diet, that have deterrent, anti-nutritional, or toxic properties. Understanding how they cope with PSMs is crucial to understand their biology, population dynamics, and evolution. This review summarizes current and emerging cutting-edge methods that can be used to characterize the metabolic fate of PSMs, from ingestion to excretion or sequestration. It further emphasizes a workflow that enables not only to study PSM metabolism at different scales, but also to tackle and validate the genetic and biochemical mechanisms involved in PSM resistance by herbivores. This review thus aims at facilitating research on PSM-mediated plant-herbivore interactions.

A pulse-chasable reporter processing assay for mammalian autophagic flux with HaloTag

Monitoring autophagic flux is necessary for most autophagy studies. The autophagic flux assays currently available for mammalian cells are generally complicated and do not yield highly quantitative results. Yeast autophagic flux is routinely monitored with the GFP-based processing assay, whereby the amount of GFP proteolytically released from GFP-containing reporters (e.g., GFP-Atg8), detected by immunoblotting, reflects autophagic flux. However, this simple and effective assay is typically inapplicable to mammalian cells because GFP is efficiently degraded in lysosomes while the more proteolytically resistant RFP accumulates in lysosomes under basal conditions. Here, we report a HaloTag (Halo)-based reporter processing assay to monitor mammalian autophagic flux. We found that Halo is sensitive to lysosomal proteolysis but becomes resistant upon ligand binding. When delivered into lysosomes by autophagy, pulse-labeled Halo-based reporters (e.g., Halo-LC3 and Halo-GFP) are proteolytically processed to generate Halo^ligand when delivered into lysosomes by autophagy. Hence, the amount of free Halo^ligand detected by immunoblotting or in-gel fluorescence imaging reflects autophagic flux. We demonstrate the applications of this assay by monitoring the autophagy pathways, macroautophagy, selective autophagy, and even bulk nonselective autophagy. With the Halo-based processing assay, mammalian autophagic flux and lysosome-mediated degradation can be monitored easily and precisely.

Current Advances in CETSA

Knowing that the drug candidate binds to its intended target is a vital part of drug discovery. Thus, several labeled and label-free methods have been developed to study target engagement. In recent years, the cellular thermal shift assay (CETSA) with its variations has been widely adapted to drug discovery workflows. Western blot–based CETSA is used primarily to validate the target binding of a molecule to its target protein whereas CETSA based on bead chemistry detection methods (CETSA HT) has been used to screen molecular libraries to find novel molecules binding to a pre-determined target. Mass spectrometry–based CETSA also known as thermal proteome profiling (TPP) has emerged as a powerful tool for target deconvolution and finding novel binding partners for old and novel molecules. With this technology, it is possible to probe thermal shifts among over 7,000 proteins from one sample and to identify the wanted target binding but also binding to unwanted off-targets known to cause adverse effects. In addition, this proteome-wide method can provide information on the biological process initiated by the ligand binding. The continued development of mass spectrometry labeling reagents, such as isobaric tandem mass tag technology (TMT) continues to increase the throughput of CETSA MS, allowing its use for structure–activity relationship (SAR) studies with a limited number of molecules. In this review, we discussed the differences between different label-free methods to study target engagement, but our focus was on CETSA and recent advances in the CETSA method.

Mass spectrometry-based technologies for probing the 3D world of plant proteins

Over the past two decades, mass spectrometric (MS)-based proteomics technologies have facilitated the study of signaling pathways throughout biology. Nowhere is this needed more than in plants, where an evolutionary history of genome duplications has resulted in large gene families involved in posttranslational modifications and regulatory pathways. For example, at least 5% of the Arabidopsis thaliana genome (ca. 1,200 genes) encodes protein kinases and protein phosphatases that regulate nearly all aspects of plant growth and development. MS-based technologies that quantify covalent changes in the side-chain of amino acids are critically important, but they only address one piece of the puzzle. A more crucially important mechanistic question is how noncovalent interactions-which are more difficult to study-dynamically regulate the proteome's 3D structure. The advent of improvements in protein 3D technologies such as cryo-electron microscopy, nuclear magnetic resonance, and X-ray crystallography has allowed considerable progress to be made at this level, but these methods are typically limited to analyzing proteins, which can be expressed and purified in milligram quantities. Newly emerging MS-based technologies have recently been developed for studying the 3D structure of proteins. Importantly, these methods do not require protein samples to be purified and require smaller amounts of sample, opening the wider proteome for structural analysis in complex mixtures, crude lysates, and even in intact cells. These MS-based methods include covalent labeling, crosslinking, thermal proteome profiling, and limited proteolysis, all of which can be leveraged by established MS workflows, as well as newly emerging methods capable of analyzing intact macromolecules and the complexes they form. In this review, we discuss these recent innovations in MS-based "structural" proteomics to provide readers with an understanding of the opportunities they offer and the remaining challenges for understanding the molecular underpinnings of plant structure and function.

