Canonical protein phosphorylation patterns are a thoroughly studied post-translational modification (PTM) driving distinct regulatory mechanisms in both prokaryotes, and eukaryotes. In contrast, the identification and investigation of essential components that regulate non-canonical phosphorylation has received considerably less attention, although these PTMs are associated with important functions. One notable example is arginine phosphorylation which modulates processes such as protein degradation, transcriptional regulation and spore germination in bacteria. Herein we introduce the first in class covalent activity-based probes to study phosphoarginine-phosphatases. We identify unsaturated phosphonamidic acids as bespoke electrophilic phosphoarginine (pArg) mimics, which allowed to uncover a series of unprecedented pArg-phosphatases, which in part had been previously annotated as low molecular weight tyrosine-phosphatases across phylogenetically distinct microbial species. This work, which serves as the first example of proteome-wide activity-based profiling of pArg phosphatases will help inform the development of new therapeutic modalities and expand our understanding of bacterial signal transduction. ### Competing Interest Statement The authors have declared no competing interest. Deutsche Forschungsgemeinschaft, 392923329, HA 4468/10-1 Leibniz Association, https://ror.org/01n6r0e97, SAW-2018-FMP-4-P5label European Union, breakingBAC 101096911

Glucocorticoids such as dexamethasone (DXE) are first-line treatments for inflammatory bowel disease (IBD). IBD patients also experience an increased colonization of the intestine by sulfate-reducing Desulfovibrio spp. Here, we show that DXE modulates bacterial motility in the gut commensal Desulfovibrio desulfuricans through a metabolism-independent mechanism. To identify bacterial targets, we developed a DXE-derived chemical probe and performed affinity-based protein profiling, which revealed the flagellar cap protein FliD (Ddes_0530) as a principal binding partner. Structural modeling using AlphaFold3 and Boltz2 predicted DXE binding within a conserved groove of the FliD C-terminal domain. Furthermore, the tip of the flagellum of Desulfovibrio , but not that of Escherichia coli could be fluorescently labeled with TAMRA-DXE, but not with TAMRA-norethiosterone, suggesting specific binding of DXE to Ddes_0530 in situ. As consequence of this interaction, transmission electron microscopy showed that DXE treatment prevented flagellation in a subpopulation and reduced flagellar length in D. desulfuricans strains ATCC 27774 and CCUG 72978, respectively. Quantitative motility tracking revealed a non-monotonic, dose-dependent modulation of swimming velocity, with peak stimulation at 10 μM DXE, accompanied by straighter trajectories and enhanced net displacement. Together, these findings uncover a previously unrecognized mode of action for DXE which directly perturbs flagellar biogenesis and motility of an important gut microbiome member of IBD patients.

Abstract Antibiotic resistance continues to rise, yet most new drug candidates act through long-established targets. Faster mode of action (MoA) assessment would enable more effective prioritization of screening hits and help identify compounds with novel mechanisms. In this study, we aimed to develop a scalable framework for MoA inference from antibiotic-induced cellular response profiles in Escherichia coli . We generated a multimodal dataset spanning more than 50 antibiotics, including proteome profiles, chemical structure descriptors, inhibitory concentrations and growth dynamics, and used it to build MAPPER (Mode of Action Prediction via Proteomics-Enhanced Representation), a framework comprising a fixed multimodal predictor and an uncertainty module. MAPPER accurately classified antibiotics across nine mechanistic classes, flagged compounds with likely novel mechanisms and retained predictive power in proteomics-only transfer experiments across mass spectrometry platforms and external data. Together, these results establish MAPPER as an innovative tool for MoA prediction and novelty detection, enabling prioritization of antibacterial candidates with distinct mechanisms.

The fluoroquinolone (FQ) class of antibiotics includes the world’s most prescribed antibiotics such as ciprofloxacin, levofloxacin, and ofloxacin that are known for their low bacterial resistance. This is despite their potential to trigger severe side effects, such as myopathy, hearing loss, tendinopathy, and tendon rupture. Thus, healthcare organizations around the world have recommended limiting the prescription of FQs. Tendinopathy is a common name for maladies that cause pain and degeneration in the tendon tissue, which can result in tendon rupture. Whilst there are several identified effects of FQ on tendons, the exact molecular mechanisms behind FQ-mediated tendon rupture are unclear. Previous research studies indicated that FQ-mediated tendinopathy and tendon rupture can be induced by changes in gene expression, metabolism, and function of tendon resident cells, thus leading to alterations in the extracellular matrix. Hence, this review begins with an update on FQs, their mode of action, and their known side effects, as well as summary information on tendon tissue structure and cellular content. Next, how FQs affect the tendon tissue and trigger tendinopathy and tendon rupture is explored in detail. Lastly, possible preventative measures and promising areas for future research are also discussed. Specifically, follow-up studies should focus on understanding the FQ-mediated tendon changes in a more complex manner and integrating in vitro with in vivo models. With respect to in vitro systems, the field should move towards three-dimensional models that reflect the cellular diversity found in the tissue.

