Structural Assignment Research Articles

Use of customized 3-dimensional printed mandibular prostheses with a dental implant pressure-reducing device in mandibular body defect: A finite element study performing multiresponse surface methodology

Background/purposeSegmental body defects of the mandible result in the complete loss of the affected region. In our previous study, we investigated the clinical applicability of a customized mandible prosthesis (CMP) with a pressure-reducing device (PRD) in an animal study. In this study, we further incorporated dental implants into the CMP and explored the use of dental implant PRD (iPRD) designs. Materials and methodsBy employing a finite element analysis approach, we created 4 types of CMP: CMP, CMP with iPRD, CMP-PRD, and CMP-PRD with iPRD. We developed 2 parameters for the iPRD: cone length (CL) in the upper part and spring pitch (SP) in the lower part. Using the response surface methodology (RSM), we determined the most suitable structural assignment for the iPRD. ResultsOur results indicate that CMP-PRD had the highest von Mises stress value for the entire assembly (1076.26 MPa). For retentive screws and abutments, CMP with iPRD had the highest von Mises stress value (319.97 and 452.78 MPa, respectively). CMP-PRD had the highest principal stress (131.66 MPa) in the anterior mandible. The iPRD reduced principal stress in both the anterior and posterior mandible. Using the RSM, we generated 25 groups for comparison to achieve the most favorable results for the iPRD and we might suggest the CL to 12 mm and the SP to 0.4 mm in the further clinical trials. ConclusionUse of the PRD and iPRD in CMP may resolve the challenges associated with CMP, thereby promoting its usage in clinical practice.

Talarolides Revisited: Cyclic Heptapeptides from an Australian Marine Tunicate-Associated Fungus, Talaromyces sp. CMB-TU011.

Application of a miniaturized 24-well plate system for cultivation profiling (MATRIX) permitted optimization of the cultivation conditions for the marine-derived fungus Talaromyces sp. CMB-TU011, facilitating access to the rare cycloheptapeptide talarolide A (1) along with three new analogues, B-D (2-4). Detailed spectroscopic analysis supported by Marfey's analysis methodology was refined to resolve N-Me-l-Ala from N-Me-d-Ala, l-allo-Ile from l-Ile and l-Leu, and partial and total syntheses of 2, and permitted unambiguous assignment of structures for 1 (revised) and 2-4. Consideration of diagnostic ROESY correlations for the hydroxamates 1 and 3-4, and a calculated solution structure for 1, revealed how cross-ring H-bonding to the hydroxamate moiety influences (defines/stabilizes) the cyclic peptide conformation. Such knowledge draws attention to the prospect that hydroxamates may be used as molecular bridges to access new cyclic peptide conformations, offering the prospect of new biological properties, including enhanced oral bioavailability.

Techniques for Developing Reliable Machine Learning Classifiers Applied to Understanding and Predicting Protein:Protein Interaction Hot Spots.

With machine learning now transforming the sciences, successful prediction of biological structure or activity is mainly limited by the extent and quality of data available for training, the astute choice of features for prediction, and thorough assessment of the robustness of prediction on a variety of new cases. In this chapter, we address these issues while developing and sharing protocols to build a robust dataset and rigorously compare several predictive classifiers using the open-source Python machine learning library, scikit-learn. We show how to evaluate whether enough data has been used for training and whether the classifier has been overfit to training data. The most telling experiment is 500-fold repartitioning of the training and test sets, followed by prediction, which gives a good indication of whether a classifier performs consistently well on different datasets. An intuitive method is used to quantify which features are most important for correct prediction.The resulting well-trained classifier, hotspotter, can robustly predict the small subset of amino acid residues on the surface of a protein that are energetically most important for binding a protein partner: the interaction hot spots. Hotspotter has been trained and tested here on a curated dataset assembled from 1046 non-redundant alanine scanning mutation sites with experimentally measured change in binding free energy values from 97 different protein complexes; this dataset is available to download. The accessible surface area of the wild-type residue at a given site and its degree of evolutionary conservation proved the most important features to identify hot spots. A variant classifier was trained and validated for proteins where only the amino acid sequence is available, augmented by secondary structure assignment. This version of hotspotter requiring fewer features is almost as robust as the structure-based classifier. Application to the ACE2 (angiotensin converting enzyme 2)receptor, which mediates COVID-19 virus entry into human cells, identified the critical hot spot triad of ACE2 residues at the center of the small interface with the CoV-2 spike protein. Hotspotter results can be used to guide the strategic design of protein interfaces and ligands and also to identify likely interfacial residues for protein:protein docking.