Precipitate-Supported Thermal Proteome Profiling Coupled with Deep Learning for Comprehensive Screening of Drug Target Proteins

Although thermal proteome profiling (TPP) acts as a popular modification-free approach for drug target deconvolution, some key problems are still limiting screening sensitivity. In the prevailing TPP workflow, only the soluble fractions are analyzed after thermal treatment, while the precipitate fractions that also contain abundant information of drug-induced stability shifts are discarded; the sigmoid melting curve fitting strategy used for data processing suffers from discriminations for a part of human proteome with multiple transitions. In this study, a precipitate-supported TPP (PSTPP) assay was presented for unbiased and comprehensive analysis of protein-drug interactions at the proteome level. In PSTPP, only these temperatures where significant precipitation is observed were applied to induce protein denaturation and the complementary information contained in both supernatant fractions and precipitate fractions was used to improve the screening specificity and sensitivity. In addition, a novel image recognition algorithm based on deep learning was developed to recognize the target proteins, which circumvented the problems that exist in the sigmoid curve fitting strategy. PSTPP assay was validated by identifying the known targets of methotrexate, raltitrexed, and SNS-032 with good performance. Using a promiscuous kinase inhibitor, staurosporine, we delineated 99 kinase targets with a specificity up to 83% in K562 cell lysates, which represented a significant improvement over the existing thermal shift methods. Furthermore, the PSTPP strategy was successfully applied to analyze the binding targets of rapamycin, identifying the well-known targets, FKBP1A, as well as revealing a few other potential targets.

Is Protein Folding a Thermodynamically Unfavorable, Active, Energy-Dependent Process?

The prevailing current view of protein folding is the thermodynamic hypothesis, under which the native folded conformation of a protein corresponds to the global minimum of Gibbs free energy G. We question this concept and show that the empirical evidence behind the thermodynamic hypothesis of folding is far from strong. Furthermore, physical theory-based approaches to the prediction of protein folds and their folding pathways so far have invariably failed except for some very small proteins, despite decades of intensive theory development and the enormous increase of computer power. The recent spectacular successes in protein structure prediction owe to evolutionary modeling of amino acid sequence substitutions enhanced by deep learning methods, but even these breakthroughs provide no information on the protein folding mechanisms and pathways. We discuss an alternative view of protein folding, under which the native state of most proteins does not occupy the global free energy minimum, but rather, a local minimum on a fluctuating free energy landscape. We further argue that ΔG of folding is likely to be positive for the majority of proteins, which therefore fold into their native conformations only through interactions with the energy-dependent molecular machinery of living cells, in particular, the translation system and chaperones. Accordingly, protein folding should be modeled as it occurs in vivo, that is, as a non-equilibrium, active, energy-dependent process.

Hsp40 Affinity to Identify Proteins Destabilized by Cellular Toxicant Exposure

Environmental toxins and toxicants can damage proteins and threaten cellular proteostasis. Most current methodologies to identify misfolded proteins in cells survey the entire proteome for sites of changed reactivity. We describe and apply a quantitative proteomics methodology to identify destabilized proteins based on their binding to the human Hsp40 chaperone DNAJB8. These protein targets are validated by an orthogonal limited proteolysis assay using parallel reaction monitoring. We find that a brief exposure of HEK293T cells to meta-arsenite increases the affinity of two dozen proteins to DNAJB8, including known arsenite-sensitive proteins. In particular, arsenite treatment destabilizes both the pyruvate dehydrogenase complex E1 subunit and several RNA-binding proteins. This platform can be used to explore how environmental toxins impact cellular proteostasis and to identify the susceptible proteome.

