A deconstruction-reconstruction strategy for pyrimidine diversification.

Structure-Activity Relationship (SAR) studies are fundamental to drug and agrochemical development, yet only a few synthetic strategies apply to the nitrogen heteroaromatics frequently encountered in small molecule candidates.1-3 Here, we present an alternative approach where we convert pyrimidine-containing compounds various other nitrogen heteroaromatics. Transforming pyrmidines into their corresponding N-arylpyrimidinium salts enables cleavage into a three-carbon iminoenamine building block, used for various heterocycle-forming reactions. This deconstruction-reconstruction sequence diversifies the initial pyrimidine core and enables access to various heterocycles, such as azoles.4 In effect, this approach allows heterocycle formation on complex molecules, resulting in analogs that would be challenging to obtain by other methods. We anticipate this deconstruction-reconstruction strategy will extend to other heterocycle classes.

Late-stage benzenoid-to-troponoid skeletal modification of the cephalotanes exemplified by the total synthesis of harringtonolide.

Skeletal modifications enable elegant and rapid access to various derivatives of a compound that would otherwise be difficult to prepare. They are therefore a powerful tool, especially in the synthesis of natural products or drug discovery, to explore different natural products or to improve the properties of a drug candidate starting from a common intermediate. Inspired by the biosynthesis of the cephalotane natural products, we report here a single-atom insertion into the framework of the benzenoid subfamily, providing access to the troponoid congeners - representing the reverse of the proposed biosynthesis (i.e., a contra-biosynthesis approach). Computational evaluation of our designed transformation prompted us to investigate a Büchner-Curtius-Schlotterbeck reaction of a p-quinol methylether, which ultimately results in the synthesis of harringtonolide in two steps from cephanolide A, which we had previously prepared. Additional computational studies reveal that unconventional selectivity outcomes are driven by the choice of a Lewis acid and the nucleophile, which should inform further developments of these types of reactions.

Bottom-Up Atomistic Descriptions of Top-Down Macroscopic Measurements: Computational Benchmarks for Hammett Electronic Parameters.

The ability to relate substituent electronic effects to chemical reactivity is a cornerstone of physical organic chemistry and Linear Free Energy Relationships. The computation of electronic parameters is increasingly attractive since they can be obtained rapidly for structures and substituents without available experimental data and can be applied beyond aromatic substituents, for example, in studies of transition metal complexes and aliphatic and radical systems. Nevertheless, the description of "top-down" macroscopic observables, such as Hammett parameters using a "bottom-up" computational approach, poses several challenges for the practitioner. We have examined and benchmarked the performance of various computational charge schemes encompassing quantum mechanical methods that partition charge density, methods that fit charge to physical observables, and methods enhanced by semiempirical adjustments alongside NMR values. We study the locations of the atoms used to obtain these descriptors and their correlation with empirical Hammett parameters and rate differences resulting from electronic effects. These seemingly small choices have a much more significant impact than previously imagined, which outweighs the level of theory or basis set used. We observe a wide range of performance across the different computational protocols and observe stark and surprising differences in the ability of computational parameters to capture para- vs meta-electronic effects. In general, σm predictions fare much worse than σp. As a result, the choice of where to compute these descriptors-for the ring carbons or the attached H or other substituent atoms-affects their ability to capture experimental electronic differences. Density-based schemes, such as Hirshfeld charges, are more stable toward unphysical charge perturbations that result from nearby functional groups and outperform all other computational descriptors, including several commonly used basis set based schemes such as Natural Population Analysis. Using attached atoms also improves the statistical correlations. We obtained general linear relationships for the global prediction of experimental Hammett parameters from computed descriptors for use in statistical modeling studies.

The real-time infection hospitalisation and fatality risk across the COVID-19 pandemic in England.

