tracerDB: a crowdsourced fluorescent tracer database for target engagement analysis.

Investigating ligand-protein complexes is essential in the areas of chemical biology and drug discovery. However, detailed information on key reagents such as fluorescent tracers and associated data for the development of widely used bioluminescence resonance energy transfer (BRET) assays including NanoBRET, time-resolved Förster resonance energy transfer (TR-FRET) and fluorescence polarization (FP) assays are not easily accessible to the research community. We created tracerDB, a curated database of validated tracers. This resource provides an open access knowledge base and a unified system for tracer and assay validation. The database is freely available at https://www.tracerdb.org/ .

A data science roadmap for open science organizations engaged in early-stage drug discovery.

The Structural Genomics Consortium is an international open science research organization with a focus on accelerating early-stage drug discovery, namely hit discovery and optimization. We, as many others, believe that artificial intelligence (AI) is poised to be a main accelerator in the field. The question is then how to best benefit from recent advances in AI and how to generate, format and disseminate data to enable future breakthroughs in AI-guided drug discovery. We present here the recommendations of a working group composed of experts from both the public and private sectors. Robust data management requires precise ontologies and standardized vocabulary while a centralized database architecture across laboratories facilitates data integration into high-value datasets. Lab automation and opening electronic lab notebooks to data mining push the boundaries of data sharing and data modeling. Important considerations for building robust machine-learning models include transparent and reproducible data processing, choosing the most relevant data representation, defining the right training and test sets, and estimating prediction uncertainty. Beyond data-sharing, cloud-based computing can be harnessed to build and disseminate machine-learning models. Important vectors of acceleration for hit and chemical probe discovery will be (1) the real-time integration of experimental data generation and modeling workflows within design-make-test-analyze (DMTA) cycles openly, and at scale and (2) the adoption of a mindset where data scientists and experimentalists work as a unified team, and where data science is incorporated into the experimental design.

Chemogenomics for NR1 nuclear hormone receptors.

Nuclear receptors (NRs) regulate transcription in response to ligand binding and NR modulation allows pharmacological control of gene expression. Although some NRs are relevant as drug targets, the NR1 family, which comprises 19 NRs binding to hormones, vitamins, and lipid metabolites, has only been partially explored from a translational perspective. To enable systematic target identification and validation for this protein family in phenotypic settings, we present an NR1 chemogenomic (CG) compound set optimized for complementary activity/selectivity profiles and chemical diversity. Based on broad profiling of candidates for specificity, toxicity, and off-target liabilities, sixty-nine comprehensively annotated NR1 agonists, antagonists and inverse agonists covering all members of the NR1 family and meeting potency and selectivity standards are included in the final NR1 CG set. Proof-of-concept application of this set reveals effects of NR1 members in autophagy, neuroinflammation and cancer cell death, and confirms the suitability of the set for target identification and validation.

A national surveillance system for continuous monitoring of blood transfusion safety: German haemovigilance data.

BACKGROUND AND OBJECTIVES: Haemovigilance (HV) systems aim to improve transfusion outcomes in patients and donor safety. An important question for blood regulators is how to ensure an effective HV system. MATERIALS AND METHODS: We retrospectively analysed the HV reports submitted to Paul-Ehrlich-Institut over the last two decades. RESULTS: Between 2011 and 2020, 50.86 million units of blood components were used, and 8931 suspected serious donor and recipient adverse reactions (SARs), 874 serious adverse events (SAEs) and 12,073 donor look-backs were reported. Following implementation of specific risk-minimization measures (RMMs) between 2000 and 2010, SAR reporting rates decreased for transfusion-transmitted viral infections (TTVIs), transfusion-related acute lung injury (TRALI) and transfusion-transmitted bacterial infections (TTBIs), while increasing for other serious adverse transfusion reactions. Within this decade, the overall blood component use decreased. CONCLUSION: Long-term data collection forms the basis to establish trends and changes in reporting and to evaluate the effect of RMM. Standardized criteria for reaction types, seriousness and imputability assessments and availability of a denominator are important elements. Central data collection and independent assessment allow for monitoring HV data in a nationwide context over time. Stakeholder involvement and transparent feedback on the benefit of RMM will help to achieve the objectives of HV.

