Perspective: The complex relationship between charge, mobility, and gas-phase protein structure

Ion mobility spectrometry coupled to mass spectrometry (IMS/MS) is a widely used tool for biomolecular separations and structural elucidation. The application of IMS/MS has resulted in exciting developments in structural proteomics and genomics. This perspective gives a brief background of the field, addresses some of the important issues in making structural measurements, and introduces complementary techniques.

Quantifying the Impact of the Peptide Identification Framework on the Results of Fast Photochemical Oxidation of Protein Analysis

Fast Photochemical Oxidation of Proteins (FPOP) is a promising technique for studying protein structure and dynamics. The quality of insight provided by FPOP depends on the reliability of the determination of the modification site. This study investigates the performance of two search engines, Mascot and PEAKS, for the data processing of FPOP analyses. Comparison of Mascot and PEAKS of the hemoglobin--haptoglobin Bruker timsTOF data set (PXD021621) revealed greater consistency in the Mascot identification of modified peptides, with around 26% of the IDs being mutual for all three replicates, compared to approximately 22% for PEAKS. The intersection between Mascot and PEAKS results revealed a limited number (31%) of shared modified peptides. Principal Component Analysis (PCA) using the peptide-spectrum match (PSM) score, site probability, and peptide intensity was applied to evaluate the results, and the analyses revealed distinct clusters of modified peptides. Mascot showed the ability to assess confident site determination, even with lower PSM scores. However, high PSM scores from PEAKS did not guarantee a reliable determination of the modification site. Fragmentation coverage of the modification position played a crucial role in Mascot assignments, while the AScore localizations from PEAKS often become ambiguous because the software employs MS/MS merging.

Parsing 20 Years of Public Data by AI Maps Trends in Proteomics and Forecasts Technology

The trends of the last 20 years in biotechnology were revealed using artificial intelligence and natural language processing (NLP) of publicly available data. Implementing this "science-of-science" approach, we capture convergent trends in the field of proteomics in both technology development and application across the phylogenetic tree of life. With major gaps in our knowledge about protein composition, structure, and location over time, we report trends in persistent, popular approaches and emerging technologies across 94 ideas from a corpus of 29 journals in PubMed over two decades. New metrics for clusters of these ideas reveal the progression and popularity of emerging approaches like single-cell, spatial, compositional, and chemical proteomics designed to better capture protein-level chemistry and biology. This analysis of the proteomics literature with advanced analytic tools quantifies the Rate of Rise for a next generation of technologies to better define, quantify, and visualize the multiple dimensions of the proteome that will transform our ability to measure and understand proteins in the coming decade.

Recruitment of trimeric eIF2 by phosphatase non-catalytic subunit PPP1R15B

Regulated protein phosphorylation controls most cellular processes. The protein phosphatase PP1 is the catalytic subunit of many holoenzymes that dephosphorylate serine/threonine residues. How these enzymes recruit their substrates is largely unknown. Here, we integrated diverse approaches to elucidate how the PP1 non-catalytic subunit PPP1R15B (R15B) captures its full trimeric eIF2 substrate. We found that the substrate-recruitment module of R15B is largely disordered with three short helical elements, H1, H2, and H3. H1 and H2 form a clamp that grasps the substrate in a region remote from the phosphorylated residue. A homozygous N423D variant, adjacent to H1, reducing substrate binding and dephosphorylation was discovered in a rare syndrome with microcephaly, developmental delay, and intellectual disability. These findings explain how R15B captures its 125 kDa substrate by binding the far end of the complex relative to the phosphosite to present it for dephosphorylation by PP1, a paradigm of broad relevance.

Analysis of the Tropism of SARS-CoV-2 Based on the Host Interactome of the Spike Protein

The β-coronavirus SARS-CoV-2 causes severe acute respiratory syndrome (COVID-19) in humans. It enters and infects epithelial airway cells upon binding of the receptor binding domain (RBD) of the virus entry protein spike to the host receptor protein Angiotensin Converting Enzyme 2 (ACE2). Here, we used coimmunoprecipitation coupled with bottom-up mass spectrometry to identify host proteins that engaged with the spike protein in human bronchial epithelial cells (16HBEo-). We found that the spike protein bound to extracellular laminin and thrombospondin and endoplasmatic reticulum (ER)-resident DJB11 and FBX2 proteins. The ER-resident proteins UGGT1, CALX, HSP7A, and GRP78/BiP bound preferentially to the original Wuhan D614 over the mutated G614 spike protein in the more rapidly spreading Alpha SARS-CoV-2 strain. The increase in protein binding to the D614 spike might be explained by higher accessibility of cryptic sites in "RDB open" and "S2 only" D614 spike protein conformations and may enable SARS-CoV-2 to infect additional, ACE2-negative cell types. Moreover, a novel proteome-based cell type set enrichment analysis (pCtSEA) found that host factors like laminin might render additional cell types such as macrophages and epithelial cells in the nephron permissive to SARS-CoV-2 infection.

Combination of deep XLMS with deep learning reveals an ordered rearrangement and assembly of a major protein component of the vaccinia virion

IMPORTANCE

An outstanding problem in the understanding of poxvirus biology is the molecular structure of the mature virion. Via deep learning methods combined with chemical cross-linking mass spectrometry, we have addressed the structure and assembly pathway of P4a, a key poxvirus virion core component.

Global analysis of aging-related protein structural changes uncovers enzyme-polymerization-based control of longevity

Aging is associated with progressive phenotypic changes. Virtually all cellular phenotypes are produced by proteins, and their structural alterations can lead to age-related diseases. However, we still lack comprehensive knowledge of proteins undergoing structural-functional changes during cellular aging and their contributions to age-related phenotypes. Here, we conducted proteome-wide analysis of early age-related protein structural changes in budding yeast using limited proteolysis-mass spectrometry (LiP-MS). The results, compiled in online ProtAge catalog, unraveled age-related functional changes in regulators of translation, protein folding, and amino acid metabolism. Mechanistically, we found that folded glutamate synthase Glt1 polymerizes into supramolecular self-assemblies during aging, causing breakdown of cellular amino acid homeostasis. Inhibiting Glt1 polymerization by mutating the polymerization interface restored amino acid levels in aged cells, attenuated mitochondrial dysfunction, and led to lifespan extension. Altogether, this comprehensive map of protein structural changes enables identifying mechanisms of age-related phenotypes and offers opportunities for their reversal.