The COVID-19 pandemic led to 231,841 deaths and 940,243 hospitalisations in England, by the end of March 2023. This paper calculates the real-time infection hospitalisation risk (IHR) and infection fatality risk (IFR) using the Office for National Statistics Coronavirus Infection Survey (ONS CIS) and the Real-time Assessment of Community Transmission Survey between November 2020 to March 2023. The IHR and the IFR in England peaked in January 2021 at 3.39% (95% Credible Intervals (CrI): 2.79, 3.97) and 0.97% (95% CrI: 0.62, 1.36), respectively. After this time, there was a rapid decline in the severity from infection, with the lowest estimated IHR of 0.32% (95% CrI: 0.27, 0.39) in December 2022 and IFR of 0.06% (95% CrI: 0.04, 0.08) in April 2022. We found infection severity to vary more markedly between regions early in the pandemic however, the absolute heterogeneity has since reduced. The risk from infection of SARS-CoV-2 has changed substantially throughout the COVID-19 pandemic with a decline of 86.03% (80.86, 89.35) and 89.67% (80.18, 93.93) in the IHR and IFR, respectively, since early 2021. From April 2022 until March 2023, the end of the ONS CIS study, we found fluctuating patterns in the severity of infection with the resumption of more normative mixing, resurgent epidemic waves, patterns of waning immunity, and emerging variants that have shown signs of convergent evolution.

Understanding the infection severity and epidemiological characteristics of mpox in the UK.

In May 2022, individuals infected with the monkeypox virus were detected in the UK without clear travel links to endemic areas. Understanding the clinical characteristics and infection severity of mpox is necessary for effective public health policy. The study period of this paper, from the 1st June 2022 to 30th September 2022, included 3,375 individuals that tested positive for the monkeypox virus. The posterior mean times from infection to hospital admission and length of hospital stay were 14.89 days (95% Credible Intervals (CrI): 13.60, 16.32) and 7.07 days (95% CrI: 6.07, 8.23), respectively. We estimated the modelled Infection Hospitalisation Risk to be 4.13% (95% CrI: 3.04, 5.02), compared to the overall sample Case Hospitalisation Risk (CHR) of 5.10% (95% CrI: 4.38, 5.86). The overall sample CHR was estimated to be 17.86% (95% CrI: 6.06, 33.11) for females and 4.99% (95% CrI: 4.27, 5.75) for males. A notable difference was observed between the CHRs that were estimated for each sex, which may be indicative of increased infection severity in females or a considerably lower infection ascertainment rate. It was estimated that 74.65% (95% CrI: 55.78, 86.85) of infections with the monkeypox virus in the UK were captured over the outbreak.

Predicting Lewis Acidity: Machine Learning the Fluoride Ion Affinity of p-Block-Atom-Based Molecules.

"How strong is this Lewis acid?" is a question researchers often approach by calculating its fluoride ion affinity (FIA) with quantum chemistry. Here, we present FIA49k, an extensive FIA dataset with 48,986 data points calculated at the RI-DSD-BLYP-D3(BJ)/def2-QZVPP//PBEh-3c level of theory, including 13 different p-block atoms as the fluoride accepting site. The FIA49k dataset was used to train FIA-GNN, two message-passing graph neural networks, which predict gas and solution phase FIA values of molecules excluded from training with a mean absolute error of 14 kJ mol-1 (r2=0.93) from the SMILES string of the Lewis acid as the only input. The level of accuracy is notable, given the wide energetic range of 750 kJ mol-1 spanned by FIA49k. The model's value was demonstrated with four case studies, including predictions for molecules extracted from the Cambridge Structural Database and by reproducing results from catalysis research available in the literature. Weaknesses of the model are evaluated and interpreted chemically. FIA-GNN and the FIA49k dataset can be reached via a free web app (www.grebgroup.de/fia-gnn).

Designing solvent systems using self-evolving solubility databases and graph neural networks.

