Frontiers in Chemistry

Autophagic clearance of hyperphosphorylated tau is impaired in tauopathies, leading to the progressive accumulation of toxic tau species. Fungal metabolites provide a rich yet largely untapped source of neuroactive molecules with therapeutic potential. Here, we investigated metabolites from Lions Mane (Hericium erinaceus), Magic Mushrooms (Psilocybe spp.), and Ergot fungi (Claviceps spp.) using a computational drug-discovery workflow. We characterised their structural diversity, predicted blood-brain barrier permeability and toxicological properties, and integrated network pharmacology with protein-protein interaction and functional enrichment analyses to identify autophagy-related targets. Peroxisome proliferator-activated receptor gamma (PPARG), glycogen synthase kinase-3 beta (GSK3B), and casein kinase 2 alpha 1 (CSNK2A1) emerged as the three most promising candidates, given their complementary roles linking autophagy and tau pathology and their attractiveness as targets for multi-target drug discovery. Their interactions with fungal metabolites were evaluated by molecular docking, Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) rescoring, molecular dynamics simulations, complemented by machine-learning quantitative structure-activity relationship (QSAR) modelling as an additional, ligand-based line of evidence. Molecular dynamics and MM/GBSA analyses confirmed stable, target-specific binding for Corallocin A and Erinacerin M (PPARG), Chaetopyranin and Ergocryptine (GSK3B), and Hericioic Acid D and Isohericerin (CSNK2A1), alongside Emodin, a reference compound with previously reported activity against all three targets. QSAR predictions were informative primarily for the PPARG candidates, which fell within the models applicability domain; predictions for the remaining candidates fell outside their respective models applicability domains and were therefore not interpretable as evidence for or against their prioritisation. Reanalysis of an independent hippocampal proteomic dataset from Alzheimers disease patients showed CSNK2A1 protein levels to be significantly altered in the CA3 subfield, providing an additional, correlative line of support for this target; PPARG and GSK3B showed no significant changes in protein abundance, which does not preclude their functional involvement given their extensive post-translational regulation. Overall, these findings identify fungal metabolites as promising multi-target autophagy modulator candidates and provide a systematic computational strategy for prioritising them for experimental validation in tauopathies.

Gastrointestinal infections are a leading cause of death and morbidity worldwide. Antibiotics as current treatments are ineffective or not recommended due to the emergence of multidrug resistant organisms. The initial step of the pathogenesis for most of the enteric infections is the binding of the pathogen to oligosaccharide receptors on the surface of host cells, making these receptors attractive targets for novel antimicrobial strategies that do not rely on conventional antibiotics. Here, we developed an alternative therapeutic intervention based on a novel microbiome-based chemical engineering approach. We synthesized cholesteryl-peptides as flexible chemical scaffold for the presentation of carbohydrate GM1 mimic receptors in probiotic bacteria acting as a decoy for cholera toxin neutralization. The GM1-cholesteryl-peptides were stably embedded into the membranes of both gram positive and gram negative probiotics, Lactobacillus reuteri DSM and Escherichia coli Nissle 1917 respectively. The resulting GM1-coated probiotics demonstrated to quench nearly 100% of cholera toxin in vitro, functioning as decoys by preventing toxin binding to epithelial cells. The present study strongly suggests that our new and versatile biomimetic non-recombinant system could be employed to neutralize the functional effect of infections mediated by oligosaccharide receptors.

G protein-coupled receptors (GPCRs) represent the largest membrane protein family in the human body and the major targets of FDA-approved medications. Unlike some other physiological proteins, GPCRs are highly plastic and often exist as collections of conformational ensembles in the environment to exert their function. Therefore, understanding how a GPCR adopts different conformational ensembles in response to ligands and signaling partners is essential for drug development. 19F-NMR has emerged as one of the most promising tools in this regard; however, a well-established 19F-labeling system is still lacking, including an effective 19F probe that meets both environmental susceptibility and NMR sensitivity requirements, even though progress has been made dramatically in recent years. Thus, this manuscript reports a novel conformational probe (4-(bromomethyl)-ethoxy-2-(trifluoromethyl)benzene, BTMB) that offers paramount benefits for future GPCR conformational dynamics studies. To rationalize the mechanism behind BTMB's superiority for future probe development, we performed MD simulations, referenced to the current state-of-the-art probe, BTFMA. Our study suggests that the spatial proximity of aromatic residues significantly influences the chemical shift dispersion and linewidths of related 19F-probe-profiled conformational states, as well as the rigidity and compactness of -CF3 in the target protein.