Assignment of product ions produced from ciguatoxin-3C provides a deep insight into the fragmentation mechanism of polycyclic ether compounds.

Marine polycyclic ethers have drawn attention owing to their unique chemical structures and involvement in food poisoning and fish killing. To study structural diversity, we performed a structural assignment of product ions produced from a representative ladder-shaped polycyclic ether, ciguatoxin-3C, and elucidated the mechanism of generation. The product ions used for the structural assignment were produced from a precursor ion [M + H]+ using liquid chromatography/quadrupole time-of-flight mass spectrometry, by employing an atmospheric pressure chemical ionization source. Three charged sites were considered at both terminals of a molecule. Typical charge-remote fragmentation was produced at the respective charge sites, yielding a hybrid spectrum. C-C bonds bordering two ethers could cleave and trigger the fission of two other bonds. Prominent ions indicating the serial loss of water molecules resulted from the simultaneous deprivation of ethereal oxygen and hydrogen atoms. The resultant double bonds formed long chains of conjugated polyenes, which stabilized charge via resonance. Three alternative charge sites produce a hybrid spectrum. The simultaneous fission of three bonds was explained. For the first time, intense ions due to serial dehydration were explained by the elimination of ether oxygen atoms and the subsequent conjugation of double bonds. All product ions were considered by the structural features of polycyclic ether that facilitates the formation of conjugated polyenes.

Identification of organic micro-pollutants in surface water using MS-based infrared ion spectroscopy

Comprehensive monitoring of organic micro-pollutants (OMPs) in drinking water sources relies on non-target screening (NTS) using liquid-chromatography and high-resolution mass spectrometry (LC-HRMS). Identification of OMPs is typically based on accurate mass and tandem mass spectrometry (MS/MS) data by matching against entries in compound databases and MS/MS spectral libraries. MS/MS spectra are, however, not always diagnostic for the full molecular structure and, moreover, emerging OMPs or OMP transformation products may not be present in libraries. Here we demonstrate how infrared ion spectroscopy (IRIS), an emerging MS-based method for structural elucidation, can aid in the identification of OMPs. IRIS measures the IR spectrum of an m/z-isolated ion in a mass spectrometer, providing an orthogonal diagnostic for molecular identification. Here, we demonstrate the workflow for identification of OMPs in river water and show how quantum-chemically predicted IR spectra can be used to screen potential candidates and suggest structural assignments. A crucial step herein is to define a set of candidate structures, presumably including the actual OMP, for which we present several strategies based on domain knowledge, the IR spectrum and MS/MS spectrum.

Synthesis, Computational Study of β-lactam Derivatives Bearing Quinazoline Schiff Bases as Anthelmintics