Enabling cryo-EM density interpretation from yeast native cell extracts by proteomics data and AlphaFold structures

In the cellular context, proteins participate in communities to perform their function. The detection and identification of these communities as well as in-community interactions has long been the subject of investigation, mainly through proteomics analysis with mass spectrometry. With the advent of cryogenic electron microscopy and the "resolution revolution," their visualization has recently been made possible, even in complex, native samples. The advances in both fields have resulted in the generation of large amounts of data, whose analysis requires advanced computation, often employing machine learning approaches to reach the desired outcome. In this work, we first performed a robust proteomics analysis of mass spectrometry (MS) data derived from a yeast native cell extract and used this information to identify protein communities and inter-protein interactions. Cryo-EM analysis of the cell extract provided a reconstruction of a biomolecule at medium resolution (∼8 Å (FSC = 0.143)). Utilizing MS-derived proteomics data and systematic fitting of AlphaFold-predicted atomic models, this density was assigned to the 2.6 MDa complex of yeast fatty acid synthase. Our proposed workflow identifies protein complexes in native cell extracts from Saccharomyces cerevisiae by combining proteomics, cryo-EM, and AI-guided protein structure prediction.

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

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

Recent advances in the efficient degradation of lignocellulosic metabolic networks by lytic polysaccharide monooxygenase

Along with long-term evolution, the plant cell wall generates lignocellulose and other anti-degradation barriers to confront hydrolysis by fungi. Lytic polysaccharide monooxygenase (LPMO) is a newly defined oxidase in lignocellulosic degradation systems that significantly fuels hydrolysis. LPMO accepts electrons from wide sources, such as cellobiose dehydrogenase (CDH), glucose-methanol-choline (GMC) oxidoreductases, and small phenols. In addition, the extracellular cometabolic network formed by cosubstrates improves the degradation efficiency, forming a stable and efficient lignocellulose degradation system. In recent years, using structural proteomics to explore the internal structure and the complex redox system of LPMOs has become a research hotspot. In this review, the diversity of LPMOs, catalytic domains, carbohydrate binding modules, direct electron transfer with CDH, cosubstrates, and degradation networks of LPMOs are explored, which can provide a systematic reference for the application of lignocellulosic degradation systems in industrial approaches.

The utility of proteases in proteomics, from sequence profiling to structure and function analysis

In mass spectrometry (MS)-based bottom-up proteomics, protease digestion plays an essential role in profiling both proteome sequences and post-translational modifications (PTMs). Trypsin is the gold standard in digesting intact proteins into small-size peptides, which are more suitable for high-performance liquid chromatography (HPLC) separation and tandem MS (MS/MS) characterization. However, protein sequences lacking Lys and Arg cannot be cleaved by trypsin and may be missed in conventional proteomic analysis. Proteases with cleavage sites complementary to trypsin are widely applied in proteomic analysis to greatly improve the coverage of proteome sequences and PTM sites. In this review, we survey the common and newly emerging proteases used in proteomics analysis mainly in the last 5 years, focusing on their unique cleavage features and specific proteomics applications such as missing protein characterization, new PTM discovery, and de novo sequencing. In addition, we summarize the applications of proteases in structural proteomics and protein function analysis in recent years. Finally, we discuss the future development directions of new proteases and applications in proteomics.

Bioinformatics Insights on the Physicochemical Properties of SCN5A Mutant Proteins Associated with the Brugada Syndrome

BACKGROUND

The Brugada syndrome (BrS) is a heart rhythm condition that is commonly associated with a strong predisposition for sudden cardiac death. Malignant ventricular arrhythmias could occur secondary to the dysfunction of the cardiac sodium voltage-gated Na(v)1.5 channel (SCN5A).

OBJECTIVE

This study aimed to perform a multiparametric computational analysis of the physicochemical properties of SCN5A mutants associated with BrS using a set of bioinformatics tools.

METHODS

In-house algorithms were calibrated to calculate, in a double-blind test, the Polarity Index Method (PIM) profile and protein intrinsic disorder predisposition (PIDP) profile of each sequence, and computer programs specialized in the genomic analysis were used.

RESULTS

Specific regularities in the charge/polarity and PIDP profile of the SCN5A mutant proteins enabled the re-creation of the taxonomy, allowing us to propose a bioinformatics method that takes advantage of the PIM profile to identify this group of proteins from their sequence.

CONCLUSION

Bioinformatics programs could reproduce characteristic PIM and PIDP profiles of the BrS-related SCN5A mutant proteins. This information can contribute to a better understanding of these altered proteins.

Structural Analysis of Phosphorylation Proteoforms in a Dynamic Heterogeneous System Using Flash Oxidation Coupled In-Line with Ion Exchange Chromatography

Protein posttranslational modifications (PTMs) are key modulators of protein structure and function that often change in a dynamic fashion in response to cellular stimuli. Dynamic PTMs are very challenging to structurally characterize using modern techniques, including covalent labeling methods, due to the presence of multiple proteoforms and conformers together in solution. We have coupled an ion exchange high-performance liquid chromatography separation with a flash oxidation system [ion exchange chromatography liquid chromatography-flash oxidation (IEX LC-FOX)] to successfully elucidate structural changes among three phosphoproteoforms of ovalbumin (OVA) during dephosphorylation with alkaline phosphatase. Real-time dosimetry indicates no difference in the effective radical dose between peaks or across the peak, demonstrating both the lack of scavenging of the NaCl gradient and the lack of a concentration effect on radical dose between peaks of different intensities. The use of IEX LC-FOX allows us to structurally probe into each phosphoproteoform as it elutes from the column, capturing structural data before the dynamics of the system to reintroduce heterogeneity. We found significant differences in the residue-level oxidation between the hydroxyl radical footprint of nonphosphorylated, monophosphorylated, and diphosphorylated OVA. Not only were our data consistent with the previously reported stabilization of OVA structure by phosphorylation, but local structural changes were also consistent with the measured order of dephosphorylation of Ser344 being removed first. These results demonstrate the utility of IEX LC-FOX for measuring the structural effects of PTMs, even in dynamic systems.

Omics Approaches in Drug Development against Leishmaniasis: Current Scenario and Future Prospects

Leishmaniasis is a zoonotic disease transmitted in humans by the bite of Leishmania-infected phlebotomine sandflies. Each year approximately 58,500 cases of leishmaniasis are diagnosed across the globe, with a mortality rate of nearly seven percent. There are over 20 parasitic strains of Leishmania which are known to cause distinct types of leishmaniasis and pose an endemic threat to humans worldwide. Therefore, it is crucial to develop potential medications and vaccines to combat leishmaniasis. However, the task of developing therapeutic solutions is challenging due to Leishmania's digenetic lifecycle. The challenge is further intensified by cases of resistance against the available drugs. Owing to these challenges, the conventional drug development regimen is further limited by target discovery and ligand suitability for the targets. On the other hand, as an added advantage, the emergence of omics-based tools, such as high-end proteomics, transcriptomics and genomics, has hastened the pace of target discovery and target-based drug development. It is now becoming apparent that multi-omics convergence and an inter-connected systems approach is less time-consuming and more cost-effective for any drug-development process. This comprehensive review is an attempt to summarize the current knowledge on the muti-omics approach in drug development against leishmaniasis. In particular, it elaborates the potential target identification from secreted proteins in various stages of Leishmania infection and also illustrates the convergence of transcriptomic and genomic data towards the collective goal of drug discovery. This review also provides an understanding of the potential parasite's drug targets and drug resistance characteristics of the parasite, which can be used in designing effective and specific therapeutics.

