Target identification of usnic acid in bacterial and human cells.

Usnic acid is a natural product with versatile biological activities against various organisms. Here, we utilise a chemical proteomic strategy to gain insights into its target scope in bacterial and human cells. First, we excluded DNA binding as a major reason for its antibacterial activity, and second, we commenced with target profiling, which unravelled several metal cofactor-dependent enzymes in both species indicating a polypharmacological mode of action. Interestingly, our synthetic studies revealed a selectivity switch at usnic acid, which maintains antibacterial activity but lacks strong cytotoxic effects.

Synergizing Chemical Structures and Bioassay Descriptions for Enhanced Molecular Property Prediction in Drug Discovery.

The precise prediction of molecular properties can greatly accelerate the development of new drugs. However, in silico molecular property prediction approaches have been limited so far to assays for which large amounts of data are available. In this study, we develop a new computational approach leveraging both the textual description of the assay of interest and the chemical structure of target compounds. By combining these two sources of information via self-supervised learning, our tool can provide accurate predictions for assays where no measurements are available. Remarkably, our approach achieves state-of-the-art performance on the FS-Mol benchmark for zero-shot prediction, outperforming a wide variety of deep learning approaches. Additionally, we demonstrate how our tool can be used for tailoring screening libraries for the assay of interest, showing promising performance in a retrospective case study on a high-throughput screening campaign. By accelerating the early identification of active molecules in drug discovery and development, this method has the potential to streamline the identification of novel therapeutics.

Thermal Proteome Profiling Reveals Insight to Antiproliferative and Pro-Apoptotic Effects of Lagunamide A in the Modulation of DNA Damage Repair.

Lagunamide A is a biologically active natural product with a yet unidentified molecular mode of action. Cellular studies revealed that lagunamide A is a potent inhibitor of cancer cell proliferation, promotes apoptosis and causes mitochondrial dysfunction. To decipher the cellular mechanism responsible for these effects, we utilized thermal protein profiling (TPP) and identified EYA3 as a stabilized protein in cells upon lagunamide A treatment. EYA3, involved in the DNA damage repair process, was functionally investigated via siRNA based knockdown studies and corresponding effects of lagunamide A on DNA repair were confirmed. Furthermore, we showed that lagunamide A sensitized tumor cells to treatment with the drug doxorubicin highlighting a putative therapeutic strategy.

Neocarzilin Inhibits Cancer Cell Proliferation via BST-2 Degradation, Resulting in Lipid Raft-Trapped EGFR.

Neocarzilin (NCA) is a natural product exhibiting potent antimigratory as well as antiproliferative effects. While vesicle amine transport protein 1 (VAT-1) was previously shown to inhibit migration upon NCA binding, the molecular mechanisms responsible for impaired proliferation remained elusive. We here introduce a chemical probe closely resembling the structural and stereochemical features of NCA and unravel bone marrow stromal antigen 2 (BST-2) as one of the targets responsible for the antiproliferative effect of NCA in cancer cells. The antiproliferative mechanism of NCA was confirmed in corresponding BST-2 knockout (KO) HeLa cells, which were less sensitive to compound treatment. Vice versa, reconstitution of BST-2 in the KO cells again reduced proliferation upon NCA addition, comparable to that of wild-type (wt) HeLa cells. Whole proteome mass spectrometric (MS) analysis of NCA-treated wt and KO cancer cells revealed regulated pathways and showed reduced levels of BST-2 upon NCA treatment. In-depth analysis of BST-2 levels in response to proteasome and lysosome inhibitors unraveled a lysosomal degradation path upon NCA treatment. As BST-2 mediates the release of epidermal growth factor receptor (EGFR) from lipid rafts to turn on proliferation signaling pathways, reduced BST-2 levels led to attenuated phosphorylation of STAT3. Furthermore, fluorescence microscopy confirmed increased colocalization of EGFR and lipid rafts in the presence of NCA. Overall, NCA represents a versatile anticancer natural product with a unique dual mode of action and unconventional inhibition of proliferation via BST-2 degradation.

Bacillamide D produced by Bacillus cereus from the mouse intestinal bacterial collection (miBC) is a potent cytotoxin in vitro.