Analysis of Proteomic Characteristics of Peripheral Blood in Preeclampsia and Study of Changes in Fetal Arterial Doppler Parameters Based on Magnetic Nanoparticles

Background

Traditional mass spectrometry detection methods have low detection efficiency for low-abundance proteins, thus limiting the application of proteomic analysis in the diagnosis of preeclampsia. Magnetic nanomaterials have good superparamagnetism and have obvious advantages in the field of biological separation and enrichment.

Aim

The objective of this study is to explore the value of superparamagnetic iron oxide nanoparticles in the proteomic analysis of preeclampsia.

Materials and Methods

42 patients and 40 normal pregnant women were selected in this study for analysis. Gene Ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed to evaluate the function of these differential proteins. Proteomic analysis was used to analyze the differential proteins. Color Doppler ultrasound technology was used to detect changes in the blood flow of the fetal umbilical artery and cerebral artery.

Results

16 differential proteins in the serum of pregnant women with preeclampsia and normal pregnant women were detected. The 16 proteins are mainly related to angiogenesis and endothelial function proteins, coagulation cascade proteins, placental growth factor, and so on. Biological function analysis revealed that these proteins are mainly enriched in the nuclear factor kB (NF-κB) signaling pathway. Moreover, our data suggested that compared with the fetus in the uterus of normal pregnant women, the umbilical artery S/D, PI, and RI of the fetus in preeclampsia were greatly increased, and the cerebral artery S/D, PI, and RI were greatly decreased.

Conclusion

Biological function analysis revealed that 16 proteins are mainly enriched in the NF-κB signaling pathway. Compared with the normal group, the umbilical artery S/D, PI, and RI of the preeclampsia group were greatly increased, and the cerebral artery S/D, PI, and RI were all greatly reduced. Our findings provided a more comprehensive reference for us to study the mechanism of preeclampsia at the molecular level and also provide data support for the screening of relevant markers for early diagnosis of preeclampsia.

Integration of Mass Spectrometry Data for Structural Biology

Mass spectrometry (MS) is increasingly being used to probe the structure and dynamics of proteins and the complexes they form with other macromolecules. There are now several specialized MS methods, each with unique sample preparation, data acquisition, and data processing protocols. Collectively, these methods are referred to as structural MS and include cross-linking, hydrogen-deuterium exchange, hydroxyl radical footprinting, native, ion mobility, and top-down MS. Each of these provides a unique type of structural information, ranging from composition and stoichiometry through to residue level proximity and solvent accessibility. Structural MS has proved particularly beneficial in studying protein classes for which analysis by classic structural biology techniques proves challenging such as glycosylated or intrinsically disordered proteins. To capture the structural details for a particular system, especially larger multiprotein complexes, more than one structural MS method with other structural and biophysical techniques is often required. Key to integrating these diverse data are computational strategies and software solutions to facilitate this process. We provide a background to the structural MS methods and briefly summarize other structural methods and how these are combined with MS. We then describe current state of the art approaches for the integration of structural MS data for structural biology. We quantify how often these methods are used together and provide examples where such combinations have been fruitful. To illustrate the power of integrative approaches, we discuss progress in solving the structures of the proteasome and the nuclear pore complex. We also discuss how information from structural MS, particularly pertaining to protein dynamics, is not currently utilized in integrative workflows and how such information can provide a more accurate picture of the systems studied. We conclude by discussing new developments in the MS and computational fields that will further enable in-cell structural studies.

Crosslinking mass spectrometry unveils novel interactions and structural distinctions in the model green alga Chlamydomonas reinhardtii

Interactomics is an emerging field that seeks to identify both transient and complex-bound protein interactions that are essential for metabolic functions. Crosslinking mass spectrometry (XL-MS) has enabled untargeted global analysis of these protein networks, permitting largescale simultaneous analysis of protein structure and interactions. Increased commercial availability of highly specific, cell permeable crosslinkers has propelled the study of these critical interactions forward, with the development of MS-cleavable crosslinkers further increasing confidence in identifications. Herein, the global interactome of the unicellular alga Chlamydomonas reinhardtii was analyzed via XL-MS by implementing the MS-cleavable disuccinimidyl sulfoxide (DSSO) crosslinker and enriching for crosslinks using strong cation exchange chromatography. Gentle lysis via repeated freeze-thaw cycles facilitated in vitro analysis of 157 protein-protein crosslinks (interlinks) and 612 peptides linked to peptides of the same protein (intralinks) at 1% FDR throughout the C. reinhardtii proteome. The interlinks confirmed known protein relationships across the cytosol and chloroplast, including coverage on 42% and 38% of the small and large ribosomal subunits, respectively. Of the 157 identified interlinks, 92% represent the first empirical evidence of interaction observed in C. reinhardtii. Several of these crosslinks point to novel associations between proteins, including the identification of a previously uncharacterized Mg-chelatase associated protein (Cre11.g477733.t1.2) bound to seven distinct lysines on Mg-chelatase (Cre06.g306300.t1.2). Additionally, the observed intralinks facilitated characterization of novel protein structures across the C. reinhardtii proteome. Together, these data establish a framework of protein-protein interactions that can be further explored to facilitate understanding of the dynamic protein landscape in C. reinhardtii.