Utilizing an artificial intelligence system to build the digital structural proteome of reef-building corals

BACKGROUND

Reef-building corals play an important role in the marine ecosystem, and analyzing their proteomes from a structural perspective will exert positive effects on exploring their biology. Here we integrated mass spectrometry with newly published ColabFold to obtain digital structural proteomes of dominant reef-building corals.

RESULTS

Of the 8,382 homologous proteins in Acropora muricata, Montipora foliosa, and Pocillopora verrucosa identified, 8,166 received predicted structures after about 4,060 GPU hours of computation. The resulting dataset covers 83.6% of residues with a confident prediction, while 25.9% have very high confidence.

CONCLUSIONS

Our work provides insight-worthy predictions for coral research, confirms the reliability of ColabFold in practice, and is expected to be a reference case in the impending high-throughput era of structural proteomics.

Advances in mass spectrometry-based phosphoproteomics for elucidating abscisic acid signaling and plant responses to abiotic stress

Abiotic stresses have significant impacts on crop yield and quality. Even though significant efforts during the past decade have been devoted to uncovering the core signaling pathways associated with the phytohormone abscisic acid (ABA) and abiotic stress in plants, abiotic stress signaling mechanisms in most crops remain largely unclear. The core components of the ABA signaling pathway, including early events in the osmotic stress-induced phosphorylation network, have recently been elucidated in Arabidopsis with the aid of phosphoproteomics technologies. We now know that SNF1-related kinases 2 (SnRK2s) are not only inhibited by the clade A type 2C protein phosphatases (PP2Cs) through dephosphorylation, but also phosphorylated and activated by upstream mitogen-activated protein kinase kinase kinases (MAP3Ks). Through describing the course of studies to elucidate abiotic stress and ABA signaling, we will discuss how we can take advantage of the latest innovations in mass-spectrometry-based phosphoproteomics and structural proteomics to boost our investigation of plant regulation and responses to ABA and abiotic stress.

Bioinformatics-based Characterization of the Sequence Variability of Zika Virus Polyprotein and Envelope Protein (E)

Background:

Zika virus, which is widely spread and infects humans through the bites of Aedes albopictus and Aedes aegypti female mosquitoes, represents a serious global health issue.

Objective:

The objective of the present study is to computationally characterize Zika virus polyproteins (UniProt Name: PRO_0000443018 [residues 1-3423], PRO_0000445659 [residues 1-3423] and PRO_0000435828 [residues 1-3419]) and their envelope proteins using their physico-chemical properties.

Methods:

To achieve this, the Polarity Index Method (PIM) profile and the Protein Intrinsic Disorder Predisposition (PIDP) profile of 3 main groups of proteins were evaluated: structural proteins extracted from specific Databases, Zika virus polyproteins, and their envelope proteins (E) extracted from UniProt Database. Once the PIM profile of the Zika virus envelope proteins (E) was obtained and since the Zika virus polyproteins were also identified with this profile, the proteins defined as “reviewed proteins” extracted from the UniProt Database were searched for the similar PIM profile. Finally, the difference between the PIM profiles of the Zika virus polyproteins and their envelope proteins (E) was tested using 2 non-parametric statistical tests.

Results:

It was found and tested that the PIM profile is an efficient discriminant that allows obtaining a “computational fingerprint” of each Zika virus polyprotein from its envelope protein (E).

Conclusion:

PIM profile represents a computational tool, which can be used to effectively discover Zika virus polyproteins from Databases, from their envelope proteins (E) sequences.

Mass Spectrometry and Machine Learning Reveal Determinants of Client Recognition by Antiamyloid Chaperones

The assembly of proteins and peptides into amyloid fibrils is causally linked to serious disorders such as Alzheimer's disease. Multiple proteins have been shown to prevent amyloid formation in vitro and in vivo, ranging from highly specific chaperone-client pairs to completely nonspecific binding of aggregation-prone peptides. The underlying interactions remain elusive. Here, we turn to the machine learning-based structure prediction algorithm AlphaFold2 to obtain models for the nonspecific interactions of β-lactoglobulin, transthyretin, or thioredoxin 80 with the model amyloid peptide amyloid β and the highly specific complex between the BRICHOS chaperone domain of C-terminal region of lung surfactant protein C and its polyvaline target. Using a combination of native mass spectrometry (MS) and ion mobility MS, we show that nonspecific chaperoning is driven predominantly by hydrophobic interactions of amyloid β with hydrophobic surfaces in β-lactoglobulin, transthyretin, and thioredoxin 80, and in part regulated by oligomer stability. For C-terminal region of lung surfactant protein C, native MS and hydrogen-deuterium exchange MS reveal that a disordered region recognizes the polyvaline target by forming a complementary β-strand. Hence, we show that AlphaFold2 and MS can yield atomistic models of hard-to-capture protein interactions that reveal different chaperoning mechanisms based on separate ligand properties and may provide possible clues for specific therapeutic intervention.

Cancer Conformational Landscape Shapes Tumorigenesis

During tumorigenesis, DNA mutations in protein coding sequences can alter amino acid sequences which can change the structures of proteins. While the 3D structure of mutated proteins has been studied with atomic resolution, the precise impact of somatic mutations on the 3D proteome during malignant transformation remains unknown because methods to reveal in vivo protein structures in high throughput are limited. Here, we measured the accessibility of the lysine ε-amine for chemical modification across proteomes using covalent protein painting (CPP) to indirectly determine alterations in the 3D proteome. CPP is a novel, high-throughput quantitative mass spectrometric method that surveyed a total of 8052 lysine sites across the 60 cell lines of the well-studied anticancer cell line panel (NCI60). Overall, 5.2 structural alterations differentiated any cancer cell line from the other 59. Structural aberrations in 98 effector proteins correlated with the selected presence of 90 commonly mutated proteins in the NCI60 cell line panel, suggesting that different tumor genotypes reshape a limited set of effector proteins. We searched our dataset for druggable conformational aberrations and identified 49 changes in the cancer conformational landscape that correlated with the growth inhibition profiles of 300 drug candidates out of 50,000 small molecules. We found that alterations in heat shock proteins are key predictors of anticancer drug efficacy, which implies that the proteostasis network may have a general but hitherto unrecognized role in maintaining malignancy. Individual lysine sites may serve as biomarkers to guide drug selection or may be directly targeted for anticancer drug development.

