A perspective on the PDB's impact on the field of glycobiology

Analysis of carbohydrates and glycoconjugates by matrix-assisted laser desorption/ionization mass spectrometry: An update for 2021-2022

The use of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry for the analysis of carbohydrates and glycoconjugates is a well-established technique and this review is the 12th update of the original article published in 1999 and brings coverage of the literature to the end of 2022. As with previous review, this review also includes a few papers that describe methods appropriate to analysis by MALDI, such as sample preparation, even though the ionization method is not MALDI. The review follows the same format as previous reviews. It is divided into three sections: (1) general aspects such as theory of the MALDI process, matrices, derivatization, MALDI imaging, fragmentation, quantification and the use of computer software for structural identification. (2) Applications to various structural types such as oligo- and polysaccharides, glycoproteins, glycolipids, glycosides and biopharmaceuticals, and (3) other general areas such as medicine, industrial processes, natural products and glycan synthesis where MALDI is extensively used. Much of the material relating to applications is presented in tabular form. MALDI is still an ideal technique for carbohydrate analysis, particularly in its ability to produce single ions from each analyte and advancements in the technique and range of applications show little sign of diminishing.

Genetic associations in ankylosing spondylitis: circulating proteins as drug targets and biomarkers

Background

Ankylosing spondylitis (AS) is a complex condition with a significant genetic component. This study explored circulating proteins as potential genetic drug targets or biomarkers to prevent AS, addressing the need for innovative and safe treatments.

Methods

We analyzed extensive data from protein quantitative trait loci (pQTLs) with up to 1,949 instrumental variables (IVs) and selected the top single-nucleotide polymorphism (SNP) associated with AS risk. Utilizing a two-sample Mendelian randomization (MR) approach, we assessed the causal relationships between identified proteins and AS risk. Colocalization analysis, functional enrichment, and construction of protein-protein interaction networks further supported these findings. We utilized phenome-wide MR (phenMR) analysis for broader validation and repurposing of drugs targeting these proteins. The Drug-Gene Interaction database (DGIdb) was employed to corroborate drug associations with potential therapeutic targets. Additionally, molecular docking (MD) techniques were applied to evaluate the interaction between target protein and four potential AS drugs identified from the DGIdb.

Results

Our analysis identified 1,654 plasma proteins linked to AS, with 868 up-regulated and 786 down-regulated. 18 proteins (AGER, AIF1, ATF6B, C4A, CFB, CLIC1, COL11A2, ERAP1, HLA-DQA2, HSPA1L, IL23R, LILRB3, MAPK14, MICA, MICB, MPIG6B, TNXB, and VARS1) that show promise as therapeutic targets for AS or biomarkers, especially MAPK14, supported by evidence of colocalization. PhenMR analysis linked these proteins to AS and other diseases, while DGIdb analysis identified potential drugs related to MAPK14. MD analysis indicated strong binding affinities between MAPK14 and four potential AS drugs, suggesting effective target-drug interactions.

Conclusion

This study underscores the utility of MR analysis in AS research for identifying biomarkers and therapeutic drug targets. The involvement of Th17 cell differentiation-related proteins in AS pathogenesis is particularly notable. Clinical validation and further investigation are essential for future applications.

Genome-wide bioinformatics analysis of human protease capacity for proteolytic cleavage of the SARS-CoV-2 spike glycoprotein