Pyridoxal 5'-phosphate (PLP) is an essential cofactor for enzymes that catalyze diverse reactions in central metabolism. 2-Aminoacrylate (2AA) is a reactive enamine and an obligate catalytic intermediate in some PLP-mediated reactions. In the absence of the enamine/imine deaminase RidA, Salmonella enterica accumulates 2AA, which causes cellular stress. 2AA can attack PLP in the active site of some enzymes and covalently inactivate them by forming a 2AA-PLP adduct, which has already been characterized for some target enzymes in vivo and in vitro. The mechanism of 2AA attack suggests that a majority of cellular PLP-DEs would be targets of 2AA damage. Herein, a chemical proteomics workflow that uses PL (pyridoxal) probes to enrich PLP-DEs with a click chemistry-based protocol was implemented to investigate the global scale of 2AA damage in S. enterica. The results showed that PLP-DEs could be enriched in S. enterica with two different PL probes. When cells were labeled by providing a PL probe as the sole source of vitamin B6, several proteins were found to be more enriched when grown in conditions of high 2AA versus low 2AA stress. These data identified proteins that were previously shown to be attacked by 2AA as well as new candidate targets, demonstrating the usefulness of this approach to define the 2AA stress response with a global perspective. Growth analyses indicated that 2AA stress impacts the salvage of PL probes, suggesting that these and other PL probes will be valuable in future physiological studies to understand PLP salvage, a critical pathway in all organisms. In total, this study expands our understanding of 2AA metabolism and takes an initial step toward characterizing the global impact of 2AA stress in S. enterica. IMPORTANCE:Loss of RidA homologs results in 2-aminoacrylate stress in Salmonella and other bacteria. The stress is derived from the reaction of 2AA with a pyridoxal phosphate cofactor in metabolic enzymes, which inactivates the respective enzymes. This study uses a chemical proteomic method and, with an initial test case, explores the damage that is generated by 2AA on a global proteomic scale. This work provides a basis for probing the extent of 2AA stress in different organisms and for identifying the enzymes targeted by 2AA.

Antimicrobial resistance is a threat to human health rendering current first-line antibiotics ineffective. New agents overcoming resistance mechanisms are urgently needed to guarantee successful treatment of human disease in the future. Chlorotonils, a natural product class with yet unknown mode of action, were shown to have broad-spectrum activity against multi-resistant Gram-positive bacteria and the malaria parasite Plasmodium falciparum, with promising activity and safety in murine infection models. Here, we report that chlorotonils can target the cell membrane, cell wall, and protein biosynthesis. They can be characterized by a rapid onset of action via interference with ion homeostasis leading to membrane depolarization, however, without inducing severe barrier failure or cellular lysis. Further characterization confirmed binding of chlorotonils to bacterial membrane lipids eventually leading to uncontrolled potassium transport. Additionally, we identified functional inhibition of the peptidoglycan biosynthesis protein YbjG and methionine aminopeptidase MetAP as secondary targets of chlorotonils.

The escalating crisis of multiresistant bacteria demands the rapid discovery of novel antibiotics that transcend the limitations imposed by the biased chemical space of current libraries. To address this challenge, we introduce an innovative deep learning-driven pipeline for de novo antibiotic design. Our unique approach leverages a chemical language model to generate structurally unprecedented antibiotic candidates. The model was trained on a diverse chemical space of drug-like molecules and natural products. We then applied transfer learning using a data set of diverse antibiotic scaffolds to refine its generative capabilities. Using predictive modeling and expert curation, we prioritized the most promising compounds for synthesis. This pipeline identified a lead candidate with potent activity against methicillin-resistant Staphylococcus aureus. We then performed iterative refinement by synthesizing 40 derivatives of the lead compound. This effort produced a suite of active compounds, with 30 showing activity against S. aureus and 17 against Escherichia coli. Among these, lead compound D8 exhibited remarkable submicromolar and single-digit micromolar potency against the aforementioned pathogens, respectively. Mechanistic investigations point to the reductive generation of reactive species as its primary mode of action. This work validates a deep-learning pipeline that explores chemical space to generate antibiotic candidates. This process yields a potent nitrofuran derivative and a set of experimentally validated scaffolds to seed future antibiotic development.