Label-free visual proteomics: Coupling MS- and EM-based approaches in structural biology

Combining diverse experimental structural and interactomic methods allows for the construction of comprehensible molecular encyclopedias of biological systems. Typically, this involves merging several independent approaches that provide complementary structural and functional information from multiple perspectives and at different resolution ranges. A particularly potent combination lies in coupling structural information from cryoelectron microscopy or tomography (cryo-EM or cryo-ET) with interactomic and structural information from mass spectrometry (MS)-based structural proteomics. Cryo-EM/ET allows for sub-nanometer visualization of biological specimens in purified and near-native states, while MS provides bioanalytical information for proteins and protein complexes without introducing additional labels. Here we highlight recent achievements in protein structure and interactome determination using cryo-EM/ET that benefit from additional MS analysis. We also give our perspective on how combining cryo-EM/ET and MS will continue bridging gaps between molecular and cellular studies by capturing and describing 3D snapshots of proteomes and interactomes.

Structural Alternation in Heat Shock Proteins of Activated Macrophages

The inflammatory response of macrophages is an orderly and complex process under strict regulation accompanied by drastic changes in morphology and functions. It is predicted that proteins will undergo structural changes during these finely regulated processes. However, changes in structural proteome in macrophages during the inflammatory response remain poorly characterized. In the present study, we applied limited proteolysis coupled mass spectrometry (LiP-MS) to identify proteome-wide structural changes in lipopolysaccharide (LPS)-activated macrophages. We identified 386 structure-specific proteolytic fingerprints from 230 proteins. Using the Gene Ontology (GO) biological process enrichment, we discovered that proteins with altered structures were enriched into protein folding-related terms, in which HSP60 was ranked as the most changed protein. We verified the structural changes in HSP60 by using cellular thermal shift assay (CETSA) and native CETSA. Our results showed that the thermal stability of HSP60 was enhanced in activated macrophages and formed an HSP10-less complex. In conclusion, we demonstrate that in situ structural systems biology is an effective method to characterize proteomic structural changes and reveal that the structures of chaperone proteins vary significantly during macrophage activation.

Collision Cross Sections for Native Proteomics: Challenges and Opportunities

Recent advancements place a comprehensive catalog of protein structure, oligomeric state, sequence, and modification status tentatively within reach, thus providing an unprecedented roadmap to therapies for many human diseases. To achieve this goal, revolutionary technologies capable of bridging key gaps in our ability to simultaneously measure protein composition and structure must be developed. Much of the current progress in this area has been catalyzed by mass spectrometry (MS) tools, which have become an indispensable resource for interrogating the structural proteome. For example, methods associated with native proteomics seek to comprehensively capture and quantify the endogenous assembly states for all proteins within an organism. Such technologies have often been partnered with ion mobility (IM) separation, from which collision cross section (CCS) information can be rapidly extracted to provide protein size information. IM technologies are also being developed that utilize CCS values to enhance the confidence of protein identification workflows derived from liquid chromatography-IM-MS analyses of enzymatically produced peptide mixtures. Such parallel advancements in technology beg the question: can CCS values prove similarly useful for the identification of intact proteins and their complexes in native proteomics? In this perspective, I examine current evidence and technology trends to explore the promise and limitations of such CCS information for the comprehensive analysis of multiprotein complexes from cellular mixtures.

Structural mapping techniques distinguish the surfaces of fibrillar 1N3R and 1N4R human tau

The rigid core of intracellular tau filaments from Alzheimer's disease (AD), Pick's disease (PiD), and Corticobasal disease (CBD) brains has been shown to differ in their cryo-EM atomic structure. Despite providing critical information on the intimate arrangement of a fraction of htau molecule within the fibrillar scaffold, the cryo-EM studies neither yield a complete picture of tau fibrillar assemblies structure nor contribute insights into the surfaces that define their interactions with numerous cellular components. Here, using proteomic approaches such as proteolysis and molecular covalent painting, we mapped the exposed amino acid stretches at the surface and those constituting the fibrillar core of in vitro-assembled fibrils of human htau containing one N-terminal domain and three (1N3R) or four (1N4R) C-terminal microtubule-binding repeat domains as a result of alternative splicing. Using limited proteolysis, we identified the proteolytic fragments composing the molecular “bar-code” for each type of fibril. Our results are in agreement with structural data reported for filamentous tau from AD, PiD, and CBD cases predigested with the protease pronase. Finally, we report two amino acid stretches, exposed to the solvent in 1N4R not in 1N3R htau, which distinguish the surfaces of these two kinds of fibrils. Our findings open new perspectives for the design of highly specific ligands with diagnostic and therapeutic potential.

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

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

Protein Footprinting via Covalent Protein Painting Reveals Structural Changes of the Proteome in Alzheimer's Disease

Misfolding and aggregation of amyloid-β peptide and hyperphosphorylated tau are molecular markers of Alzheimer's disease (AD), and although the 3D structures of these aberrantly folded proteins have been visualized in exquisite detail, no method has been able to survey protein folding across the proteome in AD. Here, we present covalent protein painting (CPP), a mass spectrometry-based protein footprinting approach to quantify the accessibility of lysine ε-amines for covalent modification at the surface of natively folded proteins. We used CPP to survey the reactivity of 2645 lysine residues and therewith the structural proteome of HEK293T cells and found that reactivity increased upon mild heat shock. CPP revealed that the accessibility of lysine residues for covalent modification in tubulin-β (TUBB), in succinate dehydrogenase (SHDB), and in amyloid-β peptide (Aβ) is altered in human postmortem brain samples of patients with neurodegenerative diseases. The structural alterations of TUBB and SHDB in patients with AD, dementia with Lewy bodies (DLB), or both point to broader perturbations of the 3D proteome beyond Aβ and hyperphosphorylated tau.

A model of full-length RAGE in complex with S100B

The receptor for advanced glycation end products (RAGE) is an immunoglobulin-type multiligand transmembrane protein expressed in numerous cell types, including the central nervous system cells. RAGE interaction with S100B, released during brain tissue damage, leads to RAGE upregulation and initialization of a spiral proinflammatory associated with different neural disorders. Here, we present the structural characterization of the hetero-oligomeric complex of the full-length RAGE with S100B, obtained by a combination of mass spectrometry-based methods and molecular modeling. We predict that RAGE functions as a tightly packed tetramer exposing a positively charged surface formed by V domains for S100B binding. Based on HDX results we demonstrate an allosteric coupling of the distal extracellular V domains and the transmembrane region, indicating a possible mechanism of signal transmission by RAGE across the membrane. Our model provides an insight into RAGE-ligand interactions, providing a basis for the rational design of the therapeutic modifiers of its activity.

Top-Down and Bottom-Up Proteomics Methods to Study RNA Virus Biology

RNA viruses cause a wide range of human diseases that are associated with high mortality and morbidity. In the past decades, the rise of genetic-based screening methods and high-throughput sequencing approaches allowed the uncovering of unique and elusive aspects of RNA virus replication and pathogenesis at an unprecedented scale. However, viruses often hijack critical host functions or trigger pathological dysfunctions, perturbing cellular proteostasis, macromolecular complex organization or stoichiometry, and post-translational modifications. Such effects require the monitoring of proteins and proteoforms both on a global scale and at the structural level. Mass spectrometry (MS) has recently emerged as an important component of the RNA virus biology toolbox, with its potential to shed light on critical aspects of virus-host perturbations and streamline the identification of antiviral targets. Moreover, multiple novel MS tools are available to study the structure of large protein complexes, providing detailed information on the exact stoichiometry of cellular and viral protein complexes and critical mechanistic insights into their functions. Here, we review top-down and bottom-up mass spectrometry-based approaches in RNA virus biology with a special focus on the most recent developments in characterizing host responses, and their translational implications to identify novel tractable antiviral targets.