A Comparison of Two Stability Proteomics Methods for Drug Target Identification in OnePot 2D Format

Stability proteomics techniques that do not require drug modifications have emerged as an attractive alternative to affinity purification methods in drug target engagement studies. Two representative techniques include the chemical-denaturation-based SPROX (Stability of Proteins from Rates of Oxidation), which utilizes peptide-level quantification and thermal-denaturation-based TPP (Thermal Proteome Profiling), which utilizes protein-level quantification. Recently, the "OnePot" strategy was adapted for both SPROX and TPP to increase the throughput. When combined with the 2D setup which measures both the denaturation and the drug dose dimensions, the OnePot 2D format offers improved analysis specificity with higher resource efficiency. However, a systematic evaluation of the OnePot 2D format and a comparison between SPROX and TPP are still lacking. Here, we performed SPROX and TPP to identify protein targets of a well-studied pan-kinase inhibitor staurosporine with K562 lysate, in curve-fitting and OnePot 2D formats. We found that the OnePot 2D format provided ∼10× throughput, achieved ∼1.6× protein coverage and involves more straightforward data analysis. We also compared SPROX with the current "gold-standard" stability proteomics technique TPP in the OnePot 2D format. The protein coverage of TPP is ∼1.5 fold of SPROX; however, SPROX offers protein domain-level information, identifies comparable numbers of kinase hits, has higher signal (R value), and requires ∼3× less MS time. Unique SPROX hits encompass higher-molecular-weight proteins, compared to the unique TPP hits, and include atypical kinases. We also discuss hit stratification and prioritization strategies to promote the efficiency of hit followup.

Proteomic landscape of Alzheimer's Disease: novel insights into pathogenesis and biomarker discovery

Mass spectrometry-based proteomics empowers deep profiling of proteome and protein posttranslational modifications (PTMs) in Alzheimer's disease (AD). Here we review the advances and limitations in historic and recent AD proteomic research. Complementary to genetic mapping, proteomic studies not only validate canonical amyloid and tau pathways, but also uncover novel components in broad protein networks, such as RNA splicing, development, immunity, membrane transport, lipid metabolism, synaptic function, and mitochondrial activity. Meta-analysis of seven deep datasets reveals 2,698 differentially expressed (DE) proteins in the landscape of AD brain proteome (n = 12,017 proteins/genes), covering 35 reported AD genes and risk loci. The DE proteins contain cellular markers enriched in neurons, microglia, astrocytes, oligodendrocytes, and epithelial cells, supporting the involvement of diverse cell types in AD pathology. We discuss the hypothesized protective or detrimental roles of selected DE proteins, emphasizing top proteins in "amyloidome" (all biomolecules in amyloid plaques) and disease progression. Comprehensive PTM analysis represents another layer of molecular events in AD. In particular, tau PTMs are correlated with disease stages and indicate the heterogeneity of individual AD patients. Moreover, the unprecedented proteomic coverage of biofluids, such as cerebrospinal fluid and serum, procures novel putative AD biomarkers through meta-analysis. Thus, proteomics-driven systems biology presents a new frontier to link genotype, proteotype, and phenotype, accelerating the development of improved AD models and treatment strategies.

Proteomic Analysis of Rhesus Macaque Brain Explants Treated With Borrelia burgdorferi Identifies Host GAP-43 as a Potential Factor Associated With Lyme Neuroborreliosis

Background

Lyme neuroborreliosis (LNB) is one of the most dangerous manifestations of Lyme disease, but the pathogenesis and inflammatory mechanisms are not fully understood.

