Corrigendum: Determination of CSF GFAP, CCN5, and vWF levels enhances the diagnostic accuracy of clinically defined MS from non-MS patients with CSF oligoclonal bands.

[This corrects the article DOI: 10.3389/fimmu.2021.811351.].

Bending a photonic wire into a ring.

Natural light-harvesting systems absorb sunlight and transfer its energy to the reaction centre, where it is used for photosynthesis. Synthetic chromophore arrays provide useful models for understanding energy migration in these systems. Research has focused on mimicking rings of chlorophyll molecules found in purple bacteria, known as 'light-harvesting system 2'. Linear meso-meso linked porphyrin chains mediate rapid energy migration, but until now it has not been possible to bend them into rings. Here we show that oligo-pyridyl templates can be used to bend these rod-like photonic wires to create covalent nanorings that consist of 24 porphyrin units and a single butadiyne link. Their elliptical conformations have been probed by scanning tunnelling microscopy. This system exhibits two excited state energy transfer processes: one from a bound template to the peripheral porphyrins and one, in the template-free ring, from the exciton-coupled porphyrin array to the π-conjugated butadiyne-linked porphyrin dimer segment.

Metabolomics detects clinically silent neuroinflammatory lesions earlier than neurofilament-light chain in a focal multiple sclerosis animal model.

BACKGROUND: Despite widespread searches, there are currently no validated biofluid markers for the detection of subclinical neuroinflammation in multiple sclerosis (MS). The dynamic nature of human metabolism in response to changes in homeostasis, as measured by metabolomics, may allow early identification of clinically silent neuroinflammation. Using the delayed-type hypersensitivity (DTH) MS rat model, we investigated the serum and cerebrospinal fluid (CSF) metabolomics profiles and neurofilament-light chain (NfL) levels, as a putative marker of neuroaxonal damage, arising from focal, clinically silent neuroinflammatory brain lesions and their discriminatory abilities to distinguish DTH animals from controls. METHODS: 1H nuclear magnetic resonance (NMR) spectroscopy metabolomics and NfL measurements were performed on serum and CSF at days 12, 28 and 60 after DTH lesion initiation. Supervised multivariate analyses were used to determine metabolomics differences between DTH animals and controls. Immunohistochemistry was used to assess the extent of neuroinflammation and tissue damage. RESULTS: Serum and CSF metabolomics perturbations were detectable in DTH animals (vs. controls) at all time points, with the greatest change occurring at the earliest time point (day 12) when the neuroinflammatory response was most intense (mean predictive accuracy [SD]-serum: 80.6 [10.7]%, p < 0.0001; CSF: 69.3 [13.5]%, p < 0.0001). The top discriminatory metabolites at day 12 (serum: allantoin, cytidine; CSF: glutamine, glucose) were all reduced in DTH animals compared to controls, and correlated with histological markers of neuroinflammation, particularly astrogliosis (Pearson coefficient, r-allantoin: r = - 0.562, p = 0.004; glutamine: r = - 0.528, p = 0.008). Serum and CSF NfL levels did not distinguish DTH animals from controls at day 12, rather, significant differences were observed at day 28 (mean [SEM]-serum: 38.5 [4.8] vs. 17.4 [2.6] pg/mL, p = 0.002; CSF: 1312.0 [379.1] vs. 475.8 [74.7] pg/mL, p = 0.027). Neither serum nor CSF NfL levels correlated with markers of neuroinflammation; serum NfL did, however, correlate strongly with axonal loss (r = 0.641, p = 0.001), but CSF NfL did not (p = 0.137). CONCLUSIONS: While NfL levels were elevated later in the pathogenesis of the DTH lesion, serum and CSF metabolomics were able to detect early, clinically silent neuroinflammation and are likely to present sensitive biomarkers for the assessment of subclinical disease activity in patients.

Reading and erasing of the phosphonium analogue of trimethyllysine by epigenetic proteins.