Integrative proteomics identifies thousands of distinct, multi-epitope, and high-affinity nanobodies

The antibody immune response is essential for the survival of mammals. However, we still lack a systematic understanding of the antibody repertoire. Here, we developed a proteomic strategy to survey, at an unprecedented scale, the landscape of antigen-engaged, circulating camelid heavy-chain antibodies, whose minimal binding fragments are called VHH antibodies or nanobodies. The sensitivity and robustness of this approach were validated with three antigens spanning orders of magnitude in immune responses; thousands of distinct, high-affinity nanobody families were reliably identified and quantified. Using high-throughput structural modeling, cross-linking mass spectrometry, mutagenesis, and deep learning, we mapped and analyzed the epitopes of >100,000 antigen-nanobody complexes. Our results revealed a surprising diversity of ultrahigh-affinity camelid nanobodies for specific antigen binding on various dominant epitope clusters. Nanobodies utilize both shape and charge complementarity to enable highly selective antigen binding. Interestingly, we found that nanobody-antigen binding can mimic conserved intracellular protein-protein interactions. A record of this paper's Transparent Peer Review process is included in the Supplemental information.

Scratching the surface: native mass spectrometry of peripheral membrane protein complexes

A growing number of integral membrane proteins have been shown to tune their activity by selectively interacting with specific lipids. The ability to regulate biological functions via lipid interactions extends to the diverse group of proteins that associate only peripherally with the lipid bilayer. However, the structural basis of these interactions remains challenging to study due to their transient and promiscuous nature. Recently, native mass spectrometry has come into focus as a new tool to investigate lipid interactions in membrane proteins. Here, we outline how the native MS strategies developed for integral membrane proteins can be applied to generate insights into the structure and function of peripheral membrane proteins. Specifically, native MS studies of proteins in complex with detergent-solubilized lipids, bound to lipid nanodiscs, and released from native-like lipid vesicles all shed new light on the role of lipid interactions. The unique ability of native MS to capture and interrogate protein–protein, protein–ligand, and protein–lipid interactions opens exciting new avenues for the study of peripheral membrane protein biology.

Proteomic Approaches to Study SARS-CoV-2 Biology and COVID-19 Pathology

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), was declared a pandemic infection in March 2020. As of December 2020, two COVID-19 vaccines have been authorized for emergency use by the U.S. Food and Drug Administration, but there are no effective drugs to treat COVID-19, and pandemic mitigation efforts like physical distancing have had acute social and economic consequences. In this perspective, we discuss how the proteomic research community can leverage technologies and expertise to address the pandemic by investigating four key areas of study in SARS-CoV-2 biology. Specifically, we discuss how (1) mass spectrometry-based structural techniques can overcome limitations and complement traditional structural approaches to inform the dynamic structure of SARS-CoV-2 proteins, complexes, and virions; (2) virus-host protein-protein interaction mapping can identify the cellular machinery required for SARS-CoV-2 replication; (3) global protein abundance and post-translational modification profiling can characterize signaling pathways that are rewired during infection; and (4) proteomic technologies can aid in biomarker identification, diagnostics, and drug development in order to monitor COVID-19 pathology and investigate treatment strategies. Systems-level high-throughput capabilities of proteomic technologies can yield important insights into SARS-CoV-2 biology that are urgently needed during the pandemic, and more broadly, can inform coronavirus virology and host biology.

Dynamic 3D proteomes reveal protein functional alterations at high resolution in situ

Biological processes are regulated by intermolecular interactions and chemical modifications that do not affect protein levels, thus escaping detection in classical proteomic screens. We demonstrate here that a global protein structural readout based on limited proteolysis-mass spectrometry (LiP-MS) detects many such functional alterations, simultaneously and in situ, in bacteria undergoing nutrient adaptation and in yeast responding to acute stress. The structural readout, visualized as structural barcodes, captured enzyme activity changes, phosphorylation, protein aggregation, and complex formation, with the resolution of individual regulated functional sites such as binding and active sites. Comparison with prior knowledge, including other ‘omics data, showed that LiP-MS detects many known functional alterations within well-studied pathways. It suggested distinct metabolite-protein interactions and enabled identification of a fructose-1,6-bisphosphate-based regulatory mechanism of glucose uptake in E. coli. The structural readout dramatically increases classical proteomics coverage, generates mechanistic hypotheses, and paves the way for in situ structural systems biology.

•

Dynamic structural proteomic screens detect functional changes at high resolution

•

Detect enzyme activity, phosphorylation, and molecular interactions in situ

•

Generate new molecular hypotheses and increase functional proteomics coverage

•

Enabled discovery of a regulatory mechanism of glucose uptake in E. coli

Parallel Chemoselective Profiling for Mapping Protein Structure

Solution-based structural techniques complement high-resolution structural data by providing insight into the oft-missed links between protein structure and dynamics. Here, we present Parallel Chemoselective Profiling, a solution-based structural method for characterizing protein structure and dynamics. Our method utilizes deep mutational scanning saturation mutagenesis data to install amino acid residues with specific chemistries at defined positions on the solvent-exposed surface of a protein. Differences in the extent of labeling of installed mutant residues are quantified using targeted mass spectrometry, reporting on each residue's local environment and structural dynamics. Using our method, we studied how conformation-selective, ATP-competitive inhibitors affect the local and global structure and dynamics of full-length Src kinase. Our results highlight how parallel chemoselective profiling can be used to study a dynamic multi-domain protein, and suggest that our method will be a useful addition to the relatively small toolkit of existing protein footprinting techniques.

Emerging Role of Mass Spectrometry-Based Structural Proteomics in Elucidating Intrinsic Disorder in Proteins

Inherent disorder is an integral part of all proteomes, represented as fully or partially unfolded proteins. The lack of order in intrinsically disordered proteins (IDPs) results in an incredibly flexible, floppy, and heterogeneous ensemble, contrary to the well-structured and unique organization of folded proteins. Despite such unusual demeanor, IDPs are crucial for numerous cellular processes and are increasingly being associated with disease-causing pathologies. These warrant more intensive investigation of this atypical class of protein. Traditional biophysical tools, however, fall short of analyzing IDPs, thus making their structure-function characterization challenging. Mass spectrometry (MS) in recent years has evolved as a valuable tool for elucidating the unusual conformational facets of IDPs. In this review, the features of advanced MS techniques such as Hydrogen-deuterium exchange (HDX)-MS, native MS, limited proteolysis (LiP)-MS, chemical cross-linking (XL)-MS, and Fast photochemical oxidation of proteins (FPOP)-MS are briefly discussed. Recent MS studies on IDPs and the unique advantages/shortfalls associated with the above methods while evaluating structural proteomics of IDPs, are illustrated. Eventually the future scope of the MS methods in further decoding the unexplored landscapes of IDPs is presented.