Background: Infections caused by parasites continue to pose a risk to both human and animal health. The most popular drug classes for treating these infections include thiabendazole, imidazothiazoles, levamisole, and avermectins (obtained from the fermentation products of Streptomyces avermitilis). The majority of bacteria that we come across in any form of infection are successfully combatted by β- lactam medicines. Similar to the majority of treatments, problems with treatment resistance to these drugs have evolved over time, necessitating the development of new anthelmintic medications. This study aims to investigate a series of quinazoline-bearing β-lactam rings as potent anthelmintic agents. Methods: The new series of quinazoline bearing β-lactam was synthesized via reaction of 5-bromo anthranilic acid with acetic anhydride to produce 6-bromo-2-methyl-4H-benzo (1,3) oxazin-4-one which was then converted into 3-amino-6-bromo-2-methylquinazolin-4(3H)-one by the reaction of hydrazine hydrate in the presence of anhydrous pyridine. The resultant intermediate then goes through a Schiff reaction with various aromatic aldehydes, followed by reflux with triethylamine and chloroacetyl chloride. Results: Structural assignments of these compounds have been made by elemental analysis, FTIR,1HNMR and Mass spectral data and the purity of the compounds was determined by TLC. Molecular docking studies showed the effective binding of synthesized derivatives with tubulin in comparison to the orientation of standard drugs. The anthelmintic activities of all the synthesized compounds were evaluated separately for their possible using common Indian earthworm Pheritima posthuma. Conclusion: A total of ten derivatives of quinazoline bearing β-lactam ring were designed, synthesized and evaluated against the Indian earthworm Pheritima posthuma. Out of ten derivatives, SQD2 and SQD6, showed promising anthelmintic activity when compared with standard drugs albendazole and piperazine citrate.

Defect rocksalt structures in the La-Na-N system.

Sodium azide (NaN3) is a versatile nitrogen source that can be used for the synthesis of new nitrides under high-pressure and temperature conditions. Reactions between lanthanum nitride (LaN) and sodium azide (NaN3) at 800°C under 8 GPa pressure have led to the discovery of two defect rocksalt phases which are the first reported ternaries in the La-Na-N system. Preliminary structure assignments have been made based on fits to powder X-ray diffraction profiles. One phase is La1-xNa3xN with vacancies at octahedral La sites and interstitial tetrahedral Na cations. This phase has a tetragonally distorted rocksalt structure (space group I4[Formula: see text]mmm, a = 3.8704(2) and c = 5.2098(3) Å for nominal x = 0.10) and the distortion decreases with increasing Na content (space group I4[Formula: see text]mmm, a = 3.8060(2) Å, c = 5.2470(3) Å for nominal x = 0.14), further giving a cubic phase (a = 5.3055(2) Å) for nominal x = 0.25. This coexists with another cubic [Formula: see text] phase (a = 5.1561 (5) Å), tentatively identified as rocksalt 'NaN1/3' stabilized by a small amount of La; NaLayN(1+3y)/3 with y ≈ 1%. These initial investigations reveal that the high-pressure La-Na-N phase diagram may be rich in defect rocksalt-type materials although further work using neutron diffraction will be needed to confirm the structures. This article is part of the theme issue 'Exploring the length scales, timescales and chemistry of challenging materials (Part 1)'.

Comparative metabolomic profiling of Cupriavidus necator B-4383 revealed production of cupriachelin siderophores, one with activity against Cryptococcus neoformans.

Cupriavidus necator H16 is known to be a rich source of linear lipopeptide siderophores when grown under iron-depleted conditions; prior literature termed these compounds cupriachelins. These small molecules bear β-hydroxyaspartate moieties that contribute to a photoreduction of iron when bound as ferric cupriachelin. Here, we present structural assignment of cupriachelins from C. necator B-4383 grown under iron limitation. The characterization of B-4383 cupriachelins is based on MS/MS fragmentation analysis, which was confirmed by 1D- and 2D-NMR for the most abundant analog (1). The cupriachelin congeners distinguish these two strains with differences in the preferred lipid tail; however, our rigorous metabolomic investigation also revealed minor analogs with changes in the peptide core, hinting at a potential mechanism by which these siderophores may reduce biologically unavailable ferric iron (4-6). Antifungal screening of the C. necator B-4383 supernatant extract and the isolated cupriachelin analog (1) revealed inhibitory activity against Cryptococcus neoformans, with IC50 values of 16.6 and 3.2μg/mL, respectively. This antifungal activity could be explained by the critical role of the iron acquisition pathway in the growth and pathogenesis of the C. neoformans fungal pathogen.

Enrichment and structural assignment of geometric isomers of unsaturated furan fatty acids.