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) primarily enters the cell by binding the virus's spike (S) glycoprotein to the angiotensin-converting enzyme 2 receptor on the cell surface, followed by proteolytic cleavage by host proteases. Studies have identified furin and transmembrane protease serine 2 proteases in priming and triggering cleavages of the S glycoprotein, converting it into a fusion-competent form and initiating membrane fusion, respectively. Alternatively, SARS-CoV-2 can enter the cell through the endocytic pathway, where activation is triggered by lysosomal cathepsin L. However, other proteases are also suspected to be involved in both entry routes. In this study, we conducted a genome-wide bioinformatics analysis to explore the capacity of human proteases in hydrolyzing peptide bonds of the S glycoprotein. Predictive models of sequence specificity for 169 human proteases were constructed and applied to the S glycoprotein together with the method for predicting structural susceptibility to proteolysis of protein regions. After validating our approach on extensively studied S2' and S1/S2 cleavage sites, we applied our method to each peptide bond of the S glycoprotein across all 169 proteases. Our results indicate that various members of the proprotein convertase subtilisin/kexin type, type II transmembrane family serine protease, and kallikrein families, as well as specific coagulation factors, are capable of cleaving S2' or S1/S2 sites. We have also identified a potential cleavage site of cathepsin L at the K790 position within the S2' loop. Structural analysis suggests that cleavage of this site induces conformational changes similar to the cleavage at the R815 (S2') position, leading to the exposure of the fusion peptide and subsequent fusion with the membrane. Other potential cleavage sites and the influence of mutations in common SARS-CoV-2 variants on proteolytic efficiency are discussed.IMPORTANCEThe entry of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) into the cell, activated by host proteases, is considerably more complex in coronaviruses than in most other viruses and is not fully understood. There is evidence that other proteases beyond the known furin and transmembrane protease serine 2 can activate the spike protein. Another example of uncertainty is the cleavage site for the alternative endocytic route of SARS-CoV-2 entrance, which is still unknown. Bioinformatics methods, modeling protease specificity and estimating the structural susceptibility of protein regions to proteolysis, can aid in studying this topic by predicting the involved proteases and their cleavage sites, thereby substantially reducing the amount of experimental work. Elucidating the mechanisms of spike protein activation is crucial for preventing possible future coronavirus pandemics and developing antiviral drugs.

HES4 is a potential biomarker for bladder cancer: a Mendelian randomization study

Background: Patients with bladder cancer (BLCA) have a poor prognosis and little progress has been made in treatment. Therefore, the purpose of this work was to employ Mendelian randomization (MR) and transcriptome analysis to identify a novel biomarker that could be used to reliably diagnose BLCA. Methods: TCGA-BLCA and GSE121711 datasets were obtained from public databases. Genome-wide association study (GWAS) data of BLCA outcome (373,295 samples containing 9,904,926 single nucleotide polymorphisms) were obtained through the IEU OpenGWAS database. Differentially expressed genes were applied as exposure factors, and MR analysis was performed to identify genes that had a causal relationship with BLCA. Then, the patients were divided into high and low expression groups according to the expression levels of candidate genes, and genes with survival differences were identified. Univariate and multivariate Cox regression were used to investigate the prognostic value of the expression of these genes. A nomogram was constructed based on independent prognostic factors, and we analyzed the functions and pathways associated with the identified genes as well as their relationship with the immune microenvironment. Results: HES4 was identified as a biomarker. HES4 status, age, and stage were identified as independent prognostic factors, and an excellent nomogram was established. Bioinformatic analysis suggested that HES4 might be associated with the activation of the immune response, bone development, and cancer pathways. The BLCA samples were divided into high and low HES4 groups. The stromal score and 33 immune cells were remarkably different between the two groups, with HES4 expression being negatively correlated with macrophages and mast cells, and positively correlated with eosinophils and central memory CD4+ T cells. Finally, HES4 was up-regulated in cancer samples in both TCGA-BLCA and GSE121711 datasets. Conclusion: This study identified HES4 as an independent prognostic factor for BLCA outcome based on MR and transcriptome analysis, which provides useful information for future research on and treatment of BLCA.

