Accessing Rare α-Heterocyclic Aziridines via Brønsted Acid-catalyzed Michael Addition/Annulation: Scope, Limitations, and Mechanism.

We report an approach to the diastereoselective synthesis of 1,2-disubstituted heterocyclic aziridines. A Brønsted acid-catalyzed conjugate addition of anilines to trisubstituted heterocyclic chloroalkenes provides an intermediate 1,2-chloroamine. Diastereocontrol was found to vary significantly with solvent selection, with computational modelling confirming selective, spontaneous fragmentation in the presence of trace acids, proceeding through a pseudo-cyclic, protonated intermediate and transition state. These chloroamines can then be converted to the aziridine by treatment with LiHMDS with high stereochemical fidelity. This solvent-induced stereochemical enrichment thereby enables an efficient route to rare cis-aziridines with high dr. The scope, limitations, and mechanistic origins of selectivity are also presented.

Overview of the Knowledge Management Center for Illuminating the Druggable Genome.

The Knowledge Management Center (KMC) for the Illuminating the Druggable Genome (IDG) project aims to aggregate, update, and articulate protein-centric data knowledge for the entire human proteome, with emphasis on the understudied proteins from the three IDG protein families. KMC collates and analyzes data from over 70 resources to compile the Target Central Resource Database (TCRD), which is the web-based informatics platform (Pharos). These data include experimental, computational, and text-mined information on protein structures, compound interactions, and disease and phenotype associations. Based on this knowledge, proteins are classified into different Target Development Levels (TDLs) for identification of understudied targets. Additional work by the KMC focuses on enriching target knowledge and producing DrugCentral and other data visualization tools for expanding investigation of understudied targets.

Challenges and perspectives for naming lipids in the context of lipidomics.

INTRODUCTION: Lipids are key compounds in the study of metabolism and are increasingly studied in biology projects. It is a very broad family that encompasses many compounds, and the name of the same compound may vary depending on the community where they are studied. OBJECTIVES: In addition, their structures are varied and complex, which complicates their analysis. Indeed, the structural resolution does not always allow a complete level of annotation so the actual compound analysed will vary from study to study and should be clearly stated. For all these reasons the identification and naming of lipids is complicated and very variable from one study to another, it needs to be harmonized. METHODS & RESULTS: In this position paper we will present and discuss the different way to name lipids (with chemoinformatic and semantic identifiers) and their importance to share lipidomic results. CONCLUSION: Homogenising this identification and adopting the same rules is essential to be able to share data within the community and to map data on functional networks.

EMBL's European Bioinformatics Institute (EMBL-EBI) in 2023.

The European Molecular Biology Laboratory's European Bioinformatics Institute (EMBL-EBI) is one of the world's leading sources of public biomolecular data. Based at the Wellcome Genome Campus in Hinxton, UK, EMBL-EBI is one of six sites of the European Molecular Biology Laboratory (EMBL), Europe's only intergovernmental life sciences organisation. This overview summarises the latest developments in the services provided by EMBL-EBI data resources to scientific communities globally. These developments aim to ensure EMBL-EBI resources meet the current and future needs of these scientific communities, accelerating the impact of open biological data for all.

The ChEMBL Database in 2023: a drug discovery platform spanning multiple bioactivity data types and time periods.

ChEMBL (https://www.ebi.ac.uk/chembl/) is a manually curated, high-quality, large-scale, open, FAIR and Global Core Biodata Resource of bioactive molecules with drug-like properties, previously described in the 2012, 2014, 2017 and 2019 Nucleic Acids Research Database Issues. Since its introduction in 2009, ChEMBL's content has changed dramatically in size and diversity of data types. Through incorporation of multiple new datasets from depositors since the 2019 update, ChEMBL now contains slightly more bioactivity data from deposited data vs data extracted from literature. In collaboration with the EUbOPEN consortium, chemical probe data is now regularly deposited into ChEMBL. Release 27 made curated data available for compounds screened for potential anti-SARS-CoV-2 activity from several large-scale drug repurposing screens. In addition, new patent bioactivity data have been added to the latest ChEMBL releases, and various new features have been incorporated, including a Natural Product likeness score, updated flags for Natural Products, a new flag for Chemical Probes, and the initial annotation of the action type for ∼270 000 bioactivity measurements.

Squaramides enhance NLRP3 inflammasome activation by lowering intracellular potassium.