Methods

Cultured explants from the frontal cortex of rhesus monkey brain (n=3) were treated with live Borrelia burgdorferi (Bb) or phosphate-buffered saline (PBS) for 6, 12, and 24 h. Total protein was collected for sequencing and bioinformatics analysis. In addition, changes in protein expression in the explants over time following Bb treatment were screened.

Results

We identified 1237 differentially expressed proteins (DEPs; fold change ≥1.5 or ≤0.67, P-value ≤0.05). One of these, growth-associated protein 43 (GAP-43), was highly expressed at all time points in the explants. The results of the protein-protein interaction network analysis of DEPs suggested that GAP-43 plays a role in the neuroinflammation associated with LNB. In HMC3 cells incubated with live Bb or PBS for 6, 12, and 24 h, real-time PCR and western blot analyses confirmed the increase of GAP-43 mRNA and protein, respectively.

Conclusions

Elevated GAP-43 expression is a potential marker for LNB that may be useful for diagnosis or treatment.

Mapping the plant proteome: tools for surveying coordinating pathways

Plants rapidly respond to environmental fluctuations through coordinated, multi-scalar regulation, enabling complex reactions despite their inherently sessile nature. In particular, protein post-translational signaling and protein-protein interactions combine to manipulate cellular responses and regulate plant homeostasis with precise temporal and spatial control. Understanding these proteomic networks are essential to addressing ongoing global crises, including those of food security, rising global temperatures, and the need for renewable materials and fuels. Technological advances in mass spectrometry-based proteomics are enabling investigations of unprecedented depth, and are increasingly being optimized for and applied to plant systems. This review highlights recent advances in plant proteomics, with an emphasis on spatially and temporally resolved analysis of post-translational modifications and protein interactions. It also details the necessity for generation of a comprehensive plant cell atlas while highlighting recent accomplishments within the field.

Global Profiling of Lysine Accessibility to Evaluate Protein Structure Changes in Alzheimer's Disease

The linear sequence of amino acids in a protein folds into a 3D structure to execute protein activity and function, but it is still challenging to profile the 3D structure at the proteome scale. Here, we present a method of native protein tandem mass tag (TMT) profiling of Lys accessibility and its application to investigate structural alterations in human brain specimens of Alzheimer's disease (AD). In this method, proteins are extracted under a native condition, labeled by TMT reagents, followed by trypsin digestion and peptide analysis using two-dimensional liquid chromatography and tandem mass spectrometry (LC/LC-MS/MS). The method quantifies Lys labeling efficiency to evaluate its accessibility on the protein surface, which may be affected by protein conformations, protein modifications, and/or other molecular interactions. We systematically optimized the amount of TMT reagents, reaction time, and temperature and then analyzed protein samples under multiple conditions, including different labeling time (5 and 30 min), heat treatment, AD and normal human cases. The experiment profiled 15370 TMT-labeled peptides in 4475 proteins. As expected, the heat treatment led to extensive changes in protein conformations, with 17% of the detected proteome displaying differential labeling. Compared to the normal controls, AD brain showed different Lys accessibility of tau and RNA splicing complexes, which are the hallmarks of AD pathology, as well as proteins involved in transcription, mitochondrial, and synaptic functions. To eliminate the possibility that the observed differential Lys labeling was caused by protein level change, the whole proteome was quantified with standard TMT-LC/LC-MS/MS for normalization. Thus, this native protein TMT method enables the proteome-wide measurement of Lys accessibility, representing a straightforward strategy to explore protein structure in any biological system.

Recent advances in bioanalytical methods to measure proteome stability in cells

This review summarizes recent bioanalytical methods for measuring and profiling protein stability in cells on a proteome-wide scale, which can provide insights for proteostasis and associated diseases.

Techniques and Strategies for Potential Protein Target Discovery and Active Pharmaceutical Molecule Screening in a Pandemic

Viruses remain a major challenge in the fierce fight against diseases. There have been many pandemics caused by various viruses throughout the world over the years. Recently, the global outbreak of COVID-19 has had a catastrophic impact on human health and the world economy. Antiviral drug treatment has become another essential means to overcome pandemics in addition to vaccine development. How to quickly find effective drugs that can control the development of a pandemic is a hot issue that still needs to be resolved in medical research today. To accelerate the development of drugs, it is necessary to target the key target proteins in the development of the pandemic, screen active molecules, and develop reliable methods for the identification and characterization of target proteins based on the active ingredients of drugs. This article discusses key target proteins and their biological mechanisms in the progression of COVID-19 and other major epidemics. We propose a model based on these foundations, which includes identifying potential core targets, screening potential active molecules of core targets, and verifying active molecules. This article summarizes the related innovative technologies and methods. We hope to provide a reference for the screening of drugs related to pandemics and the development of new drugs.