Sulfation plays an important role in many metabolic processes such as substrate detoxification, solubilization or activation. The enzymes responsible for these reactions, sulfotransferases, occur in all domains of life and can be classified in two major, evolutionary independent groups, PAPS dependent and PAPS independent or arysulfate sulfotransferases (ASST) enzymes. Besides the fact that they play key roles in biological functions, sulfotransferases can be interesting enzymatic tools to selectively sulfate specific positions of various metabolites. To this end we need to understand the relation between sequence, structure and function. Actually, eukaryotic PAPS dependent sulfotransferases have extensively been studied, while we largely lack knowledge about the diversity of bacterial PAPS-independent ASSTs. We have conducted a multidisciplinary study of a bacterial sulfotransferase from Salmonella typhimurium, revealing the importance of active site residues for activity and guiding substrate specificity. Based on the crystal structure in complex with substrate, we used molecular docking combined with Quantum Mechanics/Molecular Mechanics (QM/MM) free energy calculations to investigate the reaction catalytic mechanism with a focus on the role of specific active site residues in substrate specificity. Our results show that the catalytic mechanism involving three conserved histidines is common with previously determined ASSTs, and highlight a specific pair of aromatic residues, Phe174 and Tyr557, that play an important role in defining the substrate specificity in ASST clade 5. These findings enhance our general understanding of how substrate specificity is attained and has the potential to guide further enzyme engineering to expand the acceptor scope of ASSTs.

Praziquantel, which has limited efficacy against young parasites and reduces susceptibility, is the principal therapy for schistosomiasis, a neglected tropical illness. This work identified fungal-derived compounds with potential dual inhibitory action against Schistosoma mansoni DHODH and cathepsin B1 using an integrated computational method. From 1,831 fungal metabolites, 120 were selected for molecular docking after structure standardisation, drug-likeness evaluation, ADMET, and toxicity screening. Ganoderlactone B (CID_122184973) and Spiroapplanatumine F (CID_132962217) strongly bound to DHODH and CB1, with docking affinities of -10.6 and -10.0 kcal/mol and -9.0 and -8.9, respectively. Docking validation showed good discrimination between active compounds and decoys with area-under-the-curve values of 0.98 for DHODH and 0.96 for CB1. The protein-ligand interaction study showed hydrogen bonding, hydrophobic interactions, and van der Waals contacts at the binding sites. In 100 ns molecular dynamics simulations, protein complexes exhibited modest backbone deviations and maintained compactness, although CID_132962217 showed sustained binding and a constrained conformation. MM-PBSA analysis identified CID_122184973 as the best common ligand for both targets. At the B3LYP/6-31G level, density functional theory calculations showed that CID_139584993 had the lowest HOMO-LUMO energy gap and hardness values of 3.552 and 1.776 eV, respectively, and the highest softness value of 0.282 eV-1, indicating greater electronic reactivity. Electrostatic potential mapping and QSAR predictions supported their interaction and antiparasitic potential. Overall, CID_122184973 and CID_132962217 are promising fungal scaffolds for dual-target anti-schistosomal drug development. Experimental enzyme inhibition, parasite viability, toxicity, and in vivo research are needed to confirm computational findings.

Antibiotics with new mechanisms are highly pursued to address the threat of infections caused by drug-resistant Gram-negative bacteria. Targeting MsbA, a key protein of the lipopolysaccharide biosynthesis pathway, represents a promising strategy to discover new classes of antibiotics. However, currently available MsbA-targeted molecules either lack sufficient potency or have unfavorable properties, necessitating expansion of chemical space. In this study, we chose the most promising cerastecin Cpd 4 as the template, and used two Artificial Intelligence (AI)-based tools, i.e. Link-INVENT and AutoMolDesigner for molecular design, performed chemical derivatization and antibacterial activity evaluation, which led to the discovery of Y-11 (MIC for A. baumannii: 0.5 g/mL). Encouragingly, Y-11 showed equivalent potency to Cpd4 for carbapenem-resistant A. baumannii, and less cytotoxicity and hemolysis as well as lower spontaneous resistance frequency. In vivo efficacy study demonstrated that Y-11 could effectively reduce bacterial loads in the mice infected by A. baumannii. The following mechanism study including molecular dynamics simulation, biochemical assay, and transmission electron microscope (TEM) analysis suggested that Y-11 inhibited the transport of lipooligosaccharide and impaired the formation of outer membrane, probably by competitively binding to the substrate binding site of MsbA and modulating ATPase activity. Taken together, we have discovered a MsbA-targeted small molecule Y-11 via AI-driven drug design, which provides a foundation for future antibiotic development.