The NLRP3 inflammasome is a component of the inflammatory response to infection and injury, orchestrating the maturation and release of the pro-inflammatory cytokines interleukin-1ß (IL-1ß), IL-18, and triggering pyroptotic cell death. Appropriate levels of NLRP3 activation are needed to avoid excessive tissue damage while ensuring host protection. Here we report a role for symmetrical diarylsquaramides as selective K+ efflux-dependent NLRP3 inflammasome enhancers. Treatment of macrophages with squaramides potentiated IL-1ß secretion and ASC speck formation in response to K+ efflux-dependent NLRP3 inflammasome activators without affecting priming, endosome cargo trafficking, or activation of other inflammasomes. The squaramides lowered intracellular K+ concentration which enabled cells to respond to a below-threshold dose of the inflammasome activator nigericin. Taken together these data further highlight the role of ion flux in inflammasome activation and squaramides as an interesting platform for therapeutic development in conditions where enhanced NLRP3 activity could be beneficial.

MAIP: An Open-Source Tool to Enrich High-Throughput Screening Output and Identify Novel, Druglike Molecules with Antimalarial Activity.

Efforts to tackle malaria must continue for a disease that threatens half of the global population. Parasite resistance to current therapies requires new chemotypes that are able to demonstrate effectiveness and safety. Previously, we developed a machine-learning-based approach to predict compound antimalarial activity, which was trained on the compound collections of several organizations. The resulting prediction platform, MAIP, was made freely available to the scientific community and offers a solution to prioritize molecules of interest in virtual screening and hit-to-lead optimization. Here, we experimentally validate MAIP and demonstrate how the approach was used in combination with a robust compound selection workflow and a recently introduced innovative high-throughput screening (HTS) cascade to select and purchase compounds from a public library for subsequent experimental screening. We observed a 12-fold enrichment compared with a randomly selected set of molecules, and the eight hits we ultimately selected exhibit good potency and absorption, distribution, metabolism, and excretion (ADME) profiles.

Integrative GWAS and co-localisation analysis suggests novel genes associated with age-related multimorbidity.

Advancing age is the greatest risk factor for developing multiple age-related diseases. Therapeutic approaches targeting the underlying pathways of ageing, rather than individual diseases, may be an effective way to treat and prevent age-related morbidity while reducing the burden of polypharmacy. We harness the Open Targets Genetics Portal to perform a systematic analysis of nearly 1,400 genome-wide association studies (GWAS) mapped to 34 age-related diseases and traits, identifying genetic signals that are shared between two or more of these traits. Using locus-to-gene (L2G) mapping, we identify 995 targets with shared genetic links to age-related diseases and traits, which are enriched in mechanisms of ageing and include known ageing and longevity-related genes. Of these 995 genes, 128 are the target of an approved or investigational drug, 526 have experimental evidence of binding pockets or are predicted to be tractable, and 341 have no existing tractability evidence, representing underexplored genes which may reveal novel biological insights and therapeutic opportunities. We present these candidate targets for exploration and prioritisation in a web application.

Genome-wide association analysis and Mendelian randomization proteomics identify drug targets for heart failure.

We conduct a large-scale meta-analysis of heart failure genome-wide association studies (GWAS) consisting of over 90,000 heart failure cases and more than 1 million control individuals of European ancestry to uncover novel genetic determinants for heart failure. Using the GWAS results and blood protein quantitative loci, we perform Mendelian randomization and colocalization analyses on human proteins to provide putative causal evidence for the role of druggable proteins in the genesis of heart failure. We identify 39 genome-wide significant heart failure risk variants, of which 18 are previously unreported. Using a combination of Mendelian randomization proteomics and genetic cis-only colocalization analyses, we identify 10 additional putatively causal genes for heart failure. Findings from GWAS and Mendelian randomization-proteomics identify seven (CAMK2D, PRKD1, PRKD3, MAPK3, TNFSF12, APOC3 and NAE1) proteins as potential targets for interventions to be used in primary prevention of heart failure.

Illuminating the druggable genome through patent bioactivity data.

The patent literature is a potentially valuable source of bioactivity data. In this article we describe a process to prioritise 3.7 million life science relevant patents obtained from the SureChEMBL database (https://www.surechembl.org/), according to how likely they were to contain bioactivity data for potent small molecules on less-studied targets, based on the classification developed by the Illuminating the Druggable Genome (IDG) project. The overall goal was to select a smaller number of patents that could be manually curated and incorporated into the ChEMBL database. Using relatively simple annotation and filtering pipelines, we have been able to identify a substantial number of patents containing quantitative bioactivity data for understudied targets that had not previously been reported in the peer-reviewed medicinal chemistry literature. We quantify the added value of such methods in terms of the numbers of targets that are so identified, and provide some specific illustrative examples. Our work underlines the potential value in searching the patent corpus in addition to the more traditional peer-reviewed literature. The small molecules found in these patents, together with their measured activity against the targets, are now accessible via the ChEMBL database.