N ε-Methylation of lysine residues in histones plays an essential role in the regulation of eukaryotic transcription. The 'highest' methylation mark, N ε-trimethyllysine, is specifically recognised by N ε-trimethyllysine binding 'reader' domains, and undergoes demethylation, as catalysed by 2-oxoglutarate dependent JmjC oxygenases. We report studies on the recognition of the closest positively charged N ε-trimethyllysine analogue, i.e. its trimethylphosphonium derivative (KPme3), by N ε-trimethyllysine histone binding proteins and Nε-trimethyllysine demethylases. Calorimetric and computational studies with histone binding proteins reveal that H3KP4me3 binds more tightly than the natural H3K4me3 substrate, though the relative differences in binding affinity vary. Studies with JmjC demethylases show that some, but not all, of them can accept the phosphonium analogue of their natural substrates and that the methylation state selectivity can be changed by substitution of nitrogen for phosphorus. The combined results reveal that very subtle changes, e.g. substitution of nitrogen for phosphorus, can substantially affect interactions between ligand and reader domains / demethylases, knowledge that we hope will inspire the development of highly selective small molecules modulating their activity.

Pathogen-sugar interactions revealed by universal saturation transfer analysis.

Many pathogens exploit host cell-surface glycans. However, precise analyses of glycan ligands binding with heavily modified pathogen proteins can be confounded by overlapping sugar signals and/or compounded with known experimental constraints. Universal saturation transfer analysis (uSTA) builds on existing nuclear magnetic resonance spectroscopy to provide an automated workflow for quantitating protein-ligand interactions. uSTA reveals that early-pandemic, B-origin-lineage severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike trimer binds sialoside sugars in an "end-on" manner. uSTA-guided modeling and a high-resolution cryo-electron microscopy structure implicate the spike N-terminal domain (NTD) and confirm end-on binding. This finding rationalizes the effect of NTD mutations that abolish sugar binding in SARS-CoV-2 variants of concern. Together with genetic variance analyses in early pandemic patient cohorts, this binding implicates a sialylated polylactosamine motif found on tetraantennary N-linked glycoproteins deep in the human lung as potentially relevant to virulence and/or zoonosis.

Asymmetric Azidation under Hydrogen Bonding Phase-Transfer Catalysis: A Combined Experimental and Computational Study.

Asymmetric catalytic azidation has increased in importance to access enantioenriched nitrogen containing molecules, but methods that employ inexpensive sodium azide remain scarce. This encouraged us to undertake a detailed study on the application of hydrogen bonding phase-transfer catalysis (HB-PTC) to enantioselective azidation with sodium azide. So far, this phase-transfer manifold has been applied exclusively to insoluble metal alkali fluorides for carbon-fluorine bond formation. Herein, we disclose the asymmetric ring opening of meso aziridinium electrophiles derived from ß-chloroamines with sodium azide in the presence of a chiral bisurea catalyst. The structure of novel hydrogen bonded azide complexes was analyzed computationally, in the solid state by X-ray diffraction, and in solution phase by 1H and 14N/15N NMR spectroscopy. With N-isopropylated BINAM-derived bisurea, end-on binding of azide in a tripodal fashion to all three NH bonds is energetically favorable, an arrangement reminiscent of the corresponding dynamically more rigid trifurcated hydrogen-bonded fluoride complex. Computational analysis informs that the most stable transition state leading to the major enantiomer displays attack from the hydrogen-bonded end of the azide anion. All three H-bonds are retained in the transition state; however, as seen in asymmetric HB-PTC fluorination, the H-bond between the nucleophile and the monodentate urea lengthens most noticeably along the reaction coordinate. Kinetic studies corroborate with the turnover rate limiting event resulting in a chiral ion pair containing an aziridinium cation and a catalyst-bound azide anion, along with catalyst inhibition incurred by accumulation of NaCl. This study demonstrates that HB-PTC can serve as an activation mode for inorganic salts other than metal alkali fluorides for applications in asymmetric synthesis.