The gut microbiota influences human health and the development of chronic diseases. However, our understanding of potentially protective or harmful microbe-host interactions at the molecular level is still in its infancy. To gain further insights into the hidden gut metabolome and its impact, we identified a cryptic non-ribosomal peptide BGC in the genome of Bacillus cereus DSM 28590 from the mouse intestine ( www.dsmz.de/miBC ), which was predicted to encode a thiazol(in)e substructure. Cloning and heterologous expression of this BGC revealed that it produces bacillamide D. In-depth functional evaluation showed potent cytotoxicity and inhibition of cell migration using the human cell lines HCT116 and HEK293, which was validated using primary mouse organoids. This work establishes the bacillamides as selective cytotoxins from a bacterial gut isolate that affect mammalian cells. Our targeted structure-function-predictive approach is demonstrated to be a streamlined method to discover deleterious gut microbial metabolites with potential effects on human health.

Machine Learning Assisted Hit Prioritization for High Throughput Screening in Drug Discovery.

Efficient prioritization of bioactive compounds from high throughput screening campaigns is a fundamental challenge for accelerating drug development efforts. In this study, we present the first data-driven approach to simultaneously detect assay interferents and prioritize true bioactive compounds. By analyzing the learning dynamics during training of a gradient boosting model on noisy high throughput screening data using a novel formulation of sample influence, we are able to distinguish between compounds exhibiting the desired biological response and those producing assay artifacts. Therefore, our method enables false positive and true positive detection without relying on prior screens or assay interference mechanisms, making it applicable to any high throughput screening campaign. We demonstrate that our approach consistently excludes assay interferents with different mechanisms and prioritizes biologically relevant compounds more efficiently than all tested baselines, including a retrospective case study simulating its use in a real drug discovery campaign. Finally, our tool is extremely computationally efficient, requiring less than 30 s per assay on low-resource hardware. As such, our findings show that our method is an ideal addition to existing false positive detection tools and can be used to guide further pharmacological optimization after high throughput screening campaigns.

Effectiveness of molecular fingerprints for exploring the chemical space of natural products.

Natural products are a diverse class of compounds with promising biological properties, such as high potency and excellent selectivity. However, they have different structural motifs than typical drug-like compounds, e.g., a wider range of molecular weight, multiple stereocenters and higher fraction of sp3-hybridized carbons. This makes the encoding of natural products via molecular fingerprints difficult, thus restricting their use in cheminformatics studies. To tackle this issue, we explored over 30 years of research to systematically evaluate which molecular fingerprint provides the best performance on the natural product chemical space. We considered 20 molecular fingerprints from four different sources, which we then benchmarked on over 100,000 unique natural products from the COCONUT (COlleCtion of Open Natural prodUcTs) and CMNPD (Comprehensive Marine Natural Products Database) databases. Our analysis focused on the correlation between different fingerprints and their classification performance on 12 bioactivity prediction datasets. Our results show that different encodings can provide fundamentally different views of the natural product chemical space, leading to substantial differences in pairwise similarity and performance. While Extended Connectivity Fingerprints are the de-facto option to encoding drug-like compounds, other fingerprints resulted to match or outperform them for bioactivity prediction of natural products. These results highlight the need to evaluate multiple fingerprinting algorithms for optimal performance and suggest new areas of research. Finally, we provide an open-source Python package for computing all molecular fingerprints considered in the study, as well as data and scripts necessary to reproduce the results, at https://github.com/dahvida/NP_Fingerprints .

Pronucleotide Probes Reveal a Diverging Specificity for AMPylation vs UMPylation of Human and Bacterial Nucleotide Transferases.

AMPylation is a post-translational modification utilized by human and bacterial cells to modulate the activity and function of specific proteins. Major AMPylators such as human FICD and bacterial VopS have been studied extensively for their substrate and target scope in vitro. Recently, an AMP pronucleotide probe also facilitated the in situ analysis of AMPylation in living cells. Based on this technology, we here introduce a novel UMP pronucleotide probe and utilize it to profile uninfected and Vibrio parahaemolyticus infected human cells. Mass spectrometric analysis of labeled protein targets reveals an unexpected promiscuity of human nucleotide transferases with an almost identical target set of AMP- and UMPylated proteins. Vice versa, studies in cells infected by V. parahaemolyticus and its effector VopS revealed solely AMPylation of host enzymes, highlighting a so far unknown specificity of this transferase for ATP. Taken together, pronucleotide probes provide an unprecedented insight into the in situ activity profile of crucial nucleotide transferases, which can largely differ from their in vitro activity.