Achieving reversible stiffening of biopolymer networks in a controlled manner remains a challenging topic in materials science, especially when trying to assess the following changes in mechanical material properties in real time. To address these challenges, we here utilize a custom-made measurement setup that allows us to manipulate the cross-linking state of alginate-based hydrogels in situ while quantifying the achieved alterations in the viscoelastic response of the biopolymer networks. Interpolymer connections in the biopolymer networks are created by a combination of light-induced, covalent cross-links, ionic cross-links, and DNA-based cross-links, where the latter two can be successfully removed again by employing either chelating agents (e.g., ethylenediaminetetraacetic acid and citrate) or suitable displacement DNA strands. In part, this range of the different cross-linking options mentioned is inter alia made possible by incorporating the glycoprotein mucin into the alginate system, which also allows for a range of different starting (∼0.2-400 Pa), intermediate (∼25 Pa-1.6 kPa), and final stiffnesses (∼4 Pa-1.2 kPa) of the mixed hydrogel matrix. At the same time, the presence of mucins (1-4% (w/v)) in the biopolymer mixture enhances the properties of the cytocompatible hydrogel by improving its antibacterial characteristics. Such well-controllable alginate/mucin networks with dynamically switchable mechanical properties will likely find broad applications in cell cultivation studies or tissue engineering applications.

Antibiotic resistance presents a growing global health crisis, demanding new therapeutic strategies that target novel bacterial mechanisms. Recent advances in protein structure prediction and machine learning-driven molecule generation offer a promising opportunity to accelerate drug discovery. However, practical guidance on selecting and integrating these models into real-world pipelines remains limited. In this study, we develop an end-to-end, artificial intelligence-guided antibiotic discovery pipeline that spans target identification to compound realization. We leverage structure-based clustering across predicted proteomes of multiple pathogens to identify conserved, essential, and non-human-homologous targets. We then systematically evaluate six leading 3D-structure-aware generative modelsx2014spanning diffusion, autoregressive, graph neural network, and language model architecturesx2014on their usability, chemical validity, and biological relevance. Rigorous post-processing filters and commercial analogue searches reduce over 100 000 generated compounds to a focused, synthesizable set. Our results highlight DeepBlock and TamGen as top performers across diverse criteria, while also revealing critical trade-offs between model complexity, usability, and output quality. This work provides a comparative benchmark and blueprint for deploying artificial intelligence in early-stage antibiotic development.

The OXA β-lactamases in Acinetobacter baumannii represent a primary mechanism for resistance to the carbapenems, a class of antibiotics that represent a last line for treatment. In a screen of an U.S. Food and Drug Administration (FDA)-approved drug library, we identified fendiline, a calcium channel blocker, had significantly more antimicrobial activity against OXA-23 expressing cells. Genetic and proteomic studies revealed that fendiline inhibited the essential lipoprotein trafficking pathway (Lol) in both A. baumannii (LolFD) and Escherichia coli (LolCDE). We demonstrate that OXA-23 is an outer membrane lipoprotein and its overexpression resulted in increased lethality in lolFD-depleted A. baumannii. Our results indicate that overexpression of the OXA-23 β-lactamase in A. baumannii stresses normal lipoprotein trafficking, which makes these cells more susceptible to fendiline. Overall, our data reveal a link between carbapenem resistance and the Lol pathway, which can be leveraged for new drug development.

Helicobacter pylori γ-glutamyltransferase (gGT) is a virulence factor that promotes bacterial colonization and immune tolerance. Although some studies addressed potential functional mechanisms, the supportive role of gGT for in vivo colonization remains unclear. Additionally, it is unknown how different gGT expression levels may lead to compensatory mechanisms ensuring infection and persistence. Hence, it is crucial to unravel the in vivo function of gGT. We assessed acid survival under conditions mimicking the human gastric fluid and elevated the pH in the murine stomach prior to H. pylori infection to link gGT-mediated acid resistance to colonization. By comparing proteomes of gGT-proficient and -deficient isolates before and after infecting mice, we investigated proteomic adaptations of gGT-deficient bacteria during infection. Our data indicate that gGT is crucial to sustain urease activity in acidic environments, thereby supporting survival and successful colonization. Absence of gGT triggers expression of proteins involved in the nitrogen and iron metabolism and boosts the expression of adhesins and flagellar proteins during infection, resulting in increased motility and adhesion capacity. In summary, gGT-dependent mechanisms confer a growth advantage to the bacterium in the gastric environment, which renders gGT a valuable target for the development of new treatments against H. pylori infection.