A C-Degron Structure-Based Approach for the Development of Ligands Targeting the E3 Ligase TRIM7.

TRIM7 is a ubiquitin E3 ligase with key regulatory functions, mediating viral infection, tumor biology, innate immunity, and cellular processes, such as autophagy and ferroptosis. It contains a PRYSPRY domain that specifically recognizes degron sequences containing C-terminal glutamine. Ligands that bind to the TRIM7 PRYSPRY domain may have applications in the treatment of viral infections, as modulators of inflammation, and in the design of a new class of PROTACs (PROteolysis TArgeting Chimeras) that mediate the selective degradation of therapeutically relevant proteins (POIs). Here, we developed an assay toolbox for the comprehensive evaluation of TRIM7 ligands. Using TRIM7 degron sequences together with a structure-based design, we developed the first series of peptidomimetic ligands with low micromolar affinity. The terminal carboxylate moiety was required for ligand activity but prevented cell penetration. A prodrug strategy using an ethyl ester resulted in enhanced permeability, which was evaluated using confocal imaging.

Luciferase- and HaloTag-based reporter assays to measure small-molecule-induced degradation pathway in living cells.

The rational development of small-molecule degraders (e.g., proteolysis targeting chimeras) remains a challenge as the rate-limiting steps that determine degrader efficiency are largely unknown. Standard methods in the field of targeted protein degradation mostly rely on classical, low-throughput endpoint assays such as western blots or quantitative proteomics. Here we applied NanoLuciferase- and HaloTag-based screening technologies to determine the kinetics and stability of small-molecule-induced ternary complex formation between a protein of interest and a selected E3 ligase. A collection of live-cell assays were designed to probe the most critical steps of the degradation process while minimizing the number of required expression constructs, making the proposed assay pipeline flexible and adaptable to the requirements of the users. This approach evaluates the underlying mechanism of selective target degraders and reveals the exact characteristics of the developed degrader molecules in living cells. The protocol allows scientists trained in basic cell culture and molecular biology to carry out small-molecule proximity-inducer screening via tracking of the ternary complex formation within 2 weeks of establishment, while degrader screening using the HiBiT system requires a CRISPR-Cas9 engineered cell line whose generation can take up to 3 months. After cell-line generation, degrader screening and validation can be carried out in high-throughput manner within days.

Back-pocket optimization of 2-aminopyrimidine-based macrocycles leads to potent dual EPHA2/GAK kinase inhibitors with antiviral activity.

Macrocyclization of acyclic compounds is a powerful strategy for improving inhibitor potency and selectivity. Here, we developed a 2-aminopyrimidine-based macrocyclic dual EPHA2/GAK kinase inhibitor as a chemical tool to study the role of these two kinases in viral entry and assembly. Starting with a promiscuous macrocyclic inhibitor, 6, we performed a structure-guided activity relationship and selectivity study using a panel of over 100 kinases. The crystal structure of EPHA2 in complex with the developed macrocycle 23 provided a basis for further optimization by specifically targeting the back pocket, resulting in compound 55 as a potent dual EPHA2/GAK inhibitor. Subsequent front-pocket derivatization resulted in an interesting in cellulo selectivity profile, favoring EPHA4 over the other ephrin receptor kinase family members. The dual EPHA2/GAK inhibitor 55 prevented dengue virus infection of Huh7 liver cells, mainly via its EPHA2 activity, and is therefore a promising candidate for further optimization of its activity against dengue virus.

Discovery of a Small Molecule Activator of Slack (Kcnt1) Potassium Channels That Significantly Reduces Scratching in Mouse Models of Histamine-Independent and Chronic Itch.