Discovery of an inhibitor of DNA-driven inflammation that preferentially targets the AIM2 inflammasome.

Inflammation driven by DNA sensors is now understood to be important to disease pathogenesis. Here, we describe new inhibitors of DNA sensing, primarily of the inflammasome forming sensor AIM2. Biochemistry and molecular modeling has revealed 4-sulfonic calixarenes as potent inhibitors of AIM2 that likely work by binding competitively to the DNA-binding HIN domain. Although less potent, these AIM2 inhibitors also inhibit DNA sensors cGAS and TLR9 demonstrating a broad utility against DNA-driven inflammatory responses. The 4-sulfonic calixarenes inhibited AIM2-dependent post-stroke T cell death, highlighting a proof of concept that the 4-sulfonic calixarenes could be effective at combating post-stroke immunosuppression. By extension, we propose a broad utility against DNA-driven inflammation in disease. Finally, we reveal that the drug suramin, by virtue of its structural similarities, is an inhibitor of DNA-dependent inflammation and propose that suramin could be rapidly repurposed to meet an increasing clinical need.

Applications of single-cell RNA sequencing in drug discovery and development.

Single-cell technologies, particularly single-cell RNA sequencing (scRNA-seq) methods, together with associated computational tools and the growing availability of public data resources, are transforming drug discovery and development. New opportunities are emerging in target identification owing to improved disease understanding through cell subtyping, and highly multiplexed functional genomics screens incorporating scRNA-seq are enhancing target credentialling and prioritization. ScRNA-seq is also aiding the selection of relevant preclinical disease models and providing new insights into drug mechanisms of action. In clinical development, scRNA-seq can inform decision-making via improved biomarker identification for patient stratification and more precise monitoring of drug response and disease progression. Here, we illustrate how scRNA-seq methods are being applied in key steps in drug discovery and development, and discuss ongoing challenges for their implementation in the pharmaceutical industry.

The Pathological Effects of Circulating Hydrophobic Bile Acids in Alzheimer's Disease.

Recent clinical studies have revealed that the serum levels of toxic hydrophobic bile acids (deoxy cholic acid, lithocholic acid [LCA], and glycoursodeoxycholic acid) are significantly higher in patients with Alzheimer's disease (AD) and amnestic mild cognitive impairment (aMCI) when compared to control subjects. The elevated serum bile acids may be the result of hepatic peroxisomal dysfunction. Circulating hydrophobic bile acids are able to disrupt the blood-brain barrier and promote the formation of amyloid-ß plaques through enhancing the oxidation of docosahexaenoic acid. Hydrophobic bile acid may find their ways into the neurons via the apical sodium-dependent bile acid transporter. It has been shown that hydrophobic bile acids impose their pathological effects by activating farnesoid X receptor and suppressing bile acid synthesis in the brain, blocking NMDA receptors, lowering brain oxysterol levels, and interfering with 17ß-estradiol actions such as LCA by binding to E2 receptors (molecular modelling data exclusive to this paper). Hydrophobic bile acids may interfere with the sonic hedgehog signaling through alteration of cell membrane rafts and reducing brain 24(S)-hydroxycholesterol. This article will 1) analyze the pathological roles of circulating hydrophobic bile acids in the brain, 2) propose therapeutic approaches, and 3) conclude that consideration be given to reducing/monitoring toxic bile acid levels in patients with AD or aMCI, prior/in combination with other treatments.

EMBL's European Bioinformatics Institute (EMBL-EBI) in 2022.

The European Molecular Biology Laboratory's European Bioinformatics Institute (EMBL-EBI) is one of the world's leading sources of public biomolecular data. Based at the Wellcome Genome Campus in Hinxton, UK, EMBL-EBI is one of six sites of the European Molecular Biology Laboratory (EMBL), Europe's only intergovernmental life sciences organisation. This overview summarises the status of services that EMBL-EBI data resources provide to scientific communities globally. The scale, openness, rich metadata and extensive curation of EMBL-EBI added-value databases makes them particularly well-suited as training sets for deep learning, machine learning and artificial intelligence applications, a selection of which are described here. The data resources at EMBL-EBI can catalyse such developments because they offer sustainable, high-quality data, collected in some cases over decades and made openly availability to any researcher, globally. Our aim is for EMBL-EBI data resources to keep providing the foundations for tools and research insights that transform fields across the life sciences.

Can ED chest pain patients with intermediate HEART scores be managed as outpatients?