Identifying the Target of an Antiparasitic Compound in Toxoplasma Using Thermal Proteome Profiling

Apicomplexan parasites include the causative agents of malaria and toxoplasmosis. Cell-based screens in Toxoplasma previously identified a chemical modulator of calcium signaling (ENH1) that blocked parasite egress from host cells and exhibited potent antiparasitic activity. To identify the targets of ENH1, we adapted thermal proteome profiling to Toxoplasma, which revealed calcium-dependent protein kinase 1 (CDPK1) as a target. We confirmed the inhibition of CDPK1 by ENH1 in vitro and in parasites by comparing alleles sensitive or resistant to ENH1. CDPK1 inhibition explained the block in egress; however, the effects of ENH1 on calcium homeostasis and parasite viability were CDPK1-independent, implicating additional targets. Thermal proteome profiling of lysates from parasites expressing the resistant allele of CDPK1 identified additional candidates associated with the mitochondria and the parasite pellicle-compartments that potentially function in calcium release and homeostasis. Our findings illustrate the promise of thermal profiling to identify druggable targets that modulate calcium signaling in apicomplexan parasites.

Validation of the Applicability of In-Cell Fast Photochemical Oxidation of Proteins across Multiple Eukaryotic Cell Lines

Fast photochemical oxidation of proteins (FPOP), a hydroxyl radical-based protein footprinting method, coupled to mass spectrometry has been extensively used to study protein structure and protein-protein interactions in vitro. This method utilizes hydroxyl radicals to oxidatively modify solvent-accessible amino acids and has recently been demonstrated to modify proteins within live cells (IC-FPOP) and Caenorhabditis elegans. Here, we have expanded the application of IC-FPOP into a variety of commonly used cell lines to verify the applicability of the method across various cellular systems. IC-FPOP was able to successfully modify proteins in five different cell lines (Vero, HEK 293T, CHO, MCF-10A, and MCF-7). To increase the number of oxidatively modified proteins identified, we have also employed the use of offline high pH reversed-phase liquid chromatography (RPLC) followed by concatenation and online low-pH RPLC. The coupling of IC-FPOP to 2D-LC MS/MS resulted in a 1.7-fold increase in total identifications of oxidatively modified proteins, which expanded the dynamic range of the method. This work demonstrates the efficacy of using IC-FPOP to study protein-protein interactions in cells.

Mass spectrometry-based methods for structural biology on a proteome-wide scale

Mass spectrometry (MS) has long been used to study proteins mainly via sequence identification and quantitation of expression abundance. In recent years, MS has emerged as a tool for structural biology. Intact protein structural analysis has been enabled by the development of methods such as native MS, top-down proteomics, and ion mobility MS. Other MS-based structural methods include affinity purification MS, chemical cross-linking, and protein footprinting. These methods have enabled the study of protein–protein and protein–ligand interactions and regions of conformational change. The coupling of MS with liquid chromatography has permitted the analysis of complex samples. This bottom-up proteomics workflow enables the study of protein structure in the native cellular environment and provides structural information across the proteome. It has been demonstrated that the crowded environment of the cell affects protein binding interactions and affinities. Performing studies in this complex environment is essential for understanding the functional roles of proteins. MS-based structural methods permit analysis of samples such as cell lysates, intact cells, and tissue to provide a more physiological view of protein structure. This mini-review discusses the various MS-based methods that can be used for proteome-wide structural studies and highlights some of their application.

An isothermal shift assay for proteome scale drug-target identification

Most small molecule drugs act on living systems by physically interacting with specific proteins and modulating target function. Identification of drug binding targets, within the complex milieu of the human proteome, remains a challenging task of paramount importance in drug discovery. Existing approaches for target identification employ complex workflows with limited throughput. Here, we present the isothermal shift assay (iTSA), a mass spectrometry method for proteome-wide identification of drug targets within lysates or living cells. Compared with prevailing methods, iTSA uses a simplified experimental design with increased statistical power to detect thermal stability shifts that are induced by small molecule binding. Using a pan-kinase inhibitor, staurosporine, we demonstrate improved performance over commonly used thermal proteome profiling methods, identifying known targets in cell lysates and living cells. We also demonstrate the identification of both known targets and additional candidate targets for the kinase inhibitor harmine in cell and tissue lysates.