Excessive osteoclast activity contributes to pathological bone loss in osteoporosis, rheumatoid arthritis, and osteolytic malignancies. The effects of small catechol derivatives on receptor activator of nuclear factor-{kappa}B ligand (RANKL)-induced osteoclastogenesis remain poorly understood. This study investigated the effects of 4-methylcatechol (4-MC) on RANKL-induced NF-{kappa}B activation and osteoclast differentiation. 4-MC reduced RANKL-induced NF-{kappa}B luciferase activity in HEK-293T/RANK cells. 4-MC also suppressed RANKL-induced TRAP activity in RAW264.7 cells in a concentration-dependent manner and reduced the number of TRAP-positive multinucleated osteoclasts, without affecting cell viability. Molecular docking predicted non-covalent binding of 4-MC within the ATP-binding hinge region of IKK{beta} (PDB: 4KIK), forming a close polar contact with Glu97, predicted hydrogen bonds with Cys99, and a hydrophobic contact with Ile165, within the pocket occupied by the co-crystallized inhibitor K252a. Covalent docking predicted that the oxidized quinone form of 4-MC engages Cys179 in the IKK{beta} activation loop. Quantum chemical calculations confirmed a markedly higher electrophilicity index for the oxidized quinone than for the parent catechol, supporting this mechanism. In silico ADMET profiling indicated favorable drug-likeness and safety. These findings identify IKK{beta} as a plausible molecular target of 4-MC through both non-covalent and covalent mechanisms. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=108 SRC="FIGDIR/small/741661v1_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@35a0d3org.highwire.dtl.DTLVardef@d19458org.highwire.dtl.DTLVardef@1623fadorg.highwire.dtl.DTLVardef@1429e8b_HPS_FORMAT_FIGEXP M_FIG C_FIG

The cornea is the outermost layer of the eye, most vulnerable to injury including from chemical exposure, either environmental, industrial or chemical weapons. For example, exposure of the eye to sulfur mustard (SM) can cause mustard gas keratopathy, resulting in devastating consequences for vision. Available treatments for corneal mustard keratopathy are either ineffective, or if used for a prolonged time, have deleterious side effects. Here, we aimed to harness the anti-inflammatory and anti-angiogenic peptide angiotensin-(1-7), known as Ang-(1-7), that is derived from the renin-angiotensin system (RAS). We designed and developed a protein-like polymer (PLP) displaying a brush of norleucine modified Ang (1-7) peptides (NLE Ang (1-7) PLP), which is a more potent derivative of Ang-(1-7), for administration as an eye drop. In a mouse model of nitrogen mustard (NM)-induced corneal injury, topical treatment and intraperitoneal (i.p.) injection of NLE Ang (1-7) PLP persistently minimized: (i) corneal haze; (ii) edema; (iii), expression of pro-inflammatory and pro-angiogenic genes; and (iv) neovascularization and conjunctivalization as evidenced after a prolonged treatment and recovery period. Collectively, our observations have demonstrated the efficacy of this novel polymer proteomimetic based eye drop treatment in reducing chemical agent-induced corneal injury as well as indicating its potential application in other ocular surface diseases associated with inflammation and angiogenesis.