Designing solvent systems is key to achieving the facile synthesis and separation of desired products from chemical processes, so many machine learning models have been developed to predict solubilities. However, breakthroughs are needed to address deficiencies in the model's predictive accuracy and generalizability; this can be addressed by expanding and integrating experimental and computational solubility databases. To maximize predictive accuracy, these two databases should not be trained separately, and they should not be simply combined without reconciling the discrepancies from different magnitudes of errors and uncertainties. Here, we introduce self-evolving solubility databases and graph neural networks developed through semi-supervised self-training approaches. Solubilities from quantum-mechanical calculations are referred to during semi-supervised learning, but they are not directly added to the experimental database. Dataset augmentation is performed from 11 637 experimental solubilities to >900 000 data points in the integrated database, while correcting for the discrepancies between experiment and computation. Our model was successfully applied to study solvent selection in organic reactions and separation processes. The accuracy (mean absolute error around 0.2 kcal mol-1 for the test set) is quantitatively useful in exploring Linear Free Energy Relationships between reaction rates and solvation free energies for 11 organic reactions. Our model also accurately predicted the partition coefficients of lignin-derived monomers and drug-like molecules. While there is room for expanding solubility predictions to transition states, radicals, charged species, and organometallic complexes, this approach will be attractive to predictive chemistry areas where experimental, computational, and other heterogeneous data should be combined.

Identifying employee, workplace and population characteristics associated with COVID-19 outbreaks in the workplace: a population-based study.

OBJECTIVES: To identify risk factors that contribute to outbreaks of COVID-19 in the workplace and quantify their effect on outbreak risk. METHODS: We identified outbreaks of COVID-19 cases in the workplace and investigated the characteristics of the individuals, the workplaces, the areas they work and the mode of commute to work, through data linkages based on Middle Layer Super Output Areas in England between 20 June 2021 and 20 February 2022. We estimated population-level associations between potential risk factors and workplace outbreaks, adjusting for plausible confounders identified using a directed acyclic graph. RESULTS: For most industries, increased physical proximity in the workplace was associated with increased risk of COVID-19 outbreaks, while increased vaccination was associated with reduced risk. Employee demographic risk factors varied across industry, but for the majority of industries, a higher proportion of black/African/Caribbean ethnicities and living in deprived areas, was associated with increased outbreak risk. A higher proportion of employees in the 60-64 age group was associated with reduced outbreak risk. There were significant associations between gender, work commute modes and staff contract type with outbreak risk, but these were highly variable across industries. CONCLUSIONS: This study has used novel national data linkages to identify potential risk factors of workplace COVID-19 outbreaks, including possible protective effects of vaccination and increased physical distance at work. The same methodological approach can be applied to wider occupational and environmental health research.

The MAGIC trial: a pragmatic, multicentre, parallel, noninferiority, randomised trial of melatonin versus midazolam in the premedication of anxious children attending for elective surgery under general anaesthesia.

BACKGROUND: Child anxiety before general anaesthesia and surgery is common. Midazolam is a commonly used premedication to address this. Melatonin is an alternative anxiolytic, however trials evaluating its efficacy in children have delivered conflicting results. METHODS: This multicentre, double-blind randomised trial was performed in 20 UK NHS Trusts. A sample size of 624 was required to declare noninferiority of melatonin. Anxious children, awaiting day case elective surgery under general anaesthesia, were randomly assigned 1:1 to midazolam or melatonin premedication (0.5 mg kg-1, maximum 20 mg) 30 min before transfer to the operating room. The primary outcome was the modified Yale Preoperative Anxiety Scale-Short Form (mYPAS-SF). Secondary outcomes included safety. Results are presented as n (%) and adjusted mean differences with 95% confidence intervals. RESULTS: The trial was stopped prematurely (n=110; 55 per group) because of recruitment futility. Participants had a median age of 7 (6-10) yr, and 57 (52%) were female. Intention-to-treat and per-protocol modified Yale Preoperative Anxiety Scale-Short Form analyses showed adjusted mean differences of 13.1 (3.7-22.4) and 12.9 (3.1-22.6), respectively, in favour of midazolam. The upper 95% confidence interval limits exceeded the predefined margin of 4.3 in both cases, whereas the lower 95% confidence interval excluded zero, indicating that melatonin was inferior to midazolam, with a difference considered to be clinically relevant. No serious adverse events were seen in either arm. CONCLUSION: Melatonin was less effective than midazolam at reducing preoperative anxiety in children, although the early termination of the trial increases the likelihood of bias. CLINICAL TRIAL REGISTRATION: ISRCTN registry: ISRCTN18296119.