Metabolomic Biomarkers in Blood Samples Identify Cancers in a Mixed Population of Patients with Nonspecific Symptoms.

PURPOSE: Early diagnosis of cancer is critical for improving patient outcomes, but cancers may be hard to diagnose if patients present with nonspecific signs and symptoms. We have previously shown that nuclear magnetic resonance (NMR) metabolomics analysis can detect cancer in animal models and distinguish between differing metastatic disease burdens. Here, we hypothesized that biomarkers within the blood metabolome could identify cancers within a mixed population of patients referred from primary care with nonspecific symptoms, the so-called "low-risk, but not no-risk" patient group, as well as distinguishing between those with and without metastatic disease. EXPERIMENTAL DESIGN: Patients (n = 304 comprising modeling, n = 192, and test, n = 92) were recruited from 2017 to 2018 from the Oxfordshire Suspected CANcer (SCAN) pathway, a multidisciplinary diagnostic center (MDC) referral pathway for patients with nonspecific signs and symptoms. Blood was collected and analyzed by NMR metabolomics. Orthogonal partial least squares discriminatory analysis (OPLS-DA) models separated patients, based upon diagnoses received from the MDC assessment, within 62 days of initial appointment. RESULTS: Area under the ROC curve for identifying patients with solid tumors in the independent test set was 0.83 [95% confidence interval (CI): 0.72-0.95]. Maximum sensitivity and specificity were 94% (95% CI: 73-99) and 82% (95% CI: 75-87), respectively. We could also identify patients with metastatic disease in the cohort of patients with cancer with sensitivity and specificity of 94% (95% CI: 72-99) and 88% (95% CI: 53-98), respectively. CONCLUSIONS: For a mixed group of patients referred from primary care with nonspecific signs and symptoms, NMR-based metabolomics can assist their diagnosis, and may differentiate both those with malignancies and those with and without metastatic disease. See related commentary by Van Tine and Lyssiotis, p. 1477.

Objective biomarkers for clinical relapse in multiple sclerosis: a metabolomics approach.

Accurate determination of relapses in multiple sclerosis is important for diagnosis, classification of clinical course and therapeutic decision making. The identification of biofluid markers for multiple sclerosis relapses would add to our current diagnostic armamentarium and increase our understanding of the biology underlying the clinical expression of inflammation in multiple sclerosis. However, there is presently no biofluid marker capable of objectively determining multiple sclerosis relapses although some, in particular neurofilament-light chain, have shown promise. In this study, we sought to determine if metabolic perturbations are present during multiple sclerosis relapses, and, if so, identify candidate metabolite biomarkers and evaluate their discriminatory abilities at both group and individual levels, in comparison with neurofilament-light chain. High-resolution global and targeted 1H nuclear magnetic resonance metabolomics as well as neurofilament-light chain measurements were performed on the serum in four groups of relapsing-remitting multiple sclerosis patients, stratified by time since relapse onset: (i) in relapse (R); (ii) last relapse (LR) ≥ 1 month (M) to < 6 M ago; (iii) LR ≥ 6 M to < 24 M ago; and (iv) LR ≥ 24 M ago. Two hundred and one relapsing-remitting multiple sclerosis patients were recruited: R (n = 38), LR 1-6 M (n = 28), LR 6-24 M (n = 34), LR ≥ 24 M (n = 101). Using supervised multivariate analysis, we found that the global metabolomics profile of R patients was significantly perturbed compared to LR ≥ 24 M patients. Identified discriminatory metabolites were then quantified using targeted metabolomics. Lysine and asparagine (higher in R), as well as, isoleucine and leucine (lower in R), were shortlisted as potential metabolite biomarkers. ANOVA of these metabolites revealed significant differences across the four patient groups, with a clear trend with time since relapse onset. Multivariable receiver operating characteristics analysis of these four metabolites in discriminating R versus LR ≥ 24 M showed an area under the curve of 0.758, while the area under the curve for serum neurofilament-light chain was 0.575. Within individual patients with paired relapse-remission samples, all four metabolites were significantly different in relapse versus remission, with the direction of change consistent with that observed at group level, while neurofilament-light chain was not discriminatory. The perturbations in the identified metabolites point towards energy deficiency and immune activation in multiple sclerosis relapses, and the measurement of these metabolites, either singly or in combination, are useful as biomarkers to differentiate relapse from remission at both group and individual levels.