A Pd-labile fluoroquinolone prodrug efficiently prevents biofilm formation on coated surfaces.

Surface-adhered bacteria on implants represent a major challenge for antibiotic treatment. We introduce hydrogel-coated surfaces loaded with tailored Pd-nanosheets which catalyze the release of antibiotics from inactive prodrugs. Masked and antibiotically inactive fluoroquinolone analogs were efficiently activated at the surface and prevented the formation of Staphylococcus aureus biofilms.

Monitoring host-pathogen interactions using chemical proteomics.

With the rapid emergence and the dissemination of microbial resistance to conventional chemotherapy, the shortage of novel antimicrobial drugs has raised a global health threat. As molecular interactions between microbial pathogens and their mammalian hosts are crucial to establish virulence, pathogenicity, and infectivity, a detailed understanding of these interactions has the potential to reveal novel therapeutic targets and treatment strategies. Bidirectional molecular communication between microbes and eukaryotes is essential for both pathogenic and commensal organisms to colonise their host. In particular, several devastating pathogens exploit host signalling to adjust the expression of energetically costly virulent behaviours. Chemical proteomics has emerged as a powerful tool to interrogate the protein interaction partners of small molecules and has been successfully applied to advance host-pathogen communication studies. Here, we present recent significant progress made by this approach and provide a perspective for future studies.

Lubricity, wear prevention, and anti-biofouling properties of macromolecular coatings for endotracheal tubes.

Macromolecular coatings can improve the surface properties of many medical devices by enhancing their wetting behavior, tribological performance, and anti-biofouling properties - and covalent coatings produced from mucin glycoproteins have been shown to be very powerful in all those aspects. However, obtaining highly functional mucin glycoproteins is, at the moment, still a time-consuming process, which renders mucins rather expensive compared to other biomacromolecules. Here, we study a set of commercially available macromolecules that have the potential of substituting mucins in coatings for endotracheal tubes (ETTs). We present an overview of the different properties these macromolecular coatings establish on the ETT surface and whether they withstand storage or sterilization processes. Our study pinpoints several strategies of how to enhance the lubricity of ETTs by applying macromolecular coatings but also demonstrates the limited anti-biofouling abilities of well-established macromolecules such as hyaluronic acid, polyethylene glycol, and dextran. Based on the obtained results, we discuss to what extent those coatings can be considered equivalent alternatives to mucin coatings for applications on medical devices - their applicability does not have to be limited to ETTs, but could be broadened to catheters and endoscopes as well.

Structure of Staphylococcus aureus ClpP Bound to the Covalent Active-Site Inhibitor Cystargolide A.

The caseinolytic protease is a highly conserved serine protease, crucial to prokaryotic and eukaryotic protein homeostasis, and a promising antibacterial and anticancer drug target. Herein, we describe the potent cystargolides as the first natural ß-lactone inhibitors of the proteolytic core ClpP. Based on the discovery of two clpP genes next to the cystargolide biosynthetic gene cluster in Kitasatospora cystarginea, we explored ClpP as a potential cystargolide target. We show the inhibition of Staphylococcus aureus ClpP by cystargolide A and B by different biochemical methods in vitro. Synthesis of semisynthetic derivatives and probes with improved cell penetration allowed us to confirm ClpP as a specific target in S. aureus cells and to demonstrate the anti-virulence activity of this natural product class. Crystal structures show cystargolide A covalently bound to all 14 active sites of ClpP from S. aureus, Aquifex aeolicus, and Photorhabdus laumondii, and reveal the molecular mechanism of ClpP inhibition by ß-lactones, the predominant class of ClpP inhibitors.

The DNA-binding induced (de)AMPylation activity of a Coxiella burnetii Fic enzyme targets Histone H3.

The intracellular bacterial pathogen Coxiella burnetii evades the host response by secreting effector proteins that aid in establishing a replication-friendly niche. Bacterial filamentation induced by cyclic AMP (Fic) enzymes can act as effectors by covalently modifying target proteins with the posttranslational AMPylation by transferring adenosine monophosphate (AMP) from adenosine triphosphate (ATP) to a hydroxyl-containing side chain. Here we identify the gene product of C. burnetii CBU_0822, termed C. burnetii Fic 2 (CbFic2), to AMPylate host cell histone H3 at serine 10 and serine 28. We show that CbFic2 acts as a bifunctional enzyme, both capable of AMPylation as well as deAMPylation, and is regulated by the binding of DNA via a C-terminal helix-turn-helix domain. We propose that CbFic2 performs AMPylation in its monomeric state, switching to a deAMPylating dimer upon DNA binding. This study unveils reversible histone modification by a specific enzyme of a pathogenic bacterium.