Catalytic Effects of Active Site Conformational Change in the Allosteric Activation of Imidazole Glycerol Phosphate Synthase.

Imidazole glycerol phosphate synthase (IGPS) is a class-I glutamine amidotransferase (GAT) that hydrolyzes glutamine. Ammonia is produced and transferred to a second active site, where it reacts with N1-(5'-phosphoribosyl)-formimino-5-aminoimidazole-4-carboxamide ribonucleotide (PrFAR) to form precursors to purine and histidine biosynthesis. Binding of PrFAR over 25 Šaway from the active site increases glutaminase efficiency by ∼4500-fold, primarily altering the glutamine turnover number. IGPS has been the focus of many studies on allosteric communication; however, atomic details for how the glutamine hydrolysis rate increases in the presence of PrFAR are lacking. We present a density functional theory study on 237-atom active site cluster models of IGPS based on crystallized structures representing the inactive and allosterically active conformations and investigate the multistep reaction leading to thioester formation and ammonia production. The proposed mechanism is supported by similar, well-studied enzyme mechanisms, and the corresponding energy profile is consistent with steady-state kinetic studies of PrFAR + IGPS. Additional active site models are constructed to examine the relationship between active site structural change and transition-state stabilization via energy decomposition schemes. The results reveal that the inactive IGPS conformation does not provide an adequately formed oxyanion hole structure and that repositioning of the oxyanion strand relative to the substrate is vital for a catalysis-competent oxyanion hole, with or without the hVal51 dihedral flip. These findings are valuable for future endeavors in modeling the IGPS allosteric mechanism by providing insight into the atomistic changes required for rate enhancement that can inform suitable reaction coordinates for subsequent investigations.

Forecasting influenza hospital admissions within English sub-regions using hierarchical generalised additive models.

BACKGROUND: Seasonal influenza places a substantial burden annually on healthcare services. Policies during the COVID-19 pandemic limited the transmission of seasonal influenza, making the timing and magnitude of a potential resurgence difficult to ascertain and its impact important to forecast. METHODS: We have developed a hierarchical generalised additive model (GAM) for the short-term forecasting of hospital admissions with a positive test for the influenza virus sub-regionally across England. The model incorporates a multi-level structure of spatio-temporal splines, weekly cycles in admissions, and spatial correlation. Using multiple performance metrics including interval score, coverage, bias, and median absolute error, the predictive performance is evaluated for the 2022-2023 seasonal wave. Performance is measured against autoregressive integrated moving average (ARIMA) and Prophet time series models. RESULTS: Across the epidemic phases the hierarchical GAM shows improved performance, at all geographic scales relative to the ARIMA and Prophet models. Temporally, the hierarchical GAM has overall an improved performance at 7 and 14 day time horizons. The performance of the GAM is most sensitive to the flexibility of the smoothing function that measures the national epidemic trend. CONCLUSIONS: This study introduces an approach to short-term forecasting of hospital admissions for the influenza virus using hierarchical, spatial, and temporal components. The methodology was designed for the real time forecasting of epidemics. This modelling framework was used across the 2022-2023 winter for healthcare operational planning by the UK Health Security Agency and the National Health Service in England.

Seasonal influenza causes a burden for hospitals and therefore it is useful to be able to accurately predict how many patients might be admitted with the disease. We attempted to predict influenza admissions up to 14 days in the future by creating a computational model that incorporates how the disease is reported and how it spreads. We evaluated our optimised model on data acquired during the winter of 2022-2023 data in England and compared it with previously developed models. Our model was better at modelling how influenza spreads and predicting future hospital admissions than the models we compared it to. Improving how influenza admissions are forecast can enable hospitals to prepare better for increased admissions, enabling improved treatment and reduced death for all patients in hospital over winter.

Electrochemical Modification of Polypeptides at Selenocysteine.