Various disorders are accompanied by histamine-independent itching, which is often resistant to the currently available therapies. Here, it is reported that the pharmacological activation of Slack (Kcnt1, KNa1.1), a potassium channel highly expressed in itch-sensitive sensory neurons, has therapeutic potential for the treatment of itching. Based on the Slack-activating antipsychotic drug, loxapine, a series of new derivatives with improved pharmacodynamic and pharmacokinetic profiles is designed that enables to validate Slack as a pharmacological target in vivo. One of these new Slack activators, compound 6, exhibits negligible dopamine D2 and D3 receptor binding, unlike loxapine. Notably, compound 6 displays potent on-target antipruritic activity in multiple mouse models of acute histamine-independent and chronic itch without motor side effects. These properties make compound 6 a lead molecule for the development of new antipruritic therapies targeting Slack.

Development of Selective Pyrido[2,3-d]pyrimidin-7(8H)-one-Based Mammalian STE20-Like (MST3/4) Kinase Inhibitors.

Mammalian STE20-like (MST) kinases 1-4 play key roles in regulating the Hippo and autophagy pathways, and their dysregulation has been implicated in cancer development. In contrast to the well-studied MST1/2, the roles of MST3/4 are less clear, in part due to the lack of potent and selective inhibitors. Here, we re-evaluated literature compounds, and used structure-guided design to optimize the p21-activated kinase (PAK) inhibitor G-5555 (8) to selectively target MST3/4. These efforts resulted in the development of MR24 (24) and MR30 (27) with good kinome-wide selectivity and high cellular potency. The distinct cellular functions of closely related MST kinases can now be elucidated with subfamily-selective chemical tool compounds using a combination of the MST1/2 inhibitor PF-06447475 (2) and the two MST3/4 inhibitors developed. We found that MST3/4-selective inhibition caused a cell-cycle arrest in the G1 phase, whereas MST1/2 inhibition resulted in accumulation of cells in the G2/M phase.

Synthesis of Pyrazole-Based Macrocycles Leads to a Highly Selective Inhibitor for MST3.

MST1, MST2, MST3, MST4, and YSK1 are conserved members of the mammalian sterile 20-like serine/threonine (MST) family that regulate cellular functions such as proliferation and migration. The MST3 isozyme plays a role in regulating cell growth and apoptosis, and its dysregulation has been linked to high-grade tumors. To date, there are no isoform-selective inhibitors that could be used for validating the role of MST3 in tumorigenesis. We designed a series of 3-aminopyrazole-based macrocycles based on the structure of a promiscuous inhibitor. By varying the moieties targeting the solvent-exposed region and optimizing the linker, macrocycle JA310 (21c) was synthesized. JA310 exhibited high cellular potency for MST3 (EC50 = 106 nM) and excellent kinome-wide selectivity. The crystal structure of the MST3-JA310 complex provided intriguing insights into the binding mode, which is associated with large-scale structural rearrangements. In summary, JA310 demonstrates the utility of macrocyclization for the design of highly selective inhibitors and presents the first chemical probe for MST3.

Thiocillin contributes to the ecological fitness of Bacillus cereus ATCC 14579 during interspecies interactions with Myxococcus xanthus.

The soil-dwelling delta-proteobacterium Myxococcus xanthus is a model organism to study predation and competition. M. xanthus preys on a broad range of bacteria mediated by lytic enzymes, exopolysaccharides, Type-IV pilus-based motility, and specialized metabolites. Competition between M. xanthus and prey bacterial strains with various specialized metabolite profiles indicates a range of fitness, suggesting that specialized metabolites contribute to prey survival. To expand our understanding of how specialized metabolites affect predator-prey dynamics, we assessed interspecies interactions between M. xanthus and two strains of Bacillus cereus. While strain ATCC 14579 resisted predation, strain T was found to be highly sensitive to M. xanthus predation. The interaction between B. cereus ATCC 14579 and M. xanthus appears to be competitive, resulting in population loss for both predator and prey. Genome analysis revealed that ATCC 14579 belongs to a clade that possesses the biosynthetic gene cluster for production of thiocillins, whereas B. cereus strain T lacks those genes. Further, purified thiocillin protects B. cereus strains unable to produce this specialized metabolite, strengthening the finding that thiocillin protects against predation and contributes to the ecological fitness of B. cereus ATCC 14579. Lastly, strains that produce thiocillin appear to confer some level of protection to their own antibiotic by encoding an additional copy of the L11 ribosomal protein, a known target for thiopeptides. This work highlights the importance of specialized metabolites affecting predator-prey dynamics in soil microenvironments.