X-ray free-electron laser studies reveal correlated motion during isopenicillin N synthase catalysis.

Isopenicillin N synthase (IPNS) catalyzes the unique reaction of l-δ-(α-aminoadipoyl)-l-cysteinyl-d-valine (ACV) with dioxygen giving isopenicillin N (IPN), the precursor of all natural penicillins and cephalosporins. X-ray free-electron laser studies including time-resolved crystallography and emission spectroscopy reveal how reaction of IPNS:Fe(II):ACV with dioxygen to yield an Fe(III) superoxide causes differences in active site volume and unexpected conformational changes that propagate to structurally remote regions. Combined with solution studies, the results reveal the importance of protein dynamics in regulating intermediate conformations during conversion of ACV to IPN. The results have implications for catalysis by multiple IPNS-related oxygenases, including those involved in the human hypoxic response, and highlight the power of serial femtosecond crystallography to provide insight into long-range enzyme dynamics during reactions presently impossible for nonprotein catalysts.

Integrative biochemical, proteomics and metabolomics cerebrospinal fluid biomarkers predict clinical conversion to multiple sclerosis.

Eighty-five percent of multiple sclerosis cases begin with a discrete attack termed clinically isolated syndrome, but 37% of clinically isolated syndrome patients do not experience a relapse within 20 years of onset. Thus, the identification of biomarkers able to differentiate between individuals who are most likely to have a second clinical attack from those who remain in the clinically isolated syndrome stage is essential to apply a personalized medicine approach. We sought to identify biomarkers from biochemical, metabolic and proteomic screens that predict clinically defined conversion from clinically isolated syndrome to multiple sclerosis and generate a multi-omics-based algorithm with higher prognostic accuracy than any currently available test. An integrative multi-variate approach was applied to the analysis of cerebrospinal fluid samples taken from 54 individuals at the point of clinically isolated syndrome with 2-10 years of subsequent follow-up enabling stratification into clinical converters and non-converters. Leukocyte counts were significantly elevated at onset in the clinical converters and predict the occurrence of a second attack with 70% accuracy. Myo-inositol levels were significantly increased in clinical converters while glucose levels were decreased, predicting transition to multiple sclerosis with accuracies of 72% and 63%, respectively. Proteomics analysis identified 89 novel gene products related to conversion. The identified biochemical and protein biomarkers were combined to produce an algorithm with predictive accuracy of 83% for the transition to clinically defined multiple sclerosis, outperforming any individual biomarker in isolation including oligoclonal bands. The identified protein biomarkers are consistent with an exaggerated immune response, perturbed energy metabolism and multiple sclerosis pathology in the clinical converter group. The new biomarkers presented provide novel insight into the molecular pathways promoting disease while the multi-omics algorithm provides a means to more accurately predict whether an individual is likely to convert to clinically defined multiple sclerosis.

Determination of CSF GFAP, CCN5, and vWF Levels Enhances the Diagnostic Accuracy of Clinically Defined MS From Non-MS Patients With CSF Oligoclonal Bands.