Furan fatty acids (FuFAs) are valuable minor fatty acids, which are known for their excellent radical scavenging properties. Typically, the furan moiety is embedded in an otherwise saturated carboxyalkyl chain. Occasionally, these classic FuFAs are accompanied by low amounts of unsaturated furan fatty acids (uFuFAs), which additionally feature one double bond in conjugation with the furan moiety. A recent study produced evidence for the occurrence of two pairs of E-/Z-uFuFA isomers structurally related to saturated uFuFAs. Here, we present a strategy that allowed such trace compounds to be enrichedto a level suited for structure determination by NMR. Given the low amounts and the varied abundance ratio of the four uFuFA isomers, the isolation of individual compounds was not pursued. Instead, the entire isomer mixture was enriched to an amount and purity suitable for structure investigation with contemporary NMR methods. Specifically, lipid extracted from 150g latex, the richest known source of FuFAs, was subsequently fractionated by countercurrent chromatography (CCC), silver ion, and silica gel column chromatography. Analysis of the resulting mixture of four uFuFAs isomers (2.4mg in an abundance ratio of 56:23:11:9) by different NMR techniques including PSYCHE verified that the structures of the two most abundant isomers were E-9-(3-methyl-5-pentylfuran-2-yl)non-8-enoic acid and E-9-(3-methyl-5-pent-1-enylfuran-2-yl)nonanoic acid. Additionally, we introduced a computer-based method to generate an averaged chromatogram from freely selectable GC/MS runs of CCC fractions without the necessity of pooling aliquots. This method was found to besuitable to simplify subsequent enrichment steps.

Validity of Structured Assignment Sheet to Train Argumentation Skills on Buffer Solution

The purpose of this study was to produce structured task sheets to practice argumentation skills on buffer solution material. This research is a development research to produce products with the ADDIE development model which is limited to the design and development analysis stage. The developed structured assignment sheet contains enriched questions to practice argumentation skills on buffer solution material. The data obtained in this study is the feasibility of the validity aspect. The instruments used to obtain content and construct validity data were validation sheets assessed by three validators. Learning devices are declared to meet the validity criteria (based on content and construct) if they get a minimum rating mode (Mo) of 4 (valid) from the range 1 to 5 on a Likert scale. The results showed that according to the assessment component, both content and construct validity got an assessment mode (Mo) of 5 (very valid). The developed structured task sheets are declared valid to train argumentation skills.

Bypassing the Identification: MS2Quant for Concentration Estimations of Chemicals Detected with Nontarget LC-HRMS from MS2 Data.

Nontarget analysis by liquid chromatography-high-resolution mass spectrometry (LC-HRMS) is now widely used to detect pollutants in the environment. Shifting away from targeted methods has led to detection of previously unseen chemicals, and assessing the risk posed by these newly detected chemicals is an important challenge. Assessing exposure and toxicity of chemicals detected with nontarget HRMS is highly dependent on the knowledge of the structure of the chemical. However, the majority of features detected in nontarget screening remain unidentified and therefore the risk assessment with conventional tools is hampered. Here, we developed MS2Quant, a machine learning model that enables prediction of concentration from fragmentation (MS2) spectra of detected, but unidentified chemicals. MS2Quant is an xgbTree algorithm-based regression model developed using ionization efficiency data for 1191 unique chemicals that spans 8 orders of magnitude. The ionization efficiency values are predicted from structural fingerprints that can be computed from the SMILES notation of the identified chemicals or from MS2 spectra of unidentified chemicals using SIRIUS+CSI:FingerID software. The root mean square errors of the training and test sets were 0.55 (3.5×) and 0.80 (6.3×) log-units, respectively. In comparison, ionization efficiency prediction approaches that depend on assigning an unequivocal structure typically yield errors from 2× to 6×. The MS2Quant quantification model was validated on a set of 39 environmental pollutants and resulted in a mean prediction error of 7.4×, a geometric mean of 4.5×, and a median of 4.0×. For comparison, a model based on PaDEL descriptors that depends on unequivocal structural assignment was developed using the same dataset. The latter approach yielded a comparable mean prediction error of 9.5×, a geometric mean of 5.6×, and a median of 5.2× on the validation set chemicals when the top structural assignment was used as input. This confirms that MS2Quant enables to extract exposure information for unidentified chemicals which, although detected, have thus far been disregarded due to lack of accurate tools for quantification. The MS2Quant model is available as an R-package in GitHub for improving discovery and monitoring of potentially hazardous environmental pollutants with nontarget screening.