Comparative Analysis of Mass-Spectrometry-Based Proteomic Methods for Protein Target Discovery Using a One-Pot Approach

Recently, several mass-spectrometry- and protein-denaturation-based proteomic methods have been developed to facilitate protein target discovery efforts in drug mode-of-action studies. These methods, which include the stability of proteins from rates of oxidation (SPROX), pulse proteolysis (PP), chemical denaturation and protein precipitation (CPP), and thermal proteome profiling (TPP) techniques, have been used in an increasing number of applications in recent years. However, while the advantages and disadvantages to using these different techniques have been reviewed, the analytical characteristics of these methods have not been directly compared. Reported here is such a direct comparison using the well-studied immunosuppressive drug, cyclosporine A (CsA), and the proteins in a yeast cell lysate. Also described is a one-pot strategy that can be utilized with each technique to streamline data acquisition and analysis. We find that there are benefits to utilizing all four strategies for protein target discovery including increased proteomic coverage and reduced false positive rates that approach 0%. Moreover, the one-pot strategy described here makes such an experiment feasible, because of the 10-fold reduction in reagent costs and instrument time it affords.

High-throughput quantitative top-down proteomics

Top-down mass spectrometry (MS) analyzes intact proteins at the proteoform level, which allows researchers to better understand the functions of protein modifications. Recently, top-down proteomics has increased in popularity due to advancements in high-resolution mass spectrometers, increased efficiency in liquid chromatography (LC) separation, and advances in data analysis software. Some unique protein proteoforms, which have been distinguished using top-down MS, have even been shown to exhibit marked variation in biological function compared to similar proteoforms. However, the qualitative identification of a particular proteoform may not be enough to determine the biological relevance of that proteoform. Quantitative top-down MS methods have been notably applied to the study of the differing biological functions of protein proteoforms and have allowed researchers to explore proteomes at the proteoform, rather than the peptide, level. Here, we review the top-down MS methods that have been used to quantitatively identify intact proteins, discuss current applications of quantitative top-down MS analysis, and present new areas where quantitative top-down MS analysis may be implemented.

Mass spectrometric approaches for profiling protein folding and stability

Protein stability reports on protein homeostasis, function, and binding interactions, such as to other proteins, metabolites and drugs. As such, there is a pressing need for technologies that can report on protein stability. The ideal technique could be applied in vitro or in vivo systems, proteome-wide, independently of matrix, under native conditions, with residue-level resolution, and on protein at endogenous levels. Mass spectrometry has rapidly become a preferred technology for identifying and quantifying proteins. As such, it has been increasingly incorporated into methodologies for interrogating protein stability and folding. Although no single technology can satisfy all desired applications, several emerging approaches have shown outstanding success at providing biological insight into the stability of the proteome. This chapter outlines some of these recent emerging technologies.

Fast photochemical oxidation of proteins (FPOP): A powerful mass spectrometry-based structural proteomics tool

Fast photochemical oxidation of proteins (FPOP) is a MS-based method that has proved useful in studies of protein structures, interactions, conformations, and protein folding. The success of this method relies on the irreversible labeling of solvent-exposed amino acid side chains by hydroxyl radicals. FPOP generates these radicals through laser-induced photolysis of hydrogen peroxide. The data obtained provide residue-level resolution of protein structures and interactions on the microsecond timescale, enabling investigations of fast processes such as protein folding and weak protein-protein interactions. An extensive comparison between FPOP and other footprinting techniques gives insight on their complementarity as well as the robustness of FPOP to provide unique structural information once unattainable. The versatility of this method is evidenced by both the heterogeneity of samples that can be analyzed by FPOP and the myriad of applications for which the method has been successfully used: from proteins of varying size to intact cells. This review discusses the wide applications of this technique and highlights its high potential. Applications including, but not limited to, protein folding, membrane proteins, structure elucidation, and epitope mapping are showcased. Furthermore, the use of FPOP has been extended to probing proteins in cells and in vivo These promising developments are also presented herein.