Small Molecule Interactome Mapping by Photo-Affinity Labeling (SIM-PAL) to Identify Binding Sites of Small Molecules on a Proteome-Wide Scale

Identification and characterization of small molecule-protein interactions is critical to understanding the mechanism of action of bioactive small molecules. Photo-affinity labeling (PAL) enables the capture of noncovalent interactions for enrichment and unbiased analysis by mass spectrometry (MS). Quantitative proteomics of the enriched proteome reveals potential interactions, and MS characterization of binding sites provides validation and structural insight into the interactions. Here, we describe the identification of the protein targets and binding sites of a small molecule using small molecule interactome mapping by PAL (SIM-PAL). Cells are exposed to a diazirine-alkyne-functionalized small molecule, and binding interactions are covalently captured upon UV irradiation. An isotopically coded, acid-cleavable biotin azide handle is attached to the conjugated proteins using copper-catalyzed azide-alkyne cycloaddition. Biotin-labeled proteins are enriched for on-bead digestion and quantitative proteomics. Acid cleavage of the handle releases the bead-bound conjugated peptides for MS analysis and isotope-directed assignment of the binding site. © 2019 by John Wiley & Sons, Inc. Basic Protocol 1: Generation of a small molecule-conjugated protein sample following treatment of live cells Alternate Protocol: Generation of a small molecule-conjugated protein sample following treatment of cell lysate Basic Protocol 2: Copper-catalyzed azide-alkyne cycloaddition functionalization and enrichment of labeled peptides Support Protocol 1: Synthesis of acid-cleavable, isotopically coded biotin picolyl azide handle Support Protocol 2: Monitoring enrichment by immunoblotting Basic Protocol 3: Mass spectrometry analysis to identify interacting proteins and conjugation sites.

Insight into the Structure of the "Unstructured" Tau Protein

Combining structural proteomics experimental data with computational methods is a powerful tool for protein structure prediction. Here, we apply a recently developed approach for de novo protein structure determination based on the incorporation of short-distance crosslinking data as constraints in discrete molecular dynamics simulations (CL-DMD), for the determination of the conformational ensemble of tau protein in solution. The predicted structures were in agreement with surface modification and long-distance crosslinking data. Tau in solution was found as an ensemble of rather compact globular conformations with distinct topology, inter-residue contacts, and a number of transient secondary-structure elements. Regions important for pathological aggregation consistently were found to contain β strands. The determined structures are compatible with the tau protein in solution being a molten globule at near-ground state with persistent residual structural features which we were able to capture by CL-DMD. The predicted structure may facilitate an understanding of the misfolding and oligomerization pathways of the tau protein.

[Progress in structural proteomics research]

The structures of proteins are directly related to their biological functions. The regulation of protein functions mainly depends on the dynamic regulation of their conformations and interactions. The study of protein structures and functions plays an essential role in the field of life science, which is also an important direction of proteomics development. The emergence of proteomics has led to major technological advances in mass spectrometry (MS). These advancements have not only benefitted MS-based high-throughput proteomics but have also increased the impact of MS in the fields of structural and molecular biology. This review briefly describes the principles, progresses and applications of the MS-based structural proteomics methods in recent years, including the native MS analysis of active proteins, limited proteolysis, chemical cross-linking, hydrogen-deuterium exchange, covalent labeling, and thermal proteome profiling. Finally, future development of the structural proteomics was summarized and prospected.

In-Search Assignment of Monoisotopic Peaks Improves the Identification of Cross-Linked Peptides

Cross-linking/mass spectrometry has undergone a maturation process akin to standard proteomics by adapting key methods such as false discovery rate control and quantification. A poorly evaluated search setting in proteomics is the consideration of multiple (lighter) alternative values for the monoisotopic precursor mass to compensate for possible misassignments of the monoisotopic peak. Here, we show that monoisotopic peak assignment is a major weakness of current data handling approaches in cross-linking. Cross-linked peptides often have high precursor masses, which reduces the presence of the monoisotopic peak in the isotope envelope. Paired with generally low peak intensity, this generates a challenge that may not be completely solvable by precursor mass assignment routines. We therefore took an alternative route by '"in-search assignment of the monoisotopic peak" in the cross-link database search tool Xi (Xi-MPA), which considers multiple precursor masses during database search. We compare and evaluate the performance of established preprocessing workflows that partly correct the monoisotopic peak and Xi-MPA on three publicly available data sets. Xi-MPA always delivered the highest number of identifications with ∼2 to 4-fold increase of PSMs without compromising identification accuracy as determined by FDR estimation and comparison to crystallographic models.

Structural prediction of protein models using distance restraints derived from cross-linking mass spectrometry data

This protocol describes a workflow for creating structural models of proteins or protein complexes using distance restraints derived from cross-linking mass spectrometry experiments. The distance restraints are used (i) to adjust preliminary models that are calculated on the basis of a homologous template and primary sequence, and (ii) to select the model that is in best agreement with the experimental data. In the case of protein complexes, the cross-linking data are further used to dock the subunits to one another to generate models of the interacting proteins. Predicting models in such a manner has the potential to indicate multiple conformations and dynamic changes that occur in solution. This modeling protocol is compatible with many cross-linking workflows and uses open-source programs or programs that are free for academic users and do not require expertise in computational modeling. This protocol is an excellent additional application with which to use cross-linking results for building structural models of proteins. The established protocol is expected to take 6-12 d to complete, depending on the size of the proteins and the complexity of the cross-linking data.

The Druggable Pocketome of Corynebacterium diphtheriae: A New Approach for in silico Putative Druggable Targets

Diphtheria is an acute and highly infectious disease, previously regarded as endemic in nature but vaccine-preventable, is caused by Corynebacterium diphtheriae (Cd). In this work, we used an in silico approach along the 13 complete genome sequences of C. diphtheriae followed by a computational assessment of structural information of the binding sites to characterize the “pocketome druggability.” To this end, we first computed the “modelome” (3D structures of a complete genome) of a randomly selected reference strain Cd NCTC13129; that had 13,763 open reading frames (ORFs) and resulted in 1,253 (∼9%) structure models. The amino acid sequences of these modeled structures were compared with the remaining 12 genomes and consequently, 438 conserved protein sequences were obtained. The RCSB-PDB database was consulted to check the template structures for these conserved proteins and as a result, 401 adequate 3D models were obtained. We subsequently predicted the protein pockets for the obtained set of models and kept only the conserved pockets that had highly druggable (HD) values (137 across all strains). Later, an off-target host homology analyses was performed considering the human proteome using NCBI database. Furthermore, the gene essentiality analysis was carried out that gave a final set of 10-conserved targets possessing highly druggable protein pockets. To check the target identification robustness of the pipeline used in this work, we crosschecked the final target list with another in-house target identification approach for C. diphtheriae thereby obtaining three common targets, these were; hisE-phosphoribosyl-ATP pyrophosphatase, glpX-fructose 1,6-bisphosphatase II, and rpsH-30S ribosomal protein S8. Our predicted results suggest that the in silico approach used could potentially aid in experimental polypharmacological target determination in C. diphtheriae and other pathogens, thereby, might complement the existing and new drug-discovery pipelines.