Mild strategies for the selective modification of peptides and proteins are in demand for applications in therapeutic peptide and protein discovery, and in the study of fundamental biomolecular processes. Herein, we describe the development of an electrochemical selenoetherification (e-SE) platform for the efficient site-selective functionalization of polypeptides. This methodology utilizes the unique reactivity of the 21st amino acid, selenocysteine, to effect formation of valuable bioconjugates through stable selenoether linkages under mild electrochemical conditions. The power of e-SE is highlighted through late-stage C-terminal modification of the FDA-approved cancer drug leuprolide and assembly of a library of anti-HER2 affibody conjugates bearing complex cargoes. Following assembly by e-SE, the utility of functionalized affibodies for in vitro imaging and targeting of HER2 positive breast and lung cancer cell lines is also demonstrated.

Exploring Cuneanes as Potential Benzene Isosteres and Energetic Materials: Scope and Mechanistic Investigations into Regioselective Rearrangements from Cubanes.

Cuneane is a strained hydrocarbon that can be accessed via metal-catalyzed isomerization of cubane. The carbon atoms of cuneane define a polyhedron of the C2v point group with six faces─two triangular, two quadrilateral, and two pentagonal. The rigidity, strain, and unique exit vectors of the cuneane skeleton make it a potential scaffold of interest for the synthesis of functional small molecules and materials. However, the limited previous synthetic efforts toward cuneanes have focused on monosubstituted or redundantly substituted systems such as permethylated, perfluorinated, and bis(hydroxymethylated) cuneanes. Such compounds, particularly rotationally symmetric redundantly substituted cuneanes, have limited potential as building blocks for the synthesis of complex molecules. Reliable, predictable, and selective syntheses of polysubstituted cuneanes bearing more complex substitution patterns would facilitate the study of this ring system in myriad applications. Herein, we report the regioselective, AgI-catalyzed isomerization of asymmetrically 1,4-disubstituted cubanes to cuneanes. In-depth DFT calculations provide a charge-controlled regioselectivity model, and direct dynamics simulations indicate that the nonclassical carbocation invoked is short-lived and dynamic effects augment the charge model.

Fluorochemicals from fluorspar via a phosphate-enabled mechanochemical process that bypasses HF.

All fluorochemicals-including elemental fluorine and nucleophilic, electrophilic, and radical fluorinating reagents-are prepared from hydrogen fluoride (HF). This highly toxic and corrosive gas is produced by the reaction of acid-grade fluorspar (>97% CaF2) with sulfuric acid under harsh conditions. The use of fluorspar to produce fluorochemicals via a process that bypasses HF is highly desirable but remains an unsolved problem because of the prohibitive insolubility of CaF2. Inspired by calcium phosphate biomineralization, we herein disclose a protocol of treating acid-grade fluorspar with dipotassium hydrogen phosphate (K2HPO4) under mechanochemical conditions. The process affords a solid composed of crystalline K3(HPO4)F and K2-xCay(PO3F)a(PO4)b, which is found suitable for forging sulfur-fluorine and carbon-fluorine bonds.

Iridium-Catalyzed Asymmetric Difunctionalization of C-C σ-Bonds Enabled by Ring-Strained Boronate Complexes.

Enantioenriched organoboron intermediates are important building blocks in organic synthesis and drug discovery. Recently, transition metal-catalyzed enantioselective 1,2-metalate rearrangements of alkenylboronates have emerged as an attractive protocol to access these valuable reagents by installing two different carbon fragments across C═C π-bonds. Herein, we report the development of an iridium-catalyzed asymmetric allylation-induced 1,2-metalate rearrangement of bicyclo[1.1.0]butyl (BCB) boronate complexes enabled by strain release, which allows asymmetric difunctionalization of C-C σ-bonds, including dicarbonation and carboboration. This protocol provides a variety of enantioenriched three-dimensional 1,1,3-trisubstituted cyclobutane products bearing a boronic ester that can be readily derivatized. Notably, the reaction gives trans diastereoisomers that result from an anti-addition across the C-C σ-bond, which is in contrast to the syn-additions observed for reactions promoted by PdII-aryl complexes and other electrophiles in our previous works. The diastereoselectivity has been rationalized based on a combination of experimental data and density functional theory calculations, which suggest that the BCB boronate complexes are highly nucleophilic and react via early transition states with low activation barriers.