The spread and evolution of antimicrobial resistance (AMR) pose significant threats to public health, food safety, and sustainable development. Metallo bea lactamases (MBLs), a class of carbapenemases that hydrolyze carbapenems, often considered last resort antibiotics, are of particular concern and underscore the urgent need to develop effective inhibitors. Recent advancements in bicyclic boronate inhibitors represent significant progress toward this goal. Although the mechanistic basis of NDM1 inhibition by bicyclic boronate inhibitors remains incompletely elucidated, this study systematically characterizes the binding profiles and intermolecular interaction landscapes between NDM1 and four cyclic boronic acid based inhibitors, vaborbactam (RPX7009), taniborbactam (VNRX 5133), xeruborbactam (QPX7728), and ledaborbactam (VNRX-5236). We established the NDM-1-mediated hydrolysis of two representative carbapenem antibiotics, meropenem and imipenem, as the reference system for comparative analysis. While conventional docking workflows often struggle to model metalloenzyme active sites accurately, the AMDock (Assisted Molecular Docking) platform, integrated with AutoDock optimized zinc force field, enables robust and reliable docking simulations for this enzyme family. Our AMDock based molecular docking not only identified the critical NDM1 binding site residues governing hydrogen-bond networks with ligands, but also revealed that bicyclic boronate inhibitors show substantially greater binding stability than both carbapenems and their monocyclic boronate counterparts. A follow-up 100 ns all atom molecular dynamics simulation in GROMACS provided atomistic level evidence for this enhanced performance: RMSD, RMSF, radius of gyration, continuous hydrogen bonding occupancy, and 2D free energy landscape analyses all consistently supported the higher binding affinity of bicyclic boronates. Ultimately, this study characterizes two promising drug candidates, QPX7728 and VNRX5133, as competitive inhibitors that can effectively rescue carbapenem activity against NDM1 MBL mediated antimicrobial resistance. This visualization elucidates interactions between NDM1 and its two ligand classes, carbapenem antibiotics and cyclic boronate inhibitors. It reveals the stability and interaction strength underlying the distinct inhibition pattern of bicyclic boronate inhibitors in the enzyme active site, offering a promising strategy to combat antibiotic resistance.

Endophytic fungi associated with the Himalayan yew (Taxus wallichiana) represent an underexplored source of bioactive secondary metabolites. This study investigated the extracellular metabolites of Annulohypoxylon purpureonitens isolated from Nepalese T. wallichiana using bioactivity screening combined with LCMS/MS-based metabolomics. The fungal extract exhibited broad-spectrum antibacterial activity, showing the strongest inhibition against Staphylococcus aureusand Enterococcus faecalis (MIC = 500 ug/mL). It also displayed notable antioxidant capacity(DPPH, ABTS, TPC &TFC) and cytotoxicity against HeLa and MCF-7 cancer cell lines. Metabolite profiling via GNPS molecular networking, manual MS/MS validation, and MASST reverse metabolomics putatively identified diverse compounds, including hydroquinidine, chlorogenic acid, muramic acid, and cordycepin conjugates widely distributed across public microbial datasets. Overall, A. purpureonitens is a promising source of multifunctional metabolites, laying a foundation for future compound isolation and functional characterization.

The binding affinities of a chimeric analog of a riboflavin derivative linked to biotin, (6- (7,8-dimethyl-2,4-dioxo-3,4-dihydrobenzo[g]pteridin-10(2H)-yl)hexyl 5-((3aS,4S,6aR)-2- oxohexahydro-1H-thieno[3,4-d]imidazol-4-yl)pentanoate), referred to as C6-Rf-biotin-tag, to the riboflavin binding retain or streptavidin are in the M range, 1.29 {+/-} 0.277 and 3.00 {+/-} 0.459, respectively. These values suggest that C6-Rf-biotin-tag has potential applications in diagnostic assay and labelling target flavin binding proteins. The C6-Rf-biotin-tag which was characterized with respect to physical and biochemical properties retains UV/Vis spectroscopic and fluorescence behavior similar to riboflavin.

In 1998 we predicted percent human intestinal absorption (HIA) for 86 drug and drug-like compounds from six molecular descriptors chosen by a genetic algorithm with a small neural network serving as the fitness function. That result rested on one division of the compounds into three sets: training, cross-validation and external prediction. Repeating the division shows it was a rather fortunate one. An extraction is one random draw from a wide distribution, so we repeat every experiment 250 times and report the result as a distribution. Across 250 stratified extractions, 14 match the published cross-validation error and only one matches the published external prediction error. Reconstructed this way, the published six descriptors give a mean extraction error roughly twice the external prediction value we reported in 1998 (Table 1). We then applied the same six descriptors to a larger set of 780 compounds from a public compilation. Under the 1998 network they give 22.50 %HIA units on training compounds against 25.77 on extracted compounds, whereas on the 86 they give 13.43 against 30.39. More compounds close the gap between fitting and prediction. Four datasets are modeled here: 780 small molecules with HIA measured in man, 3,771 small molecules and 1,281 cyclic peptides measured across Caco-2 cell monolayers, and 7,298 cyclic peptides measured across artificial membranes. Each is its own prediction problem, and one procedure is applied to all four. A genetic algorithm chooses which descriptors to use and how many, and a random forest grades each choice on compounds its own trees never saw. The descriptors chosen most often across the 250 extractions form one consensus set for each dataset. For absorption, 25 consensus descriptors under a random forest reach an extraction rms of 20.47 %HIA units at R 0.76. On the same compounds and the same extractions, the six 1998 descriptors under the 1998 network reach 25.77 at R 0.59. The four models are served at predicthia.ai, where a structure can be drawn or pasted, scored against its training set for similarity, and the training data with fitted models downloaded. Each model served is its fixed consensus set fitted on every compound in its dataset; the accuracy quoted beside a prediction comes from evaluating that same set across 250 extractions (Table 3). The fixed sets hold 25 descriptors for absorption, 55 for Caco-2 small-molecule permeability, 50 for Caco-2 peptide permeability and 25 for artificial-membrane permeability. Keywords: human intestinal absorption; QSPR; genetic algorithm; descriptor selection; cyclic peptides; membrane permeability; oral bioavailability; repeated extraction