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

We present an integrated experimental and computational approach for de novo protein structure determination in which short-distance cross-linking data are incorporated into rapid discrete molecular dynamics (DMD) simulations as constraints, reducing the conformational space and achieving the correct protein folding on practical time scales. We tested our approach on myoglobin and FK506 binding protein-models for α helix-rich and β sheet-rich proteins, respectively-and found that the lowest-energy structures obtained were in agreement with the crystal structure, hydrogen-deuterium exchange, surface modification, and long-distance cross-linking validation data. Our approach is readily applicable to other proteins with unknown structures.

SOLEIL shining on the solution-state structure of biomacromolecules by synchrotron X-ray footprinting at the Metrology beamline

Synchrotron X-ray footprinting complements the techniques commonly used to define the structure of molecules such as crystallography, small-angle X-ray scattering and nuclear magnetic resonance. It is remarkably useful in probing the structure and interactions of proteins with lipids, nucleic acids or with other proteins in solution, often better reflecting the in vivo state dynamics. To date, most X-ray footprinting studies have been carried out at the National Synchrotron Light Source, USA, and at the European Synchrotron Radiation Facility in Grenoble, France. This work presents X-ray footprinting of biomolecules performed for the first time at the X-ray Metrology beamline at the SOLEIL synchrotron radiation source. The installation at this beamline of a stopped-flow apparatus for sample delivery, an irradiation capillary and an automatic sample collector enabled the X-ray footprinting study of the structure of the soluble protein factor H (FH) from the human complement system as well as of the lipid-associated hydrophobic protein S3 oleosin from plant seed. Mass spectrometry analysis showed that the structural integrity of both proteins was not affected by the short exposition to the oxygen radicals produced during the irradiation. Irradiated molecules were subsequently analysed using high-resolution mass spectrometry to identify and locate oxidized amino acids. Moreover, the analyses of FH in its free state and in complex with complement C3b protein have allowed us to create a map of reactive solvent-exposed residues on the surface of FH and to observe the changes in oxidation of FH residues upon C3b binding. Studies of the solvent accessibility of the S3 oleosin show that X-ray footprinting offers also a unique approach to studying the structure of proteins embedded within membranes or lipid bodies. All the biomolecular applications reported herein demonstrate that the Metrology beamline at SOLEIL can be successfully used for synchrotron X-ray footprinting of biomolecules.

Seven perspectives on GPCR H/D-exchange proteomics methods

Recent research shows surging interest to visualize human G protein-coupled receptor (GPCR) dynamic structures using the bottom-up H/D-exchange (HDX) proteomics technology. This opinion article clarifies critical technical nuances and logical thinking behind the GPCR HDX proteomics method, to help scientists overcome cross-discipline pitfalls, and understand and reproduce the protocol at high quality. The 2010 89% HDX structural coverage of GPCR was achieved with both structural and analytical rigor. This article emphasizes systematically considering membrane protein structure stability and compatibility with chromatography and mass spectrometry (MS) throughout the pipeline, including the effects of metal ions, zero-detergent shock, and freeze-thaws on HDX result rigor. This article proposes to view bottom-up HDX as two steps to guide choices of detergent buffers and chromatography settings: (I) protein HDX labeling in native buffers, and (II) peptide-centric analysis of HDX labels, which applies (a) bottom-up MS/MS to construct peptide matrix and (b) HDX MS to locate and quantify H/D labels. The detergent-low-TCEP digestion method demystified the challenge of HDX-grade GPCR digestion. GPCR HDX proteomics is a structural approach, thus its choice of experimental conditions should let structure lead and digestion follow, not the opposite.

Electronegativity and intrinsic disorder of preeclampsia-related proteins

Preeclampsia, hemorrhage, and infection are the leading causes of maternal death in underdeveloped countries. Since several proteins associated with preeclampsia are known, we conducted a computational study which evaluated the commonness and potential functionality of intrinsic disorder of these proteins and also made an attempt to characterize their origin. The origin of the preeclampsia-related proteins was assessed with a supervised technique, a Polarity Index Method (PIM), which evaluates the electronegativity of proteins based solely on their sequence. The commonness of intrinsic disorder was evaluated using several disorder predictors from the PONDR family, the charge-hydropathy plot (CH-plot) and cumulative distribution function (CDF) analyses, and using the MobiDB web-based tool, whereas potential functionality of intrinsic disorder was studied with the D2P2 resource and ANCHOR predictor of disorder-based binding sites, and the STRING tool was used to build the interactivity networks of the preeclampsia-related proteins. Peculiarities of the PIM-derived polar profile of the group of preeclampsia-related proteins were then compared with profiles of a group of lipoproteins, antimicrobial peptides, angiogenesis-related proteins, and the intrinsically disordered proteins. Our results showed a high graphical correlation between preeclampsia proteins, lipoproteins, and the angiogenesis proteins. We also showed that many preeclampsia-related proteins contain numerous functional disordered regions. Therefore, these bioinformatics results led us to assume that the preeclampsia proteins are highly associated with the lipoproteins group, and that some preeclampsia-related proteins contain significant amounts of functional disorders.

Characterizing monoclonal antibody structure by carbodiimide/GEE footprinting

Amino acid-specific covalent labeling is well suited to probe protein structure and macromolecular interactions, especially for macromolecules and their complexes that are difficult to examine by alternative means, due to size, complexity, or instability. Here we present a detailed account of carbodiimide-based covalent labeling (with GEE tagging) applied to a glycosylated monoclonal antibody therapeutic, which represents an important class of biologic drugs. Characterization of such proteins and their antigen complexes is essential to development of new biologic-based medicines. In this study, the experiments were optimized to preserve the structural integrity of the protein, and experimental conditions were varied and replicated to establish the reproducibility and precision of the technique. Homology-based models were generated and used to compare the solvent accessibility of the labeled residues, which include D, E, and the C-terminus, against the experimental surface accessibility data in order to understand the accuracy of the approach in providing an unbiased assessment of structure. Data from the protein were also compared to reactivity measures of several model peptides to explain sequence or structure-based variations in reactivity. The results highlight several advantages of this approach. These include: the ease of use at the bench top, the linearity of the dose response plots at high levels of labeling (indicating that the label does not significantly perturb the structure of the protein), the high reproducibility of replicate experiments (<2 % variation in modification extent), the similar reactivity of the 3 target probe residues (as suggested by analysis of model peptides), and the overall positive and significant correlation of reactivity and solvent accessible surface area (the latter values predicted by the homology modeling). Attenuation of reactivity, in otherwise solvent accessible probes, is documented as arising from the effects of positive charge or bond formation between adjacent amine and carboxyl groups, the latter accompanied by observed water loss. The results are also compared with data from hydroxyl radical-mediated oxidative footprinting on the same protein, showing that complementary information is gained from the 2 approaches, although the number of target residues in carbodiimide/GEE labeling is fewer. Overall, this approach is an accurate and precise method for assessing protein structure of biologic drugs.