Cryo-EM elucidates the uroplakin complex structure within liquid-crystalline lipids in the porcine urothelial membrane

The urothelium, a distinct epithelial tissue lining the urinary tract, serves as an essential component in preserving urinary tract integrity and thwarting infections. The asymmetric unit membrane (AUM), primarily composed of the uroplakin complex, constitutes a critical permeability barrier in fulfilling this role. However, the molecular architectures of both the AUM and the uroplakin complex have remained enigmatic due to the paucity of high-resolution structural data. In this study, we utilized cryo-electron microscopy to elucidate the three-dimensional structure of the uroplakin complex within the porcine AUM. While the global resolution achieved was 3.5 Å, we acknowledge that due to orientation bias, the resolution in the vertical direction was determined to be 6.3 Å. Our findings unveiled that the uroplakin complexes are situated within hexagonally arranged crystalline lipid membrane domains, rich in hexosylceramides. Moreover, our research rectifies a misconception in a previous model by confirming the existence of a domain initially believed to be absent, and pinpointing the accurate location of a crucial Escherichia coli binding site implicated in urinary tract infections. These discoveries offer valuable insights into the molecular underpinnings governing the permeability barrier function of the urothelium and the orchestrated lipid phase formation within the plasma membrane.

Unveiling Liquid-Crystalline Lipids in the Urothelial Membrane through Cryo-EM

The urothelium, a distinct epithelial tissue lining the urinary tract, serves as an essential component in preserving urinary tract integrity and thwarting infections. The asymmetric unit membrane (AUM), primarily composed of the uroplakin complex, constitutes a critical permeability barrier in fulfilling this role. However, the molecular architectures of both the AUM and the uroplakin complex have remained enigmatic due to the paucity of high-resolution structural data. In this study, we utilized cryo-electron microscopy to elucidate the three-dimensional structure of the uroplakin complex within the porcine AUM. While the global resolution achieved was 3.5 Å, we acknowledge that due to orientation bias, the resolution in the vertical direction was determined to be 6.3 Å. Our findings unveiled that the uroplakin complexes are situated within hexagonally arranged crystalline lipid membrane domains, rich in hexosylceramides. Moreover, our research rectifies a misconception in a previous model by confirming the existence of a domain initially believed to be absent, and pinpointing the accurate location of a crucial Escherichia coli binding site implicated in urinary tract infections. These discoveries offer valuable insights into the molecular underpinnings governing the permeability barrier function of the urothelium and the orchestrated lipid phase formation within the plasma membrane.

Unveiling Liquid-Crystalline Lipids in the Urothelial Membrane through Cryo-EM

The urothelium, a distinct epithelial tissue lining the urinary tract, serves as an essential component in preserving urinary tract integrity and thwarting infections. The asymmetric unit membrane (AUM), primarily composed of the uroplakin complex, constitutes a critical permeability barrier in fulfilling this role. However, the molecular architectures of both the AUM and the uroplakin complex have remained enigmatic due to the paucity of high-resolution structural data. In this investigation, we employed cryo-electron microscopy to elucidate the three-dimensional structure of the uroplakin complex embedded within the porcine AUM at a resolution of 3.5 Å. Our findings unveiled that the uroplakin complexes are situated within hexagonally arranged crystalline lipid membrane domains, rich in hexosylceramides. Moreover, our research rectifies a misconception in a previous model by confirming the existence of a domain initially believed to be absent, and pinpointing the accurate location of a crucial Escherichia coli binding site implicated in urinary tract infections. These discoveries offer valuable insights into the molecular underpinnings governing the permeability barrier function of the urothelium and the orchestrated lipid phase formation within the plasma membrane.

RCSB Protein Data Bank (RCSB.org): delivery of experimentally-determined PDB structures alongside one million computed structure models of proteins from artificial intelligence/machine learning

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), founding member of the Worldwide Protein Data Bank (wwPDB), is the US data center for the open-access PDB archive. As wwPDB-designated Archive Keeper, RCSB PDB is also responsible for PDB data security. Annually, RCSB PDB serves >10 000 depositors of three-dimensional (3D) biostructures working on all permanently inhabited continents. RCSB PDB delivers data from its research-focused RCSB.org web portal to many millions of PDB data consumers based in virtually every United Nations-recognized country, territory, etc. This Database Issue contribution describes upgrades to the research-focused RCSB.org web portal that created a one-stop-shop for open access to ∼200 000 experimentally-determined PDB structures of biological macromolecules alongside >1 000 000 incorporated Computed Structure Models (CSMs) predicted using artificial intelligence/machine learning methods. RCSB.org is a 'living data resource.' Every PDB structure and CSM is integrated weekly with related functional annotations from external biodata resources, providing up-to-date information for the entire corpus of 3D biostructure data freely available from RCSB.org with no usage limitations. Within RCSB.org, PDB structures and the CSMs are clearly identified as to their provenance and reliability. Both are fully searchable, and can be analyzed and visualized using the full complement of RCSB.org web portal capabilities.