Practical guidelines for the use of gradient boosting for molecular property prediction.

Decision tree ensembles are among the most robust, high-performing and computationally efficient machine learning approaches for quantitative structure-activity relationship (QSAR) modeling. Among them, gradient boosting has recently garnered particular attention, for its performance in data science competitions, virtual screening campaigns, and bioactivity prediction. However, different variants of gradient boosting exist, the most popular being XGBoost, LightGBM and CatBoost. Our study provides the first comprehensive comparison of these approaches for QSAR. To this end, we trained 157,590 gradient boosting models, which were evaluated on 16 datasets and 94 endpoints, comprising 1.4 million compounds in total. Our results show that XGBoost generally achieves the best predictive performance, while LightGBM requires the least training time, especially for larger datasets. In terms of feature importance, the models surprisingly rank molecular features differently, reflecting differences in regularization techniques and decision tree structures. Thus, expert knowledge must always be employed when evaluating data-driven explanations of bioactivity. Furthermore, our results show that the relevance of each hyperparameter varies greatly across datasets and that it is crucial to optimize as many hyperparameters as possible to maximize the predictive performance. In conclusion, our study provides the first set of guidelines for cheminformatics practitioners to effectively train, optimize and evaluate gradient boosting models for virtual screening and QSAR applications.

A chemical probe unravels the reactive proteome of health-associated catechols.

Catechol-containing natural products are common constituents of foods, drinks, and drugs. Natural products carrying this motif are often associated with beneficial biological effects such as anticancer activity and neuroprotection. However, the molecular mode of action behind these properties is poorly understood. Here, we apply a mass spectrometry-based competitive chemical proteomics approach to elucidate the target scope of catechol-containing bioactive molecules from diverse foods and drugs. Inspired by the protein reactivity of catecholamine neurotransmitters, we designed and synthesised a broadly reactive minimalist catechol chemical probe based on dopamine. Initial labelling experiments in live human cells demonstrated broad protein binding by the probe, which was largely outcompeted by its parent compound dopamine. Next, we investigated the competition profile of a selection of biologically relevant catechol-containing substances. With this approach, we characterised the protein reactivity and the target scope of dopamine and ten biologically relevant catechols. Strikingly, proteins associated with the endoplasmic reticulum (ER) were among the main targets. ER stress assays in the presence of reactive catechols revealed an activation of the unfolded protein response (UPR). The UPR is highly relevant in oncology and cellular resilience, which may provide an explanation of the health-promoting effects attributed to many catechol-containing natural products.

Rapid Diagnostic Platform for Personalized Vitamin B6 Detection in Erythrocytes via PLP Cofactor Mimics.

Personalized assessment of vitamin levels in point-of-care (POC) devices is urgently needed to advance the recognition of diseases associated with malnutrition and unbalanced diets. We here introduce a diagnostic platform, which showcases an easy and rapid readout of vitamin B6 (pyridoxal phosphate, PLP) levels in erythrocytes as a first step toward a home-use POC. The technology is based on fluorescent probes, which bind to PLP-dependent enzymes (PLP-DEs) and thereby indirectly report their occupancy with endogenous B6. For example, low vitamin levels result in high probe binding, yielding a strong signal and vice versa. Antibodies against signature human PLP-DEs were immobilized on microarrays to capture probe labeled enzymes for fluorescent detection. Calibrating the system with defined B6 levels revealed a concentration-depended readout as well as sufficient sensitivity for its detection in erythrocytes. To account for individual differences in protein expression, a second antibody was used to normalize protein abundance. This sandwiched assay correctly reported relative B6 levels in human erythrocyte samples, as confirmed by classical laboratory diagnostics. In principle, the platform layout can be easily expanded to other crucial vitamins beyond B6 via an analogous probe strategy.

A Chemical Proteomic Strategy Reveals Inhibitors of Lipoate Salvage in Bacteria and Parasites.