Hypothetical protein CT398 (CdsZ) interacts with σ(54) (RpoN)-holoenzyme and the type III secretion export apparatus in Chlamydia trachomatis

A significant challenge to bacteriology is the relatively large proportion of proteins that lack sufficient sequence similarity to support functional annotation (i.e. hypothetical proteins). The aim of this study was to apply protein structural homology to gain insights into a candidate protein of unknown function (CT398) within the medically important, obligate intracellular bacterium Chlamydia trachomatis. C. trachomatis is a major human pathogen responsible for numerous infections throughout the world that can lead to blindness and infertility. A 2.12 Å crystal structure of hypothetical protein CT398 was determined that was comprised of N-terminal coiled-coil and C-terminal Zn-ribbon domains. The structure of CT398 displayed a high degree of structural similarity to FlgZ (Flagellar-associated zinc-ribbon domain protein) from Helicobacter pylori. This observation directed analyses of candidate protein partners of CT398, revealing interactions with two paralogous type III secretion system (T3SS) ATPase-regulators (CdsL and FliH) and the alternative sigma factor RpoN (σ(54) ). Furthermore, genetic introduction of a conditional expression, affinity-tagged construct into C. trachomatis enabled the purification of a CT398-RpoN-holoenzyme complex, suggesting a potential role for CT398 in modulating transcriptional activity during infection. The interactions reported here, in tandem with previous FlgZ studies in H. pylori, indicate that CT398 functions as a regulator of several key areas of chlamydial biology throughout the developmental cycle. Accordingly, we propose that CT398 be named CdsZ (Contact-dependent secretion-associated zinc-ribbon domain protein).

Structural insights into interactions between ubiquitin specific protease 5 and its polyubiquitin substrates by mass spectrometry and ion mobility spectrometry

Nanoelectrospray ionization-mass spectrometry and ion mobility-mass spectrometry have been used to study the interactions of the large, multidomain, and conformationally flexible deubiquitinating enzyme ubiquitin specific protease 5 (USP5) with mono- and poly-ubiquitin (Ub) substrates. Employing a C335A active site mutant, mass spectrometry was able to detect the stable and cooperative binding of two mono-Ub molecules at the Zinc-finger ubiquitin binding protein (ZnF-UBP) and catalytic site domains of USP5. Tetra-ubiquitin, in contrast, bound to USP5 with a stoichiometry of 1 : 1, and formed additional interactions with USP5's two ubiquitin associated domains (UBAs). Charge-state distribution and ion mobility analysis revealed that both mono- and tetra-ubiquitin bound to the compact conformation of USP5 only, and that tetra-ubiquitin binding was able to shift the conformational distribution of USP5 from a mixture of extended and compact forms to a completely compact conformation.

Reduced dimensionality (3,2)D NMR experiments and their automated analysis: implications to high-throughput structural studies on proteins

Protein NMR spectroscopy has expanded dramatically over the last decade into a powerful tool for the study of their structure, dynamics, and interactions. The primary requirement for all such investigations is sequence-specific resonance assignment. The demand now is to obtain this information as rapidly as possible and in all types of protein systems, stable/unstable, soluble/insoluble, small/big, structured/unstructured, and so on. In this context, we introduce here two reduced dimensionality experiments – (3,2)D-hNCOcanH and (3,2)D-hNcoCAnH – which enhance the previously described 2D NMR-based assignment methods quite significantly. Both the experiments can be recorded in just about 2-3 h each and hence would be of immense value for high-throughput structural proteomics and drug discovery research. The applicability of the method has been demonstrated using alpha-helical bovine apo calbindin-D9k P43M mutant (75 aa) protein. Automated assignment of this data using AUTOBA has been presented, which enhances the utility of these experiments. The backbone resonance assignments so derived are utilized to estimate secondary structures and the backbone fold using Web-based algorithms. Taken together, we believe that the method and the protocol proposed here can be used for routine high-throughput structural studies of proteins.

Protein structure annotation resources

A key reason three-dimensional (3-D) protein structures are annotated with supporting or derived information is to understand the molecular basis of protein function. To this end, protein structure annotation databases curate key facts and observations, based on community-accepted standards, about the ~100,000 3-D experimental protein structures to date. This review will introduce the primary structure repositories, databases, and value-added structural annotation databases, as well as the range of information they provide. The different levels of annotation data (primary vs. derived vs. inferred) and how they should all be considered accordingly will also be described.

Advances in protein NMR provided by the NIGMS Protein Structure Initiative: impact on drug discovery

Rational drug design relies on the 3D structures of biological macromolecules, with a particular emphasis on proteins. The structural genomics-based high-throughput structure determination platforms established by the Protein Structure Initiative (PSI) of the National Institute of General Medical Science (NIGMS) of the NIH are uniquely suited to provide these structures. NMR plays a critical role in structure determination because many important protein targets do not form the single crystals required for X-ray diffraction. NMR can provide valuable structural and dynamic information on proteins and their drug complexes that cannot be obtained with X-ray crystallography. This review discusses recent advances in NMR that have been driven by structural genomics projects. These advances suggest that the future discovery and design of drugs can increasingly rely on protocols using NMR approaches for the rapid and accurate determination of structures.

Refolding out of guanidine hydrochloride is an effective approach for high-throughput structural studies of small proteins

Low in vivo solubility of recombinant proteins expressed in Escherichia coli can seriously hinder the purification of structural samples for large-scale proteomic NMR and X-ray crystallography studies. Previous results from our laboratory have shown that up to one half of all bacterial and archaeal proteins are insoluble when overexpressed in E. coli. Although a number of strategies may be used to increase in vivo protein solubility, there are no generally applicable methods, and the expression of each insoluble recombinant protein must be individually optimized. For this reason, we have tested a generic denaturation/refolding protein purification procedure to assess the number of structural samples that could be generated by using this methodology. Our results show that a denaturation/refolding protocol is appropriate for many small proteins (<or=18 kD) that are normally soluble in vivo. In addition, refolding the purified proteins by using dialysis against a single buffer allowed us to obtain soluble protein samples of 58% of small proteins that were found in the insoluble fraction in vivo, and 10% of the initial number of proteins provided good heteronuclear single quantum coherence (HSQC) NMR spectra. We conclude that a denaturation/refolding protocol is an efficient way to generate structural samples for high-throughput studies of small proteins.