LongBondEliminator: A Molecular Simulation Tool to Remove Ring Penetrations in Biomolecular Simulation Systems

We develop a workflow, implemented as a plugin to the molecular visualization program VMD, that can fix ring penetrations with minimal user input. LongBondEliminator, detects ring piercing artifacts by the long, strained bonds that are the local minimum energy conformation during minimization for some assembled simulation system. The LongBondEliminator tool then automatically treats regions near these long bonds using multiple biases applied through NAMD. By combining biases implemented through the collective variables module, density-based forces, and alchemical techniques in NAMD, LongBondEliminator will iteratively alleviate long bonds found within molecular simulation systems. Through three concrete examples with increasing complexity, a lignin polymer, an viral capsid assembly, and a large, highly glycosylated protein aggrecan, we demonstrate the utility for this method in eliminating ring penetrations from classical MD simulation systems. The tool is available via gitlab as a VMD plugin, and has been developed to be generically useful across a variety of biomolecular simulations.

Molecular determinants of the interaction between HSV-1 glycoprotein D and heparan sulfate

Literature has well-established the importance of 3-O-sulfation of neuronal cell surface glycan heparan sulfate (HS) to its interaction with herpes simplex virus type 1 glycoprotein D (gD). Previous investigations of gD to its viral receptors HVEM and nectin-1 also highlighted the conformational dynamics of gD's N- and C-termini, necessary for viral membrane fusion. However, little is known on the structural interactions of gD with HS. Here, we present our findings on this interface from both the glycan and the protein perspective. We used C-terminal and N-terminal gD variants to probe the role of their respective regions in gD/HS binding. The N-terminal truncation mutants (with Δ1-22) demonstrate equivalent or stronger binding to heparin than their intact glycoproteins, indicating that the first 22 amino acids are disposable for heparin binding. Characterization of the conformational differences between C-terminal truncated mutants by sedimentation velocity analytical ultracentrifugation distinguished between the "open" and "closed" conformations of the glycoprotein D, highlighting the region's modulation of receptor binding. From the glycan perspective, we investigated gD interacting with heparin, heparan sulfate, and other de-sulfated and chemically defined oligosaccharides using surface plasmon resonance and glycan microarray. The results show a strong preference of gD for 6-O-sulfate, with 2-O-sulfation becoming more important in the presence of 6-O-S. Additionally, 3-O-sulfation shifted the chain length preference of gD from longer chain to mid-chain length, reaffirming the sulfation site's importance to the gD/HS interface. Our results shed new light on the molecular details of one of seven known protein-glycan interactions with 3-O-sulfated heparan sulfate.

Protein Data Bank: A Comprehensive Review of 3D Structure Holdings and Worldwide Utilization by Researchers, Educators, and Students

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), funded by the United States National Science Foundation, National Institutes of Health, and Department of Energy, supports structural biologists and Protein Data Bank (PDB) data users around the world. The RCSB PDB, a founding member of the Worldwide Protein Data Bank (wwPDB) partnership, serves as the US data center for the global PDB archive housing experimentally-determined three-dimensional (3D) structure data for biological macromolecules. As the wwPDB-designated Archive Keeper, RCSB PDB is also responsible for the security of PDB data and weekly update of the archive. RCSB PDB serves tens of thousands of data depositors (using macromolecular crystallography, nuclear magnetic resonance spectroscopy, electron microscopy, and micro-electron diffraction) annually working on all permanently inhabited continents. RCSB PDB makes PDB data available from its research-focused web portal at no charge and without usage restrictions to many millions of PDB data consumers around the globe. It also provides educators, students, and the general public with an introduction to the PDB and related training materials through its outreach and education-focused web portal. This review article describes growth of the PDB, examines evolution of experimental methods for structure determination viewed through the lens of the PDB archive, and provides a detailed accounting of PDB archival holdings and their utilization by researchers, educators, and students worldwide.