Staphylococcus aureus adapts to the immunometabolite itaconic acid by inducing acid and oxidative stress responses including S-bacillithiolations and S-itaconations.

Staphylococcus aureus is a major pathogen, which has to defend against reactive oxygen and electrophilic species encountered during infections. Activated macrophages produce the immunometabolite itaconate as potent electrophile and antimicrobial upon pathogen infection. In this work, we used transcriptomics, metabolomics and shotgun redox proteomics to investigate the specific stress responses, metabolic changes and redox modifications caused by sublethal concentrations of itaconic acid in S. aureus. In the RNA-seq transcriptome, itaconic acid caused the induction of the GlnR, KdpDE, CidR, SigB, GraRS, PerR, CtsR and HrcA regulons and the urease-encoding operon, revealing an acid and oxidative stress response and impaired proteostasis. Neutralization using external urea as ammonium source improved the growth and decreased the expression of the glutamine synthetase-controlling GlnR regulon, indicating that S. aureus experienced ammonium starvation upon itaconic acid stress. In the extracellular metabolome, the amounts of acetate and formate were decreased, while secretion of pyruvate and the neutral product acetoin were strongly enhanced to avoid intracellular acidification. Exposure to itaconic acid affected the amino acid uptake and metabolism as revealed by the strong intracellular accumulation of lysine, threonine, histidine, aspartate, alanine, valine, leucine, isoleucine, cysteine and methionine. In the proteome, itaconic acid caused widespread S-bacillithiolation and S-itaconation of redox-sensitive antioxidant and metabolic enzymes, ribosomal proteins and translation factors in S. aureus, supporting its oxidative and electrophilic mode of action in S. aureus. In phenotype analyses, the catalase KatA, the low molecular weight thiol bacillithiol and the urease provided protection against itaconic acid-induced oxidative and acid stress in S. aureus. Altogether, our results revealed that under physiological infection conditions, such as in the acidic phagolysome, itaconic acid is a highly effective antimicrobial against multi-resistant S. aureus isolates, which acts as weak acid causing an acid, oxidative and electrophilic stress response, leading to S-bacillithiolation and itaconation.

A machine learning and live-cell imaging tool kit uncovers small molecules induced phospholipidosis.

Drug-induced phospholipidosis (DIPL), characterized by excessive accumulation of phospholipids in lysosomes, can lead to clinical adverse effects. It may also alter phenotypic responses in functional studies using chemical probes. Therefore, robust methods are needed to predict and quantify phospholipidosis (PL) early in drug discovery and in chemical probe characterization. Here, we present a versatile high-content live-cell imaging approach, which was used to evaluate a chemogenomic and a lysosomal modulation library. We trained and evaluated several machine learning models using the most comprehensive set of publicly available compounds and interpreted the best model using SHapley Additive exPlanations (SHAP). Analysis of high-quality chemical probes extracted from the Chemical Probes Portal using our algorithm revealed that closely related molecules, such as chemical probes and their matched negative controls can differ in their ability to induce PL, highlighting the importance of identifying PL for robust target validation in chemical biology.

Chemical proteomics reveals the target landscape of 1,000 kinase inhibitors.

Medicinal chemistry has discovered thousands of potent protein and lipid kinase inhibitors. These may be developed into therapeutic drugs or chemical probes to study kinase biology. Because of polypharmacology, a large part of the human kinome currently lacks selective chemical probes. To discover such probes, we profiled 1,183 compounds from drug discovery projects in lysates of cancer cell lines using Kinobeads. The resulting 500,000 compound-target interactions are available in ProteomicsDB and we exemplify how this molecular resource may be used. For instance, the data revealed several hundred reasonably selective compounds for 72 kinases. Cellular assays validated GSK986310C as a candidate SYK (spleen tyrosine kinase) probe and X-ray crystallography uncovered the structural basis for the observed selectivity of the CK2 inhibitor GW869516X. Compounds targeting PKN3 were discovered and phosphoproteomics identified substrates that indicate target engagement in cells. We anticipate that this molecular resource will aid research in drug discovery and chemical biology.