Fluoroquinolones (FQs) are an important class of potent broad-spectrum antibiotics. However, their general use is more and more limited by adverse side effects. While general mechanisms for the fluoroquinolone-associated disability (FQAD) have been identified, the underlying molecular targets of toxicity remain elusive. In this study, focusing on the most commonly prescribed FQs Ciprofloxacin and Levofloxacin, whole proteome analyses revealed prominent mitochondrial dysfunction in human cells, specifically of the complexes I and IV of the electron transport chain (ETC). Furthermore, global untargeted chemo-proteomic methodologies such as photo-affinity profiling with FQ-derived probes, as well as derivatization-free thermal proteome profiling, were applied to elucidate human protein off-targets of FQs in living cells. Accordingly, the interactions of FQs with mitochondrial AIFM1 and IDH2 have been identified and biochemically validated for their contribution to mitochondrial dysfunction. Of note, the FQ induced ETC dysfunction via AIFM1 activates the reverse carboxylation pathway of IDH2 for rescue, however, its simultaneous inhibition further enhances mitochondrial toxicity. This off-target discovery study provides unique insights into FQ toxicity enabling the utilization of identified molecular principles for the design of a safer FQ generation.

Antimicrobial resistance poses a fundamental global threat, necessitating new strategies for effective therapies. Cystobactamids, a class of antibacterial agents targeting bacterial gyrase and topoisomerase IV, represent a non-traditional chemical scaffold with broad-spectrum activity. For toxicological de-risking, we performed a comprehensive profiling on eukaryotic cells, focusing on cytotoxicity, genotoxicity, and mitochondrial toxicity, demonstrating cellular safety and superoxide scavenging properties. Studies in zebrafish embryos assessed developmental, cardiovascular, and hepatic toxicity, indicating a favorable in vivo safety profile. Metabolism studies revealed glucuronidation and amide bond hydrolysis as key pathways, whereby cystobactamid metabolic stability substantially improved by cobicistat co-treatment. Affinity-based protein profiling identified the cholesterol- and HCV-receptor scavenger receptor class B member 1 (SCARB1) as a primary eukaryotic off-target protein, with cystobactamids shown to inhibit SCARB1´s function, preventing hepatitis C virus pseudoparticle entry into cells. These findings suggest a high therapeutic potential for cystobactamids and highlight SCARB1 as a primary eukaryotic target.

Abstract Accurate prediction of drug–target interactions is critical for advancing drug discovery. By reducing time and cost, machine learning and deep learning can accelerate this laborious discovery process. In a novel approach, BarlowDTI, we utilise the powerful Barlow Twins architecture for feature-extraction while considering the structure of the target protein. Our method achieves state-of-the-art predictive performance against multiple established benchmarks using only one-dimensional input. The use of our hybrid approach of deep learning and gradient boosting machine as the underlying predictor ensures fast and efficient predictions without the need for substantial computational resources. We also propose the use of an influence method to investigate how the model reaches its decision based on individual training samples. By comparing co-crystal structures, we find that BarlowDTI effectively exploits catalytically active and stabilising residues, highlighting the model’s ability to generalise from one-dimensional input data. In addition, we further benchmark new baselines against existing methods. Together, these innovations improve the efficiency and effectiveness of drug–target interactions predictions, providing robust tools for accelerating drug development and deepening the understanding of molecular interactions. Therefore, we provide an easy-to-use web interface that can be freely accessed at https://www.bio.nat.tum.de/oc2/barlowdti . Scientific contribution Our computationally efficient and effective hybrid approach, combining the deep learning model Barlow Twins and gradient boosting machines, outperforms state-of-the-art methods across multiple splits and benchmarks using only one-dimensional input. Furthermore, we advance the field by proposing an influence method that elucidates model decision-making, thereby providing deeper insights into molecular interactions and improving the interpretability of drug-target interactions predictions. Graphical Abstract

Treatment of Mycobacterium tuberculosis infections is a challenging task due to long treatment regiments and a growing number of resistant clinical isolates. To identify new antibiotic hits, we screened a focused library of 400 synthetic compounds derived from a recently discovered molecule with promising anti-mycobacterial activity. A suite of more potent hit molecules was deciphered with sub-micromolar activity. Utilising tailored affinity-based probes for chemical proteomic investigations, we successfully pinpointed the mycolic acid transporter MmpL3 and two epoxide hydrolases, EphD and EphF, also linked to mycolic acid biosynthesis, as specific targets of the compounds. These targets were thoroughly and independently validated by activity assays, under- and overexpression, resistance generation, and proteomic studies. Structural refinement of the most potent hit molecules led to the development of a new lead compound that demonstrates enhanced biological activity in M. tuberculosis, low human cytotoxicity, and improved solubility and oral bioavailability - traits that are often challenging to achieve with anti-mycobacterial drugs. Overall, drug-likeness, as well as the dual mode of action, addressing the mycolic acid cell wall assembly at two distinct steps, holds significant potential for further in vivo applications.