Exploration, Representation, and Rationalization of the Conformational Phase Space of N-Glycans

Despite their fundamental biological relevance, structure-property relationships in N-glycans are fundamentally lacking, and their highly multidimensional compositional and conformational phase spaces remain largely unexplored. The torsional flexibility of the glycosidic linkages and the ring dynamics result in wide, rugged free-energy landscapes that are difficult to sample in molecular dynamics simulations. We show that a novel enhanced-sampling scheme combining replica exchange with solute and collective-variable tempering, enabling transitions over all relevant energy barriers, delivers converged distributions of solvated N-glycan conformers. Several dimensionality-reduction algorithms are compared and employed to generate conformational free-energy maps in two dimensions. Together with an originally developed conformation-based nomenclature scheme that uniquely identifies glycan conformers, our modeling procedure is applied to reveal the effect of chemical substitutions on the conformational ensemble of selected high-mannose-type and complex glycans. Moreover, the structure-prediction capabilities of two commonly used glycan force fields are assessed via the theoretical prediction of experimentally available nuclear magnetic resonance J-coupling constants. The results especially confirm the key role of ω and ψ torsion angles in discriminating between different conformational states and suggest an intriguing correlation between the torsional and ring-puckering degrees of freedom that may be biologically relevant.

Exploring Gas-Phase MS Methodologies for Structural Elucidation of Branched N-Glycan Isomers

Structural isomers of N-glycans that are identical in mass and atomic composition provide a great challenge to conventional mass spectrometry (MS). This study employs additional dimensions of structural elucidation including ion mobility (IM) spectroscopy coupled to hydrogen/deuterium exchange (HDX) and electron capture dissociation (ECD) to characterize three main A2 N-glycans and their conformers. A series of IM-MS experiments were able to separate the low abundance N-glycans and their linkage-based isomers (α1-3 and α1-6 for A2G1). HDX-IM-MS data indicated the presence of multiple gas-phase structures for each N-glycan including the isomers of A2G1. Identification of A2G1 isomers by their collision cross section was complicated due to the preferential collapse of sugars in the gas phase, but it was possible by further ECD fragmentation. The cyclic IM-ECD approach was capable of assigning and identifying each isomer to its IM peak. Two unique cross-ring fragments were identified for each isomer: m/z = 624.21 for α1-6 and m/z = 462.16 for α1-3. Based on these key fragments, the first IM peak, indicating a more compact conformation, was assigned to α1-3 and the second IM peak, a more extended conformer, was assigned to α1-6.

Artificial intelligence and machine-learning approaches in structure and ligand-based discovery of drugs affecting central nervous system

CNS disorders are indications with a very high unmet medical needs, relatively smaller number of available drugs, and a subpar satisfaction level among patients and caregiver. Discovery of CNS drugs is extremely expensive affair with its own unique challenges leading to extremely high attrition rates and low efficiency. With explosion of data in information age, there is hardly any aspect of life that has not been touched by data driven technologies such as artificial intelligence (AI) and machine learning (ML). Drug discovery is no exception, emergence of big data via genomic, proteomic, biological, and chemical technologies has driven pharmaceutical giants to collaborate with AI oriented companies to revolutionise drug discovery, with the goal of increasing the efficiency of the process. In recent years many examples of innovative applications of AI and ML techniques in CNS drug discovery has been reported. Research on therapeutics for diseases such as schizophrenia, Alzheimer's and Parkinsonism has been provided with a new direction and thrust from these developments. AI and ML has been applied to both ligand-based and structure-based drug discovery and design of CNS therapeutics. In this review, we have summarised the general aspects of AI and ML from the perspective of drug discovery followed by a comprehensive coverage of the recent developments in the applications of AI/ML techniques in CNS drug discovery.