PURPOSE: Current guidelines recommend hospital admission for patients who present to the emergency department (ED) with chest pain and are scored as intermediate risk for adverse outcomes based on the HEART score. While hospital admission for these patients allows for timely investigation and treatment, it is a resource-intensive process. This study examines whether intermediate HEART score patients can be safely managed on an outpatient basis through rapid access chest pain clinics. METHODS: This retrospective observational study included all ED chest pain patients referred to rapid access clinics from January 2018 to April 2020 in Regina and Saskatoon, Saskatchewan. ED physician HEART scores were used in lieu of reviewer HEART scores when available. The primary outcome was the rate of major adverse coronary events (MACE), a composite measure of death, acute coronary syndrome, stroke, coronary angiography, and revascularization at 6 weeks in intermediate-risk patients. Secondary outcomes were the type of MACE, rate of MACE before rapid access clinic appointment and the most predictive component of the HEART score. RESULTS: There were 1989 ED referrals, of which 817 were for intermediate-risk patients. 9.3% of intermediate-risk patients had a MACE at 6 weeks. MACE occurred before rapid access clinic follow-up in 1.1% of intermediate-risk patients, with coronary angiography being the most common MACE. Excluding coronary angiography, the risk of MACE before rapid access clinic follow-up was 0.7% in intermediate-risk patients. Components of the HEART score most predictive of MACE were troponin (OR 11.0, 95% CI: 3.7-32.3) and history (5.3, 95% CI: 2.4-11.8). CONCLUSION: This study demonstrates that rapid access clinics are likely a safe alternative to admission for intermediate-risk chest pain patients and could reduce costly inpatient admissions for chest pain. With angiography excluded, MACE rates were well below the American College of Emergency Physicians cited 2% threshold.

RéSUMé: OBJECTIF: Les directives actuelles recommandent l'admission à l'hôpital des patients qui se présentent aux urgences avec une douleur thoracique et qui sont classés comme présentant un risque intermédiaire d'effets indésirables selon le score HEART. Bien que l'hospitalisation de ces patients permette une investigation et un traitement en temps opportun, il s'agit d'un processus exigeant en ressources. Cette étude examine si les patients ayant un score HEART intermédiaire peuvent être pris en charge en toute sécurité en ambulatoire par des cliniques d'accès rapide aux douleurs thoraciques. MéTHODES: Cette étude observationnelle rétrospective a inclus tous les patients souffrant de douleurs thoraciques aux urgences orientés vers des cliniques d'accès rapide de janvier 2018 à avril 2020 à Regina et Saskatoon, en Saskatchewan. Les scores HEART des médecins des urgences ont été utilisés à la place des scores HEART des examinateurs lorsqu'ils étaient disponibles. Le principal résultat était le taux d'événements coronariens indésirables majeurs (MACE), une mesure composite du décès, du syndrome coronarien aigu, de l'accident vasculaire cérébral, de l'angiographie coronaire et de la revascularisation à 6 semaines chez les patients à risque intermédiaire. Les résultats secondaires étaient le type de MACE, le taux de MACE avant un rendez-vous à la clinique d'accès rapide et la composante la plus prédictive du score HEART. RéSULTATS: Il y a eu 1989 orientations vers les urgences, dont 817 pour des patients à risque intermédiaire. 9,3 % des patients à risque intermédiaire ont subi un MACE à 6 semaines. Un MACE est survenu avant le suivi clinique d'accès rapide chez 1,1 % des patients à risque intermédiaire, la coronarographie étant le MACE le plus fréquent. À l'exclusion de l'angiographie coronarienne, le risque de MACE avant le suivi clinique d'accès rapide était de 0,7 % chez les patients à risque intermédiaire. Les composants du score HEART les plus prédictifs de MACE étaient la troponine (OR 11,0, IC 95 % : 3,7-32,3) et les antécédents (5,3, IC 95 % : 2,4-11,8). CONCLUSION: Cette étude démontre que les cliniques d'accès rapide sont probablement une alternative sûre à l'admission pour les patients souffrant de douleurs thoraciques à risque intermédiaire et pourraient réduire les admissions coûteuses de patients hospitalisés pour des douleurs thoraciques. En excluant l'angiographie, les taux de MACE étaient bien inférieurs au seuil de 2 % cité par l'American College of Emergency Physicians.

CACHE (Critical Assessment of Computational Hit-finding Experiments): A public-private partnership benchmarking initiative to enable the development of computational methods for hit-finding.