Cancer is a serious public health problem, and is becoming more common, with a projected increase in deaths and more than 25 million new cases in coming decades. A number of molecular mechanisms are involved in the tumoral process, with one of them, never in mitosis A-related kinase 2 (NEK2), a serine/threonine protein kinase, being a frequent target of amplification in various malignancies that is responsible for chromosomal instability, aneuploidy and activation of several oncogenic pathways. Available kinase inhibitors are not yet optimized in terms of their pharmacokinetic properties for clinical use, and current therapies, such as chemotherapeutic agents or immunotherapies are often limited by their resistance. In silico methods represent an effective tool to search for novel potent inhibitors, before testing in animals, with time constraints and limited resources. To find new inhibitors of NEK2, we used E pharmacophore-based modeling and structure based virtual screening in this study. NEK2 was chosen as the target for therapeutic intervention and an energy optimized pharmacophore model was employed to screen the Enamine REAL library of millions of compounds. Pharmacodynamic and Pharmacokinetic properties of the Top hits were tested using ADMET profiling. These were further screened using molecular docking (standard precision and extra precision) and virtual screening to obtain three lead compounds 1, 2, and 3 which have docking score of -7.414, -8.037 and -7.562 respectively. MM-GBSA calculations were used to estimate the binding free energies for these complexes, which were determined to be -54.92, -54.18 and -49.23 kcal/mol. Lastly, 100 ns molecular dynamics simulations have been run to evaluate complex stability in dynamic situations. The overall results of the MD showed the overall stability of the NEK2-ligand complexes, and thus these three compounds are promising NEK2 inhibitor candidates and could be further validated in vitro and in vivo for clinical application. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=133 SRC="FIGDIR/small/742111v1_ufig1.gif" ALT="Figure 1"> View larger version (70K): org.highwire.dtl.DTLVardef@14e9cfeorg.highwire.dtl.DTLVardef@24ec78org.highwire.dtl.DTLVardef@20be75org.highwire.dtl.DTLVardef@1b80c02_HPS_FORMAT_FIGEXP M_FIG C_FIG

Neurotrophins regulate neuronal survival, differentiation, and synaptic plasticity through activation of tropomyosin receptor kinase (Trk) receptors, and their dysregulation is strongly implicated in neurodegenerative disorders, including Alzheimer's disease. However, the therapeutic application of recombinant neurotrophins remains limited by poor bioavailability, rapid degradation, and inadequate blood brain barrier permeability. Here, we report the discovery of Bavachin as a dual Trk-A/Trk-B neurotrophin mimetic via an integrated computational screening and experimental validation approach. Structure-based virtual screening of a bioactive natural product library derived from Traditional Chinese Medicine, combined with a novel consensus-ranking strategy, enabled the identification of flavonoid scaffolds targeting neurotrophin-binding sites of Trk receptors. Among these, Bavachin demonstrated robust, dose-dependent activation of both Trk-A and Trk-B receptors, but not Trk-C, indicating receptor selectivity. Induced-fit docking and molecular dynamics simulations revealed stable binding of Bavachin within conserved and receptor-specific ligand-binding pockets, consistent with its dual agonist activity. Collectively, this study identifies Bavachin as a putative small-molecule neurotrophin mimetic and establishes an integrated computational and experimental framework for the discovery of dual Trk-A/Trk-B agonists for neurodegenerative disease therapeutics.