Assessing the Critical Thinking and Deep Analysis in Medical Education Among Instructional Practices.

The purpose of this study was to examine the application of faculty to stimulate the critical thinking and deep analysis of their students through instructional practice including lecture design, assessment structure, and assignment instructions. Faculty from multiple different health colleges at Saudi Arabia were asked to respond to survey items about the activities they use in their classrooms with regards to designing lectures, assessment structures, and instructional assignments. A correlation analysis was performed to determine if the level of applied critical thinking and deep analysis that is stimulated by faculty members were statistically related between designing lectures, assessment structure, and instructional assignments. An analysis of variance (ANOVA) was also performed to determine if there were significant differences based on the demographic characteristics of the participants and level of applied critical thinking and deep analysis. A correlational analysis revealed that the mean score for designing lectures was 67.276, following by a mean score of 65.233 for instructional assignment and 64.688 for assessment structure. The result of the ANOVA showed that there was a significant difference in the perceptions of the participants between designing lectures, assessment structure, and instructional assignment (p<0.05). The participants applied critical thinking and deep analysis when they design their lectures more than assessments and instructional assignments. They had the flexibility to stimulate critical thinking during the lecture activities. In contrast, this flexibility was limited when they were structuring the assessment as they had instructions to consider and were required to provide a rubric with unified key answer which is a mandatory requirement from the assessment department. This is due to the nature of high level of critical thinking answers that lead to high subjectivity in student responses.

Stability by assigning structures by applying the multivariable subspace identification algorithm for a wind system with a DFIG

In this paper, a controller for a doubly fed induction generator (DFIG) connected to a wind system is proposed. This control assigning its own structures as an optimal control method, the electric model in the DFIG state space is also shown, for which it is expected to estimate a linear model through the subspace technique and thus to design the controller. It will be possible to show that a structure assignment controller is undoubtedly a good option for the control of multivariable systems. The results of the output signals will be analyzed when applying the controller, assigning their own structures, which will allow us to observe that the response and disturbance times are below two tenths of a second.

Discovery and structural assignment of (S)-sydosine from amphipod-derived Aspergillus sydowii MBC15-11F through HRMS, advanced Mosher, and molecular modelling analyses.

This study aims to prioritize fungal strains recovered from under-explored habitats that produce new metabolites. HRMS dereplication is used to avoid structure redundancy, and molecular modelling is used to assign absolute configuration. MBC15-11F was isolated from an amphipod and identified using ITS, 28S, and β-tubulin phylogeny as Aspergillus sydowii. Chemical profiling using taxonomic-based dereplication identified structurally diverse metabolites, including unreported ones. Large-scale fermentation led to the discovery of a new N-acyl adenosine derivative: (S)-sydosine (1) which was elucidated by NMR and HRESIMS analyses. Two known compounds were also identified as predicted by the initial dereplication process. Due to scarcity of 1, molecular modelling was used to assign its absolute configuration without hydrolysis, and is supported by advanced Mosher derivatization. When the isolated compounds were assessed against a panel of bacterial pathogens, only phenamide (3) showed anti-Staphylococcus aureus activity. Fermentation of A. sydowii yielded a new (S)-sydosine and known metabolites as predicted by HRESIMS-aided dereplication. Molecular modelling prediction of the absolute configuration of 1 agreed with advanced Mosher analysis.