Background: Inclusion of cerebrospinal fluid (CSF) oligoclonal IgG bands (OCGB) in the revised McDonald criteria increases the sensitivity of diagnosis when dissemination in time (DIT) cannot be proven. While OCGB negative patients are unlikely to develop clinically definite (CD) MS, OCGB positivity may lead to an erroneous diagnosis in conditions that present similarly, such as neuromyelitis optica spectrum disorders (NMOSD) or neurosarcoidosis. Objective: To identify specific, OCGB-complementary, biomarkers to improve diagnostic accuracy in OCGB positive patients. Methods: We analysed the CSF metabolome and proteome of CDMS (n=41) and confirmed non-MS patients (n=64) comprising a range of CNS conditions routinely encountered in neurology clinics. Results: OCGB discriminated between CDMS and non-MS with high sensitivity (85%), but low specificity (67%), as previously described. Machine learning methods revealed CCN5 levels provide greater accuracy, sensitivity, and specificity than OCGB (79%, +5%; 90%, +5%; and 72%, +5% respectively) while glial fibrillary acidic protein (GFAP) identified CDMS with 100% specificity (+33%). A multiomics approach improved accuracy further to 90% (+16%). Conclusion: The measurement of a few additional CSF biomarkers could be used to complement OCGB and improve the specificity of MS diagnosis when clinical and radiological evidence of DIT is absent.

Impact of Multiple Hydrogen Bonds with Fluoride on Catalysis: Insight from NMR Spectroscopy.

Hydrogen-bonding interactions have been explored in catalysis, enabling complex chemical reactions. Recently, enantioselective nucleophilic fluorination with metal alkali fluoride has been accomplished with BINAM-derived bisurea catalysts, presenting up to four NH hydrogen-bond donors (HBDs) for fluoride. These catalysts bring insoluble CsF and KF into solution, control fluoride nucleophilicity, and provide a chiral microenvironment for enantioselective fluoride delivery to the electrophile. These attributes encouraged a 1H/19F NMR study to gain information on hydrogen-bonding networks with fluoride in solution, as well as how these arrangements impact the efficiency of catalytic nucleophilic fluorination. Herein, NMR experiments enabled the determination of the number and magnitude of HB contacts to fluoride for thirteen bisurea catalysts. These data supplemented by diagnostic coupling constants 1hJNH···F- give insight into how multiple H bonds to fluoride influence reaction performance. In dichloromethane (DCM-d2), nonalkylated BINAM-derived bisurea catalyst engages two of its four NH groups in hydrogen bonding with fluoride, an arrangement that allows effective phase-transfer capability but low control over enantioselectivity for fluoride delivery. The more efficient N-alkylated BINAM-derived bisurea catalysts undergo urea isomerization upon fluoride binding and form dynamically rigid trifurcated hydrogen-bonded fluoride complexes that are structurally similar to their conformation in the solid state. Insight into how the countercation influences fluoride complexation is provided based on NMR data characterizing the species formed in DCM-d2 when reacting a bisurea catalyst with tetra-n-butylammonium fluoride (TBAF) or CsF. Structure-activity analysis reveals that the three hydrogen-bond contacts with fluoride are not equal in terms of their contribution to catalyst efficacy, suggesting that tuning individual electronic environment is a viable approach to control phase-transfer ability and enantioselectivity.

Terminalia bentzoë, a Mascarene Endemic Plant, Inhibits Human Hepatocellular Carcinoma Cells Growth In Vitro via G0/G1 Phase Cell Cycle Arrest.