Wnt/ß-catenin and NFκB signaling synergize to trigger growth factor-free regeneration of adult primary human hepatocytes.

BACKGROUND AND AIMS: The liver has a remarkable capacity to regenerate, which is sustained by the ability of hepatocytes to act as facultative stem cells that, while normally quiescent, re-enter the cell cycle after injury. Growth factor signaling is indispensable in rodents, whereas Wnt/ß-catenin is not required for effective tissue repair. However, the molecular networks that control human liver regeneration remain unclear. METHODS: Organotypic 3D spheroid cultures of primary human or murine hepatocytes were used to identify the signaling network underlying cell cycle re-entry. Furthermore, we performed chemogenomic screening of a library enriched for epigenetic regulators and modulators of immune function to determine the importance of epigenomic control for human hepatocyte regeneration. RESULTS: Our results showed that, unlike in rodents, activation of Wnt/ß-catenin signaling is the major mitogenic cue for adult primary human hepatocytes. Furthermore, we identified TGFß inhibition and inflammatory signaling through NF-κB as essential steps for the quiescent-to-regenerative switch that allows Wnt/ß-catenin-induced proliferation of human cells. In contrast, growth factors, but not Wnt/ß-catenin signaling, triggered hyperplasia in murine hepatocytes. High-throughput screening in a human model confirmed the relevance of NFκB and revealed the critical roles of polycomb repressive complex 2, as well as of the bromodomain families I, II, and IV. CONCLUSIONS: This study revealed a network of NFκB, TGFß, and Wnt/ß-catenin that controls human hepatocyte regeneration in the absence of exogenous growth factors, identified novel regulators of hepatocyte proliferation, and highlighted the potential of organotypic culture systems for chemogenomic interrogation of complex physiological processes.

Structural Basis for Highly Selective Class II Alpha Phosphoinositide-3-Kinase Inhibition.

Class II phosphoinositide-3-kinases (PI3Ks) play central roles in cell signaling, division, migration, and survival. Despite evidence that all PI3K class II isoforms serve unique cellular functions, the lack of isoform-selective inhibitors severely hampers the systematic investigation of their potential relevance as pharmacological targets. Here, we report the structural evaluation and molecular determinants for selective PI3K-C2α inhibition by a structure-activity relationship study based on a pteridinone scaffold, leading to the discovery of selective PI3K-C2α inhibitors called PITCOINs. Cocrystal structures and docking experiments supported the rationalization of the structural determinants essential for inhibitor activity and high selectivity. Profiling of PITCOINs in a panel of more than 118 diverse kinases showed no off-target kinase inhibition. Notably, by addressing a selectivity pocket, PITCOIN4 showed nanomolar inhibition of PI3K-C2α and >100-fold selectivity in a general kinase panel. Our study paves the way for the development of novel therapies for diseases related to PI3K-C2α function.

The pH-dependent lactose metabolism of Lactobacillus delbrueckii subsp. bulgaricus: An integrative view through a mechanistic computational model.

The fermentation process of milk to yoghurt using Lactobacillus delbrueckii subsp. bulgaricus in co-culture with Streptococcus thermophilus is hallmarked by the breakdown of lactose to organic acids such as lactate. This leads to a substantial decrease in pH - both in the medium, as well as cytosolic. The latter impairs metabolic activities due to the pH-dependence of enzymes, which compromises microbial growth. To quantitatively elucidate the impact of the acidification on metabolism of L. bulgaricus in an integrated way, we have developed a proton-dependent computational model of lactose metabolism and casein degradation based on experimental data. The model accounts for the influence of pH on enzyme activities as well as cellular growth and proliferation of the bacterial population. We used a machine learning approach to quantify the cell volume throughout fermentation. Simulation results show a decrease in metabolic flux with acidification of the cytosol. Additionally, the validated model predicts a similar metabolic behaviour within a wide range of non-limiting substrate concentrations. This computational model provides a deeper understanding of the intricate relationships between metabolic activity and acidification and paves the way for further optimization of yoghurt production under industrial settings.