Complementary methods for structural assignment of isomeric candidate structures in non-target liquid chromatography ion mobility high-resolution mass spectrometric analysis

Non-target screening with LC/IMS/HRMS is increasingly employed for detecting and identifying the structure of potentially hazardous chemicals in the environment and food. Structural assignment relies on a combination of multidimensional instrumental methods and computational methods. The candidate structures are often isomeric, and unfortunately, assigning the correct structure among a number of isomeric candidate structures still is a key challenge both instrumentally and computationally. While practicing non-target screening, it is usually impossible to evaluate separately the limitations arising from (1) the inability of LC/IMS/HRMS to resolve the isomeric candidate structures and (2) the uncertainty of in silico methods in predicting the analytical information of isomeric candidate structures due to the lack of analytical standards for all candidate structures. Here we evaluate the feasibility of structural assignment of isomeric candidate structures based on in silico–predicted retention time and database collision cross-section (CCS) values as well as based on matching the empirical analytical properties of the detected feature with those of the analytical standards. For this, we investigated 14 candidate structures corresponding to five features detected with LC/HRMS in a spiked surface water sample. Considering the predicted retention times and database CCS values with the accompanying uncertainty, only one of the isomeric candidate structures could be deemed as unlikely; therefore, the annotation of the LC/IMS/HRMS features remained ambiguous. To further investigate if unequivocal annotation is possible via analytical standards, the reversed-phase LC retention times and low- and high-resolution ion mobility spectrometry separation, as well as high-resolution MS2 spectra of analytical standards were studied. Reversed-phase LC separated the highest number of candidate structures while low-resolution ion mobility and high-resolution MS2 spectra provided little means for pinpointing the correct structure among the isomeric candidate structures even if analytical standards were available for comparison. Furthermore, the question arises which prediction accuracy is required from the in silico methods to par the analytical separation. Based on the experimental data of the isomeric candidate structures studied here and previously published in the literature (516 retention time and 569 CCS values), we estimate that to reduce the candidate list by 95% of the structures, the confidence interval of the predicted retention times would need to decrease to below 0.05 min for a 15-min gradient while that of CCS values would need to decrease to 0.15%. Hereby, we set a clear goal to the in silico methods for retention time and CCS prediction.Graphical abstract

Ozone-enabled fatty acid discovery reveals unexpected diversity in the human lipidome

Fatty acid isomers are responsible for an under-reported lipidome diversity across all kingdoms of life. Isomers of unsaturated fatty acids are often masked in contemporary analysis by incomplete separation and the absence of sufficiently diagnostic methods for structure elucidation. Here, we introduce a comprehensive workflow, to discover unsaturated fatty acids through coupling liquid chromatography and mass spectrometry with gas-phase ozonolysis of double bonds. The workflow encompasses semi-automated data analysis and enables de novo identification in complex media including human plasma, cancer cell lines and vernix caseosa. The targeted analysis including ozonolysis enables structural assignment over a dynamic range of five orders of magnitude, even in instances of incomplete chromatographic separation. Thereby we expand the number of identified plasma fatty acids two-fold, including non-methylene-interrupted fatty acids. Detection, without prior knowledge, allows discovery of non-canonical double bond positions. Changes in relative isomer abundances reflect underlying perturbations in lipid metabolism.

Lack of genetic differentiation between two sympatric lacustrine morpho-species within the Astyanax (Characidae: Teleostei) genus, Mexico

We analyzed two morpho-species, Astyanax aeneus and Astyanax caballeroi, coexisting in Lake Catemaco, with ecological differences previously associated with different trophic niches. While A. aeneus is a widely distributed species, A. caballeroi is endemic to Lake Catemaco. Due to the contrasting morphology between these two sympatric species, they were originally assigned to different genera, but little is known about their genetic differentiation. We hypothesized that these two species, which present differentiation in morphology and in trophic niches, co-occur in concomitance with assortative mating and form distinct genetic clusters. We tested this prediction by typing a set of 12 microsatellites in 348 individuals of the two morpho-species, comparing their genetic structure patterns with that of an allopatric population of A. aeneus (i.e., the Maquinas population). Genetic structure analysis, assignment analyses, and estimation of gene flow between the sympatric morpho-species were carried out. Contrary to expectations, there is a lack of genetic differentiation between the A. aeneus and A. caballeroi morpho-species. However, there was a genetic differentiation between Lake Catemaco and Río Maquinas populations of A. aeneus. In addition, we found an asymmetric gene flow pattern, with a larger migration rate from A. aeneus to A. caballeroi than in the other direction. Finally, the allopatric population of A. aeneus showed lower levels of genetic diversity than those reported for both morpho-species in the lacustrine system. Consequently, our results support the notion that these morpho-species are either in an early phase of speciation or represent a single polymorphic species. This model provides relevant information to understanding the presence of polymorphisms under gene flow and their potential impact on the speciation process.