Tropical forests constitute a prolific sanctuary of unique floral diversity and potential medicinal sources, however, many of them remain unexplored. The scarcity of rigorous scientific data on the surviving Mascarene endemic taxa renders bioprospecting of this untapped resource of utmost importance. Thus, in view of valorizing the native resource, this study has as its objective to investigate the bioactivities of endemic leaf extracts. Herein, seven Mascarene endemic plants leaves were extracted and evaluated for their in vitro antioxidant properties and antiproliferative effects on a panel of cancer cell lines, using methyl thiazolyl diphenyl-tetrazolium bromide (MTT) and clonogenic cell survival assays. Flow cytometry and comet assay were used to investigate the cell cycle and DNA damaging effects, respectively. Bioassay guided-fractionation coupled with liquid chromatography mass spectrometry (MS), gas chromatography-MS, and nuclear magnetic resonance spectroscopic analysis were used to identify the bioactive compounds. Among the seven plants tested, Terminaliabentzoë was comparatively the most potent antioxidant extract, with significantly (p < 0.05) higher cytotoxic activities. T. bentzoë extract further selectively suppressed the growth of human hepatocellular carcinoma cells and significantly halted the cell cycle progression in the G0/G1 phase, decreased the cells' replicative potential and induced significant DNA damage. In total, 10 phenolic compounds, including punicalagin and ellagic acid, were identified and likely contributed to the extract's potent antioxidant and cytotoxic activities. These results established a promising basis for further in-depth investigations into the potential use of T. bentzoë as a supportive therapy in cancer management.

Post-inflammatory behavioural despair in male mice is associated with reduced cortical glutamate-glutamine ratios, and circulating lipid and energy metabolites.

Post-inflammatory behaviours in rodents are widely used to model human depression and to test the efficacy of novel anti-depressants. Mice injected with lipopolysaccharide (LPS) display a depressive-like phenotype twenty-four hours after endotoxin administration. Despite the widespread use of this model, the mechanisms that underlie the persistent behavioural changes after the transient peripheral inflammatory response remain elusive. The study of the metabolome, the collection of all the small molecule metabolites in a sample, combined with multivariate statistical techniques provides a way of studying biochemical pathways influenced by an LPS challenge. Adult male CD-1 mice received an intraperitoneal injection of either LPS (0.83 mg/kg) or saline, and were assessed for depressive-like behaviour 24 h later. In a separate mouse cohort, pro-inflammatory cytokine gene expression and 1H nuclear magnetic resonance (NMR) metabolomics measurements were made in brain tissue and blood. Statistical analyses included Independent Sample t-tests for gene expression data, and supervised multi-variate analysis using orthogonal partial least squares discriminant analysis for metabolomics. Both plasma and brain metabolites in male mice were altered following a single peripheral LPS challenge that led to depressive-like behaviour in the forced swim test. The plasma metabolites altered by LPS are involved in energy metabolism, including lipoproteins, glucose, creatine, and isoleucine. In the brain, glutamate, serine, and N-acetylaspartate (NAA) were reduced after LPS, whereas glutamine was increased. Serine-modulated glutamatergic signalling and changes in bioenergetics may mediate the behavioural phenotype induced by LPS. In light of other data supporting a central imbalance of glutamate-glutamine cycling in depression, our results suggest that aberrant central glutaminergic signalling may underpin the depressive-like behaviours that result from both inflammation and non-immune pathophysiology. Normalising glutaminergic signalling, rather than seeking to increase serotonergic signalling, might prove to be a more coherent approach to the development of new treatments for mood disorder.

A blood-based metabolomics test to distinguish relapsing-remitting and secondary progressive multiple sclerosis: addressing practical considerations for clinical application.

The transition from relapsing-remitting multiple sclerosis (RRMS) to secondary progressive MS (SPMS) represents a huge clinical challenge. We previously demonstrated that serum metabolomics could distinguish RRMS from SPMS with high diagnostic accuracy. As differing sample-handling protocols can affect the blood metabolite profile, it is vital to understand which factors may influence the accuracy of this metabolomics-based test in a clinical setting. Herein, we aim to further validate the high accuracy of this metabolomics test and to determine if this is maintained in a 'real-life' clinical environment. Blood from 31 RRMS and 28 SPMS patients was subjected to different sample-handling protocols representing variations encountered in clinics. The effect of freeze-thaw cycles (0 or 1) and time to erythrocyte removal (30, 120, or 240 min) on the accuracy of the test was investigated. For test development, samples from the optimised protocol (30 min standing time, 0 freeze-thaw) were used, resulting in high diagnostic accuracy (mean ± SD, 91.0 ± 3.0%). This test remained able to discriminate RRMS and SPMS samples that had experienced additional freeze-thaw, and increased standing times of 120 and 240 min with accuracies ranging from 85.5 to 88.0%, because the top discriminatory metabolite biomarkers from the optimised protocol remained discriminatory between RRMS and SPMS despite these sample-handling variations. In conclusion, while strict sample-handling is essential for the development of metabolomics-based blood tests, the results confirmed that the RRMS vs. SPMS test is resistant to sample-handling variations and can distinguish these two MS stages in the clinics.