Background and Purpose: Among new psychoactive substances, synthetic cannabinoid receptor agonists (SCRAs) encompass considerable structural diversity and show wide variation in cannabinoid receptor 1 (CB1) potency and efficacy, but the molecular and receptor-interaction characteristics underlying these differences remain unclear. We assessed the pharmacological profiles of 16 SCRAs and examined structural features associated with differences in CB1 potency and efficacy. Experimental Approach: CB1 agonist activity was measured in a CB1-G15-based Ca2+ assay, and cataleptic effects were assessed in mice. Ligand-receptor interactions were characterized by molecular docking to an active-state CB1 structure. Principal component analysis (PCA) was applied to residue-level interaction profiles, and the resulting scores were tested for associations with CB1 potency and efficacy. Key Results: Potency and efficacy varied widely across cellular and animal assays, with several SCRAs exhibiting different pharmacological responses across the two experimental systems. PCA identified an interaction pattern whose PC1 scores were significantly associated with Emax but not EC50, with contributions from activation-related CB1 residues including the PHE200-TRP356 toggle switch. Molecular descriptor analysis likewise identified structural features significantly associated with in vitro and in vivo Emax. Conclusion and Implications: Our findings suggest that CB1 efficacy is associated with distinct receptor-interaction patterns among structurally diverse SCRAs. Combining functional pharmacology with receptor-level interaction analysis provides structural insight into SCRA efficacy and may help prioritize emerging compounds for further pharmacological and behavioral evaluation.

2-Deoxyribose-5-Phosphate Aldolase (DERA) is a key enzyme in the pentose phosphate pathway. Due to its C-C bond formation and stereoselective capabilities, DERA has been widely used for biocatalytic applications including the synthesis of chiral intermediates for antiviral and anticancer drugs. While protein engineering has expanded its substrate pool, improved yield, and enhanced stereoselectivity, the molecular basis of stereoselectivity remains unclear. Here, we determined the crystal structures of wildtype DERA from Geobacillus sp. and two of its variants with opposite stereoselectivity. Using a combination of structural biology, biochemistry, organic synthesis and molecular dynamic simulations, we show that the catalytic Lysine adopts two conformations and the Lysine conformation is a key determinant of DERA stereoselectivity. We also identified a mechanism of regulating stereoselectivity via a key amino acid. Using DERA from E. coli, we show that these findings are most likely conserved among bacteria.

The red palm weevil, Rhynchophorus ferrugineus (Olivier) (Coleoptera: Curculionidae), is a globally invasive quarantine pest threatening palm cultivation across 49 countries and inflicting annual economic losses estimated at over USD 100 million. Weevil larvae burrow into palm trunks, causing progressive internal structural damage that rarely produces visible external symptoms until lethal injury has occurred, rendering early detection exceptionally challenging. In the absence of effective early-warning surveillance technologies, tens of thousands of infested palm trees have been removed across major palm-cultivation regions in the Middle East and Mediterranean basin. Rapid, sensitive detection of volatile organic compounds (VOCs) emitted by weevil colonies and infested palm trees therefore represents a critical unmet need for timely pest surveillance and intervention. Existing artificial gas sensors lack the chemical selectivity required to discriminate among structurally similar VOCs, and no validated field-deployable early-detection platform has been established to date. Here, we report a portable biohybrid sensor array that mimics insect olfaction by exploiting two classes of diagnostic chemical signatures: the male-released aggregation pheromone (4RS,5RS)-4-methylnonan-5-ol (ferrugineol) and ethyl ester volatile blends emitted by weevil-infested palm trees. The R. ferrugineus odorant receptor RferOR1 was stabilised in lipid nanodiscs and co-immobilised with two in vivo-synthesised odorant-binding proteins (RferOBP1768 and RferOBP23) on quartz crystal microbalance (QCM) transducers to construct the biohybrid sensing platform. The sensor array achieved selective detection of airborne ferrugineol at a limit of detection of approximately 60 parts per billion (ppb) under field conditions, distinguishing infested from healthy palms. OBP- and OR-functionalised sensors retained full functional activity for 12 and 7 months, respectively, under ambient storage, confirming operational robustness and shelf life suitable for long-term field deployment. This work translates the molecular architecture of the insect olfactory system into a practical, field-validated chemical sensor platform with direct applicability to early-stage R. ferrugineus infestation monitoring and sustainable integrated pest management. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=112 SRC="FIGDIR/small/744605v1_ufig1.gif" ALT="Figure 1"> View larger version (54K): org.highwire.dtl.DTLVardef@69f81forg.highwire.dtl.DTLVardef@120e05dorg.highwire.dtl.DTLVardef@16a0cb6org.highwire.dtl.DTLVardef@16889a8_HPS_FORMAT_FIGEXP M_FIG C_FIG