The development of novel anti-infectives requires unprecedented strategies targeting pathways which are solely present in pathogens but absent in humans. Following this principle, we developed inhibitors of lipoic acid (LA) salvage, a crucial pathway for the survival of LA auxotrophic bacteria and parasites but non-essential in human cells. An LA-based probe was selectively transferred onto substrate proteins via lipoate protein ligase (LPL) in intact cells, and their binding sites were determined by mass spectrometry. Probe labeling served as a proxy of LPL activity, enabling in situ screenings for cell-permeable LPL inhibitors. Profiling a focused compound library revealed two substrate analogs (LAMe and C3) as inhibitors, which were further validated by binding studies and co-crystallography. Importantly, LAMe exhibited low toxicity in human cells and achieved killing of Plasmodium falciparum in erythrocytes with an EC50 value of 15 µM, making it the most effective LPL inhibitor reported to date.

The Cyanobacterial "Nutraceutical" Phycocyanobilin Inhibits Cysteine Protease Legumain.

The blue biliprotein phycocyanin, produced by photo-autotrophic cyanobacteria including spirulina (Arthrospira) and marketed as a natural food supplement or "nutraceutical," is reported to have anti-inflammatory, antioxidant, immunomodulatory, and anticancer activity. These diverse biological activities have been specifically attributed to the phycocyanin chromophore, phycocyanobilin (PCB). However, the mechanism of action of PCB and the molecular targets responsible for the beneficial properties of PCB are not well understood. We have developed a procedure to rapidly cleave the PCB pigment from phycocyanin by ethanolysis and then characterized it as an electrophilic natural product that interacts covalently with thiol nucleophiles but lacks any appreciable cytotoxicity or antibacterial activity against common pathogens and gut microbes. We then designed alkyne-bearing PCB probes for use in chemical proteomics target deconvolution studies. Target identification and validation revealed the cysteine protease legumain (also known as asparaginyl endopeptidase, AEP) to be a target of PCB. Inhibition of this target may account for PCB's diverse reported biological activities.

Profiling the Heme-Binding Proteomes of Bacteria Using Chemical Proteomics.

Heme is a cofactor with myriad roles and essential to almost all living organisms. Beyond classical gas transport and catalytic functions, heme is increasingly appreciated as a tightly controlled signalling molecule regulating protein expression. However, heme acquisition, biosynthesis and regulation is poorly understood beyond a few model organisms, and the heme-binding proteome has not been fully characterised in bacteria. Yet as heme homeostasis is critical for bacterial survival, heme-binding proteins are promising drug targets. Herein we report a chemical proteomics method for global profiling of heme-binding proteins in live cells for the first time. Employing a panel of heme-based clickable and photoaffinity probes enabled the profiling of 32-54 % of the known heme-binding proteomes in Gram-positive and Gram-negative bacteria. This simple-to-implement profiling strategy could be interchangeably applied to different cell types and systems and fuel future research into heme biology.

A comprehensive set of ER protein disulfide isomerase family members supports the biogenesis of proinflammatory interleukin 12 family cytokines.

Cytokines of the interleukin 12 (IL-12) family are assembled combinatorially from shared α and ß subunits. A common theme is that human IL-12 family α subunits remain incompletely structured in isolation until they pair with a designate ß subunit. Accordingly, chaperones need to support and control specific assembly processes. It remains incompletely understood, which chaperones are involved in IL-12 family biogenesis. Here, we site-specifically introduce photocrosslinking amino acids into the IL-12 and IL-23 α subunits (IL-12α and IL-23α) for stabilization of transient chaperone-client complexes for mass spectrometry. Our analysis reveals that a large set of endoplasmic reticulum chaperones interacts with IL-12α and IL-23α. Among these chaperones, we focus on protein disulfide isomerase (PDI) family members and reveal IL-12 family subunits to be clients of several incompletely characterized PDIs. We find that different PDIs show selectivity for different cysteines in IL-12α and IL-23α. Despite this, PDI binding generally stabilizes unassembled IL-12α and IL-23α against degradation. In contrast, α:ß assembly appears robust, and only multiple simultaneous PDI depletions reduce IL-12 secretion. Our comprehensive analysis of the IL-12/IL-23 chaperone machinery reveals a hitherto uncharacterized role for several PDIs in this process. This extends our understanding of how cells accomplish the task of specific protein assembly reactions for signaling processes. Furthermore, our findings show that cytokine secretion can be modulated by targeting specific endoplasmic reticulum chaperones.