Reducing Agent-Mediated Nonenzymatic Conversion of 2-Oxoglutarate to Succinate: Implications for Oxygenase Assays.

l-Ascorbate (l-Asc) is often added to assays with isolated FeII - and 2-oxoglutarate (2OG)-dependent oxygenases to enhance activity. l-Asc is proposed to be important in catalysis by some 2OG oxygenases in vivo. We report observations on the nonenzymatic conversion of 2OG to succinate, which is mediated by hydrogen peroxide generated by the reaction of l-Asc and dioxygen. Slow nonenzymatic oxidation of 2OG to succinate occurs with some, but not all, other reducing agents commonly used in 2OG oxygenase assays. We intend these observations will help in the robust assignment of substrates and inhibitors for 2OG oxygenases.

Global aromaticity at the nanoscale.

Aromaticity can be defined by the ability of a molecule to sustain a ring current when placed in a magnetic field. Hückel's rule states that molecular rings with [4n + 2] π-electrons are aromatic, with an induced magnetization that opposes the external field inside the ring, whereas those with 4n π-electrons are antiaromatic, with the opposite magnetization. This rule reliably predicts the behaviour of small molecules, typically with fewer than 22 π-electrons (n = 5). It is not clear whether aromaticity has a size limit, or whether Hückel's rule extends to much larger macrocycles. Here, we present evidence for global aromaticity in porphyrin nanorings with circuits of up to 162 π-electrons (n = 40); aromaticity is controlled by changing the constitution, oxidation state and conformation. Whenever a ring current is observed, its direction is correctly predicted by Hückel's rule. The largest ring currents occur when the porphyrin units have fractional oxidation states.

Studies on the selectivity of proline hydroxylases reveal new substrates including bicycles.

Studies on the substrate selectivity of recombinant ferrous-iron- and 2-oxoglutarate-dependent proline hydroxylases (PHs) reveal that they can catalyse the production of dihydroxylated 5-, 6-, and 7-membered ring products, and can accept bicyclic substrates. Ring-substituted substrate analogues (such hydroxylated and fluorinated prolines) are accepted in some cases. The results highlight the considerable, as yet largely untapped, potential for amino acid hydroxylases and other 2OG oxygenases in biocatalysis.

Monitoring protein-metal binding by 19F NMR - a case study with the New Delhi metallo-ß-lactamase 1.

19F NMR protein observed spectroscopy is evaluated as a method for analysing protein metal binding using the New Delhi metallo-ß-lactamase 1. The results imply 19F NMR is useful for analysis of different metallated protein states and investigations on equilibrium states in the presence of inhibitors. One limitation is that 19F labelling may affect metal ion binding. The sensitive readout of changes in protein behaviour observed by 19F NMR spectra coupled with the broad scope of tolerated conditions (e.g. buffer variations) means 19F NMR should be further investigated for studying metal ion interactions and the inhibition of metallo-enzymes during drug discovery.

NMR waterLOGSY as An Assay in Drug Development Programmes for Detecting Protein-Ligand Interactions-NMR waterLOGSY.

In drug development programmes, multiple assays are needed for the determination of protein-compound interactions and evaluation of potential use in assays with protein-protein interactions. In this protocol we describe the waterLOGSY NMR method for confirming protein-ligand binding events.