Protein profiling and pseudo-parallel reaction monitoring to monitor a fusion-associated conformational change in hemagglutinin

Influenza infection requires viral escape from early endosomes into the cytosol, which is enabled by an acid-induced irreversible conformational transformation in the viral protein hemagglutinin. Despite the direct relationship between this conformational change and infectivity, label-free methods for characterizing this and other protein conformational changes in biological mixtures are limited. While the chemical reactivity of the protein backbone and side-chain residues is a proxy for protein conformation, coupling this reactivity to quantitative mass spectrometry is a challenge in complex environments. Herein, we evaluate whether electrophilic amidination coupled with pseudo-parallel reaction monitoring is an effective label-free approach to detect the fusion-associated conformational transformation in recombinant hemagglutinin (rHA). We identified rHA peptides that are differentially amidinated between the pre- and post-fusion states, and validated that this difference relies upon the fusion-associated conformational switch. We further demonstrate that we can distinguish the fusion profile in a matrix of digested cellular lysate. This fusion assay can be used to evaluate fusion competence for modified HA. Graphical abstract.

DO-MS: Data-Driven Optimization of Mass Spectrometry Methods

The performance of ultrasensitive liquid chromatography and tandem mass spectrometry (LC-MS/MS) methods, such as single-cell proteomics by mass spectrometry (SCoPE-MS), depends on multiple interdependent parameters. This interdependence makes it challenging to specifically pinpoint the sources of problems in the LC-MS/MS methods and approaches for resolving them. For example, a low signal at the MS2 level can be due to poor LC separation, ionization, apex targeting, ion transfer, or ion detection. We sought to specifically diagnose such problems by interactively visualizing data from all levels of bottom-up LC-MS/MS analysis. Many software packages, such as MaxQuant, already provide such data, and we developed an open source platform for their interactive visualization and analysis: Data-driven Optimization of MS (DO-MS). We found that in many cases DO-MS not only specifically diagnosed LC-MS/MS problems but also enabled us to rationally optimize them. For example, by using DO-MS to optimize the sampling of the elution peak apexes, we increased ion accumulation times and apex sampling, which resulted in a 370% more efficient delivery of ions for MS2 analysis. DO-MS is easy to install and use, and its GUI allows for interactive data subsetting and high-quality figure generation. The modular design of DO-MS facilitates customization and expansion. DO-MS v1.0.8 is available for download from GitHub: https://github.com/SlavovLab/DO-MS . Additional documentation is available at https://do-ms.slavovlab.net .

Illuminating Biological Interactions with in Vivo Protein Footprinting

Protein footprinting coupled with mass spectrometry is being increasingly used for the study of protein interactions and conformations. The hydroxyl radical footprinting method, fast photochemical oxidation of proteins (FPOP), utilizes hydroxyl radicals to oxidatively modify solvent accessible amino acids. Here, we describe the further development of FPOP for protein structural analysis in vivo (IV-FPOP) with Caenorhabditis elegans. C. elegans, part of the nematode family, are used as model systems for many human diseases. The ability to perform structural studies in these worms would provide insight into the role of structure in disease pathogenesis. Many parameters were optimized for labeling within the worms including the microfluidic flow system and hydrogen peroxide concentration. IV-FPOP was able to modify several hundred proteins in various organs within the worms. The method successfully probed solvent accessibility similarily to in vitro FPOP, demonstrating its potential for use as a structural technique in a multiorgan system. The coupling of the method with mass spectrometry allows for amino-acid-residue-level structural information, a higher resolution than currently available in vivo methods.

Recent technical advances in proteomics

Mass spectrometry is one of the key technologies of proteomics, and over the last decade important technical advances in mass spectrometry have driven an increased capability for proteomic discovery. In addition, new methods to capture important biological information have been developed to take advantage of improving proteomic tools.

Weighing-up protein dynamics: the combination of native mass spectrometry and molecular dynamics simulations

Structural dynamics underpin biological function at the molecular level, yet many biophysical and structural biology approaches give only a static or averaged view of proteins. Native mass spectrometry yields spectra of the many states and interactions in the structural ensemble, but its spatial resolution is limited. Conversely, molecular dynamics simulations are innately high-resolution, but have a limited capacity for exploring all structural possibilities. The two techniques hence differ fundamentally in the information they provide, returning data that reflect different length scales and time scales, making them natural bedfellows. Here we discuss how the combination of native mass spectrometry with molecular dynamics simulations is enabling unprecedented insights into a range of biological questions by interrogating the motions of proteins, their assemblies, and interactions.