Regiodivergent Nucleophilic Fluorination under Hydrogen Bonding Catalysis: A Computational and Experimental Study.

The controlled programming of regiochemical outcomes in nucleophilic fluorination reactions with alkali metal fluoride is a problem yet to be solved. Herein, two synergistic approaches exploiting hydrogen bonding catalysis are presented. First, we demonstrate that modulating the charge density of fluoride with a hydrogen-bond donor urea catalyst directly influences the kinetic regioselectivity in the fluorination of dissymmetric aziridinium salts with aryl and ester substituents. Moreover, we report a urea-catalyzed formal dyotropic rearrangement, a thermodynamically controlled regiochemical editing process consisting of C-F bond scission followed by fluoride rebound. These findings offer a route to access enantioenriched fluoroamine regioisomers from a single chloroamine precursor, and more generally, new opportunities in regiodivergent asymmetric (bis)urea-based organocatalysis.

Metal-Free Arylation of Benzothiophenes at C4 by Activation as their Benzothiophene S-Oxides.

Benzothiophenes, activated by oxidation to the corresponding S-oxides, undergo C-H/C-H-type coupling with phenols to give C4 arylation products. While an electron-withdrawing group at C3 of the benzothiophene is important, the process operates without a directing group and a metal catalyst, thus rendering it compatible with sensitive functionalities-e.g. halides and formyl groups. Quantum chemical calculations suggest a formal stepwise mechanism involving heterolytic cleavage of an aryloxysulfur species to give a π-complex of the corresponding benzothiophene and a phenoxonium cation. Subsequent addition of the phenoxonium cation to the C4 position of the benzothiophene is favored over the addition to C3; Fukui functions predict that the major regioisomer is formed at the more electron-rich position between C3 and C4. Varied selective manipulation of the benzothiophene products showcase the synthetic utility of the metal-free arylation process.

Control of stereogenic oxygen in a helically chiral oxonium ion.

The control of tetrahedral carbon stereocentres remains a focus of modern synthetic chemistry and is enabled by their configurational stability. By contrast, trisubstituted nitrogen1, phosphorus2 and sulfur compounds3 undergo pyramidal inversion, a fundamental and well-recognized stereochemical phenomenon that is widely exploited4. However, the stereochemistry of oxonium ions-compounds bearing three substituents on a positively charged oxygen atom-is poorly developed and there are few applications of oxonium ions in synthesis beyond their existence as reactive intermediates5,6. There are no examples of configurationally stable oxonium ions in which the oxygen atom is the sole stereogenic centre, probably owing to the low barrier to oxygen pyramidal inversion7 and the perception that all oxonium ions are highly reactive. Here we describe the design, synthesis and characterization of a helically chiral triaryloxonium ion in which inversion of the oxygen lone pair is prevented through geometric restriction to enable it to function as a determinant of configuration. A combined synthesis and quantum calculation approach delineates design principles that enable configurationally stable and room-temperature isolable salts to be generated. We show that the barrier to inversion is greater than 110 kJ mol-1 and outline processes for resolution. This constitutes, to our knowledge, the only example of a chiral non-racemic and configurationally stable molecule in which the oxygen atom is the sole stereogenic centre.

Catalytic Enantioselective 6π Photocyclization of Acrylanilides.

Controlling absolute stereochemistry in catalytic photochemical reactions is generally challenging owing to high rates of background reactivity. Successful strategies broadly rely on selective excitation of the reaction substrate when associated with a chiral catalyst. Recent studies have demonstrated that chiral Lewis acid complexes can enable selective energy transfer from a photosensitizer to facilitate enantioselective triplet state reactions. Here, we apply this approach to the enantioselective catalysis of a 6π photocyclization through the design of an iridium photosensitizer optimized to undergo energy transfer to a reaction substrate only in the presence of a chiral Lewis acid complex. Among a group of iridium(III) sensitizers, enantioselectivity and yield closely correlate with photocatalyst triplet energy within a narrow window enabled by a modest reduction in substrate triplet energy upon binding a scandium/ligand complex. These results demonstrate that photocatalyst tuning offers a means to suppress background reactivity and improve enantioselectivity in photochemical reactions.