Structure of recombinantly expressed cockroach Lili-Mip protein in glycosylated and deglycosylated forms

BACKGROUND

The Pacific Beetle Cockroach is the only known viviparous cockroach. The pregnant females provide nutrition to the embryos by secreting milk proteins (Lili-Mips), which crystallize in vivo. The crystals that grow in the embryo are heterogeneous in their protein sequence. It is not apparent from the structure determined what role heterogeneity and glycosylation played in crystallization. Lili-Mips are very nutritious.

METHODS

Here, we report the cloning of synthesized Lili-Mip genes, their expression in Saccharomyces cerevisiae as secreted proteins, purification, crystallization, and the determination of a three-dimensional structure of one glycosylated and one deglycosylated form.

RESULTS

A 2.35 Å structure of the glycosylated form is bound to palmitoleic acid and has several Zn atom mediated interactions. A 1.45 Å structure of the deglycosylated protein revals a binding pocket that has both oleic and palmitoleic acid bound. Mass-spectrometry shows that oleic acid and palmitoleic acid are bound to the protein. Docking studies suggest that aliphatic chains of lengths 15, 16, and 18 carbons bind well in the pocket.

CONCLUSIONS

The recombinantly expressed and secreted protein is glycosylated, has a bound fatty acid, is homogenous in its protein sequences, and readily forms crystals. The deglycosylated protein also crystallizes readily, suggesting that the high crystallizability of this protein is independent of glycosylation.

GENERAL SIGNIFICANCE

Lili-Mips belong to the ubiquitous lipocalin family of proteins that bind to a large variety of ligands. While the residues lining the barrel are essential for the affinity of the ligand, our results show the role of side-chain orientations to ligand selectivity.

What is the Sugar Code?

A code is defined by the nature of the symbols, which are used to generate information‐storing combinations (e. g. oligo‐ and polymers). Like nucleic acids and proteins, oligo‐ and polysaccharides are ubiquitous, and they are a biochemical platform for establishing molecular messages. Of note, the letters of the sugar code system (third alphabet of life) excel in coding capacity by making an unsurpassed versatility for isomer (code word) formation possible by variability in anomery and linkage position of the glycosidic bond, ring size and branching. The enzymatic machinery for glycan biosynthesis (writers) realizes this enormous potential for building a large vocabulary. It includes possibilities for dynamic editing/erasing as known from nucleic acids and proteins. Matching the glycome diversity, a large panel of sugar receptors (lectins) has developed based on more than a dozen folds. Lectins ‘read’ the glycan‐encoded information. Hydrogen/coordination bonding and ionic pairing together with stacking and C−H/π‐interactions as well as modes of spatial glycan presentation underlie the selectivity and specificity of glycan‐lectin recognition. Modular design of lectins together with glycan display and the nature of the cognate glycoconjugate account for the large number of post‐binding events. They give an entry to the glycan vocabulary its functional, often context‐dependent meaning(s), hereby building the dictionary of the sugar code.

How the Protein Data Bank changed biology: An introduction to the JBC Reviews thematic series, part 1

This collection of articles celebrates the 50th anniversary of the Protein Data Bank (PDB), the single global digital archive of biological macromolecular structures. The impact of the PDB is immense; we have invited a number of top researchers in structural biology to illustrate its influence on an array of scientific fields. What emerges is a compelling picture of the synergism between the PDB and the explosive progress witnessed in many scientific areas. Availability of reliable, openly accessible, well-archived structural information has arguably had more impact on cell and molecular biology than even some of the enabling technologies such as PCR. We have seen the science move from a time when structural biologists contributed the lion’s share of the structures to the PDB and for discussion within their community to a time when any effort to achieve in-depth understanding of a biochemical or cell biological question demands an interdisciplinary approach built atop structural underpinnings.