The enzyme IspE in Plasmodium falciparum is considered an attractive drug target, as it is essential for parasite survival and is absent in the human proteome. Yet it still has not been addressed by a small-molecule inhibitor. In this study, we conducted a high-throughput screening campaign against the PfIspE enzyme. Our approach toward a PfIspE inhibitor comprises in vitro screening, structure-activity relationship studies, examining the docking position using an AlphaFold model, and finally target verification through probe binding and sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) analysis. The newly synthesized probe containing a diazirine and an alkyne moiety (23) allowed us to demonstrate its binding to IspE in the presence of a lysate of human cells (HEK293 cells) and to get evidence that both probe 23 and the best inhibitor of the series (19) compete for the same IspE binding site.

Antimicrobial resistance (AMR) is escalating globally at an alarming rate, posing a severe threat to public health and modern medicine. A substantial strategy to combat AMR and ensure safe and efficient antimicrobial therapies in the future is the development of antimicrobial agents based on novel scaffolds exerting an innovative mode of action. The antibacterial class of cystobactamids, natural products targeting the bacterial gyrase and topoisomerase IV, have such a novel scaffold, and their synthetic derivatives exhibit broad-spectrum antibiotic activity. Herein, as part of our de-risking strategy, we set out to study and characterize potential biological effects on eukaryotic cells. A comprehensive toxicological in vitro profiling focusing on general cytotoxicity, genotoxicity and mitochondrial toxicity is provided along with in vivo experiments to characterize potential developmental, cardio- and hepatotoxicity in zebrafish embryos. Results from these investigations support good safety and a presumably high therapeutic index of cystobactamids, even suggesting potential protective properties against oxidative cell stress. Furthermore, in vitro metabolism studies unveiled glucuronidation and amide bond hydrolysis as the main pathways of biotransformation in hepatocytes. Metabolic stability of cystobactamids was substantially improved by co-treatment with the CYP3A/OATP1B inhibitor cobicistat. In addition, eukaryotic off-targets of cystobactamids were studied on the molecular level employing affinity-based protein profiling and revealing scavenger receptor class B member 1 (SCARB1) as primary eukaryotic target protein. Indeed, functional inhibition of SCARB1 by cystobactamids was shown and effectively prevented hepatitis C virus pseudoparticles (HCVpp) from cell entry, thus confirming SCARB1 inhibition as novel target of the class.

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.

Herein, we describe the total synthesis of the depsipeptide vioprolide B and of an analogue, in which the (E)-dehydrobutyrine amino acid was replaced by glycine. The compounds were studied in biological assays which revealed cytotoxicity solely for vioprolide B presumably by covalent binding to cysteine residues of elongation factor eEF1A1 and of chromatin assembly factor CHAF1A.

Isonitrile natural products, also known as isocyanides, demonstrate potent antimicrobial activities, yet our understanding of their molecular targets remains limited. Here, we focus on the so far neglected group of monoisonitriles to gain further insights into their antimicrobial mode of action (MoA). Screening a focused monoisonitrile library revealed a potent S. aureus growth inhibitor with a different MoA compared to previously described isonitrile antibiotics. Chemical proteomics via competitive cysteine reactivity profiling, uncovered covalent modifications of two essential metabolic enzymes involved in the fatty acid biosynthetic process (FabF) and the hexosamine pathway (GlmS) at their active site cysteines. In-depth studies with the recombinant enzymes demonstrated concentration-dependent labeling, covalent binding to the catalytic site and corresponding functional inhibition by the isocyanide. Thermal proteome profiling and full proteome studies of compound-treated S. aureus further highlighted the destabilization and dysregulation of proteins related to the targeted pathways. Cytotoxicity and the inhibition of cytochrome P450 enzymes require optimization of the hit molecule prior to therapeutic application. The here described novel, covalent isocyanide MoA highlights the versatility of the functional group, making it a useful tool and out-of-the-box starting point for the development of innovative antibiotics.