This study aims to identify potential inhibitors of the Ag85C enzyme from Mycobacterium tuberculosis through primary docking, pharmacophore modelling, and ADME/pharmacokinetics analysis. Delamanid and Pretomanid emerged as the top hits in primary docking, demonstrating strong binding affinities and interactions with key active site residues. A robust pharmacophore model was developed, identifying essential features for binding and used to screen 4254 antituberculotic compounds, yielding three promising candidates: F0314-0040, F0398-0505, and F0349-2716. These compounds exhibited high binding affinities in major docking studies. ADME and pharmacokinetics analysis revealed favorable Drug likeness and absorption profiles, supporting their potential as effective antituberculotic agents. The integration of computational methods provided a comprehensive approach for rational drug design.

Insect glutathione S-transferases (GSTs) play critical roles in xenobiotic detoxification and insecticide resistance, making them promising targets for selective pest-control strategies. Here, we performed a comparative analysis of GSTs representing multiple classes from beneficial insects, agricultural pests, and disease vectors. We found significant isozyme-specific variations in catalytic activity, stability, and conformational dynamics, notably, in relation to inhibition by the commercial chemical agents, ethacrynic acid (ECA) and permethrin (PER). Sequence similarity network analysis revealed distinct clustering of major GST classes and further highlighted the relatively recent evolutionary divergence of the insect-specific delta and epsilon classes. Structural modeling revealed highly conserved glutathione-binding sites (G-site), but substantial variation in the hydrophobic substrate-binding regions (H-site). Further, epsilon-class GSTs exhibited 4 helices oriented approximately 10{degrees} closer to the glutathione-binding site than delta enzymes, suggesting differences in active-site architecture. Steady-state kinetic analyses using 1-chloro-2,4-dinitrobenzene (CDNB) demonstrated that epsilon GSTs are generally more catalytically efficient. Inhibition studies revealed that ECA acts as a potent mixed-type inhibitor of delta-class GSTs, reducing catalytic efficiency by up to 56-fold, whereas PER produced weaker and more species-dependent effects. Notably, ECA binding strongly stabilized delta GSTs, as measured by differential scanning fluorimetry (DSF) and induced a selective rigidification of the 3/4 linker region and active-site motifs, as observed by hydrogen-deuterium exchange mass spectrometry (HDX-MS). Collectively, these findings demonstrate the importance of analyzing the conformational dynamics mediating insect GST inhibition and provide a framework for exploiting isozyme-specific structural features in the design of next-generation selective insecticides.

Oxalyl-coenzyme A (oxalyl-CoA) is a key intermediate in oxalate metabolism in plants, fungi and oxalate-degrading bacteria, but its limited availability has restricted biochemical investigations of oxalyl-CoA-dependent enzymes. Here, we describe a practical semisynthetic procedure for the preparation of oxalyl-CoA based on rapid oxalyl transfer from S-oxalyl p-thiocresol to coenzyme A. The reaction was monitored directly by 1H NMR spectroscopy, allowing optimisation of pD and reaction conditions. Following removal of thiocresol and purification by reversed-phase HPLC, oxalyl-CoA was obtained in 39% yield as determined by quantitative 1H NMR. The product was characterised by high-resolution electrospray mass spectrometry and comprehensive 1H, 13C and 31P NMR spectroscopy, confirming its structure unequivocally. During the study, the limited stability of oxalyl-CoA in aqueous solution was documented, leading to recommendations for its purification and storage. The semisynthetic protocol provides a convenient source of analytically pure oxalyl-CoA suitable for biochemical assays and supplies reference spectroscopic data for its unambiguous identification. The biological utility of the semisynthetic oxalyl-CoA was demonstrated by its application as an acyl donor substrate in assays of PnBAHD15, enabling quantitative kinetic characterisation of the enzyme and illustrating its suitability for biochemical studies of oxalyl-CoA-dependent enzymes.