DoubleHelix: nucleic acid sequence identification, assignment and validation tool for cryo-EM and crystal structure models.

Sequence assignment is a key step of the model building process in both cryogenic electron microscopy (cryo-EM) and macromolecular crystallography (MX). If the assignment fails, it can result in difficult to identify errors affecting the interpretation of a model. There are many model validation strategies that help experimentalists in this step of protein model building, but they are virtually non-existent for nucleic acids. Here,I present doubleHelix-a comprehensive method for assignment, identification, and validation of nucleic acid sequences in structures determined using cryo-EM and MX. The method combines a neural network classifier of nucleobase identities and a sequence-independent secondary structure assignment approach. I show that the presented method can successfully assist sequence-assignment step in nucleic-acid model building at lower resolutions, where visual map interpretation is very difficult. Moreover, I present examples of sequence assignment errors detected using doubleHelix in cryo-EM and MX structures of ribosomes deposited in the Protein Data Bank, which escaped the scrutiny of available model-validation approaches. The doubleHelix program source code is available under BSD-3 license at https://gitlab.com/gchojnowski/doublehelix.

"Ghost" Fragment Ions in Structure and Site-Specific Glycoproteomics Analysis.

Mass spectrometry (MS) can unlock crucial insights into the intricate world of glycosylation analysis. Despite its immense potential, the qualitative and quantitative analysis of isobaric glycopeptide structures remains one of the most daunting hurdles in the field of glycoproteomics. The ability to distinguish between these complex glycan structures poses a significant challenge, hindering our ability to accurately measure and understand the role of glycoproteins in biological systems. A few recent publications described the use of collision energy (CE) modulation to improve structural elucidation, especially for qualitative purposes. Different linkages of glycan units usually demonstrate different stabilities under CID/HCD fragmentation conditions. Fragmentation of the glycan moiety produces low molecular weight ions (oxonium ions) that can serve as a structure-specific signature for specific glycan moieties; however, the specificity of these fragments has never been examined closely. Here, we particularly focused on N-glycoproteomics analysis and investigated fragmentation specificity using synthetic stable isotope-labeled N-glycopeptide standards. These standards were isotopically labeled at the reducing terminal GlcNAc, which allowed us to resolve fragments produced by the oligomannose core moiety and fragments generated from outer antennary structures. Our research identified the potential for false-positive structure assignments due to the occurrence of "Ghost" fragments resulting from single glyco unit rearrangement or mannose core fragmentation within the collision cell. To mitigate this issue, we have established a minimal intensity threshold for these fragments to prevent misidentification of structure-specific fragments in glycoproteomics analysis. Our findings provide a crucial step forward in the quest for more accurate and reliable glycoproteomics measurements.

Mechanistic Characterisation of the Bacterial Sesterviridene Synthase from Kitasatospora viridis.

A gene coding for a terpene synthase homolog from Kitasatospora viridis was cloned and expressed in Escherichia coli. The purified recombinant protein possessed sesterterpene synthase activity and efficiently converted geranylfarnesyl diphosphate (GFPP) with 19 % yield into the sesterterpene hydrocarbon sesterviridene A. Large scale enzymatic conversions also allowed for the isolation of two side products that are generated with very low yields of ca. 0.1 %. Several derivatives of sesterviridene A were obtained by chemical transformations, securing the NMR-based structural assignments. The absolute configuration of sesterviridene A was determined by chemical correlation using stereoselectively deuterated precursors and by anomalous dispersion X-ray crystallography. The cyclisation mechanism from GFPP to sesterviridene A was extensively studied through isotopic labelling experiments and DFT calculations.