One aspirational goal of computational chemistry is to predict potent and drug-like binders for any protein, such that only those that bind are synthesized. In this Roadmap, we describe the launch of Critical Assessment of Computational Hit-finding Experiments (CACHE), a public benchmarking project to compare and improve small molecule hit-finding algorithms through cycles of prediction and experimental testing. Participants will predict small molecule binders for new and biologically relevant protein targets representing different prediction scenarios. Predicted compounds will be tested rigorously in an experimental hub, and all predicted binders as well as all experimental screening data, including the chemical structures of experimentally tested compounds, will be made publicly available, and not subject to any intellectual property restrictions. The ability of a range of computational approaches to find novel binders will be evaluated, compared, and openly published. CACHE will launch 3 new benchmarking exercises every year. The outcomes will be better prediction methods, new small molecule binders for target proteins of importance for fundamental biology or drug discovery, and a major technological step towards achieving the goal of Target 2035, a global initiative to identify pharmacological probes for all human proteins.

In Situ Studies of Arylboronic Acids/Esters and R3SiCF3 Reagents: Kinetics, Speciation, and Dysfunction at the Carbanion-Ate Interface.

Reagent instability reduces the efficiency of chemical processes, and while much effort is devoted to reaction optimization, less attention is paid to the mechanistic causes of reagent decomposition. Indeed, the response is often to simply use an excess of the reagent. Two reaction classes with ubiquitous examples of this are the Suzuki-Miyaura cross-coupling of boronic acids/esters and the transfer of CF3 or CF2 from the Ruppert-Prakash reagent, TMSCF3. This Account describes some of the overarching features of our mechanistic investigations into their decomposition. In the first section we summarize how specific examples of (hetero)arylboronic acids can decompose via aqueous protodeboronation processes: Ar-B(OH)2 + H2O → ArH + B(OH)3. Key to the analysis was the development of a kinetic model in which pH controls boron speciation and heterocycle protonation states. This method revealed six different protodeboronation pathways, including self-catalysis when the pH is close to the pKa of the boronic acid, and protodeboronation via a transient aryl anionoid pathway for highly electron-deficient arenes. The degree of "protection" of boronic acids by diol-esterification is shown to be very dependent on the diol identity, with six-membered ring esters resulting in faster protodeboronation than the parent boronic acid. In the second section of the Account we describe 19F NMR spectroscopic analysis of the kinetics of the reaction of TMSCF3 with ketones, fluoroarenes, and alkenes. Processes initiated by substoichiometric "TBAT" ([Ph3SiF2][Bu4N]) involve anionic chain reactions in which low concentrations of [CF3]- are rapidly and reversibly liberated from a siliconate reservoir, [TMS(CF3)2][Bu4N]. Increased TMSCF3 concentrations reduce the [CF3]- concentration and thus inhibit the rates of CF3 transfer. Computation and kinetics reveal that the TMSCF3 intermolecularly abstracts fluoride from [CF3]- to generate the CF2, in what would otherwise be an endergonic α-fluoride elimination. Starting from [CF3]- and CF2, a cascade involving perfluoroalkene homologation results in the generation of a hindered perfluorocarbanion, [C11F23]-, and inhibition. The generation of CF2 from TMSCF3 is much more efficiently mediated by NaI, and in contrast to TBAT, the process undergoes autoacceleration. The process involves NaI-mediated α-fluoride elimination from [CF3][Na] to generate CF2 and a [NaI·NaF] chain carrier. Chain-branching, by [(CF2)3I][Na] generated in situ (CF2 + TFE + NaI), causes autoacceleration. Alkenes that efficiently capture CF2 attenuate the chain-branching, suppress autoacceleration, and lead to less rapid difluorocyclopropanation. The Account also highlights how a collaborative approach to experiment and computation enables mechanistic insight for control of processes.

Data-Driven Derivation of Molecular Substructures That Enhance Drug Activity in Gram-Negative Bacteria.

The complex cell envelope of Gram-negative bacteria creates a formidable barrier to antibiotic influx. Reduced drug uptake impedes drug development and contributes to a wide range of drug-resistant bacterial infections, including those caused by extremely resistant species prioritized by the World Health Organization. To develop new and efficient treatments, a better understanding of the molecular features governing Gram-negative permeability is essential. Here, we present a data-driven approach, using matched molecular pair analysis and machine learning on minimal inhibitory concentration data from Gram-positive and Gram-negative bacteria to uncover chemical features that influence Gram-negative bioactivity. We find recurring chemical moieties, of a wider range than previously known, that consistently improve activity and suggest that this insight can be used to optimize compounds for increased Gram-negative uptake. Our findings may help to expand the chemical space of broad-spectrum antibiotics and aid the search for new antibiotic compound classes.