Molecules

It was recently reported that Methylobacterium extorquens AM1 produces the citrate-hydroxamate siderophore N-deoxyschizokinen A, identified by LC-HRMS. Multiple properties were inconsistent with the assignment: the feature eluted far later than the other schizokinen derivatives (17 min versus 6-8 min), a reversed-phase shift larger than a single-hydroxyl difference in a molecule can explain, further its accurate mass deviated from the calculated one by 28 ppm, well outside the error on the co-analyzed standards and its diagnostic m/z 105 and 77 fragments suggest a molecule with an aromatic moiety. A replicate comparison of identical samples in plastic versus glass autosampler vials was decisive: the m/z 387 feature was reproducibly present with plastic vials and absent with glass. We therefore conclude that the reported detection of N-deoxyschizokinen A in M. extorquens AM1 is an artifact, and recommend glass-vial and solvent-blank controls, an explicit accurate-mass threshold, and narrow MS/MS isolation when assigning trace siderophore-like features from complex extracts.

Polo-like kinase 1 (PLK1), a key regulatory protein controlling entry into and passage through mitosis, has been targeted through its kinase domain (KD) with mixed clinical success. Inhibition through the Polo-box domain (PBD) is a viable alternative through targeting the sub-cellular localization and kinase activity of PLK1. Novel non-peptidic compounds, termed abbapolins, were discovered through the REPLACE strategy and have been lead optimized through structure-based strategies and screening analogs in the NCI-60 tumor cell panel. Proteomic analysis revealed a correlation between abbapolin activity and PLK1 protein levels in the cell lines part of the NCI-60. Prostate cell lines were identified as among the most sensitive and led to further detailed studies of their activity in prostate cancer models. Compounds were evaluated for their pharmacokinetic properties, and in vivo efficacy, and results showed significant antitumor xenograft activity with no observable gross toxicity. Treated tumors were analyzed for loss of PLK1, which was previously shown to be induced by abbapolin binding. Results obtained showed a significant degradation of PLK1 in abbapolin-treated vs untreated tumors, thereby confirming on-target action in vivo and revealing PLK1 levels as a potential pharmacodynamic marker. Lead compounds were shown to sensitize PC tumors resistant to androgen deprivation therapy paving the way for future combination studies in vivo. These data provide an alternative pathway for effective PLK1 therapeutics that avoid the reported problems of molecules targeting the KD, in vivo proof-of-concept for the REPLACE strategy and validation for targeting the PBD as an anti-tumor drug development strategy.

Chagas disease, caused by Trypanosoma cruzi, demands novel therapeutic strategies that overcome the toxicity and limited efficacy of current treatments. To address this need, herein we report an integrative, target-centric strategy that combines parasite proteome mining, structural modeling, and experimental validation. Functional enrichment and druggability analyses identified phosphopyruvate hydratase (PPH) as a promising candidate due to its essential metabolic role and limited similarity to human homologs. Notably, proteome mining revealed the presence and conservation of PPH across kinetoplastid parasites, including Leishmania donovani, supporting its evaluation beyond T. cruzi. For the selected PPH sequences, AlphaFold-derived three-dimensional models underwent extensive molecular dynamics refinement, yielding stable conformational ensembles suitable for structure-based studies. Using this validated model, virtual screening of the Latin American Natural Products Database - LANaPDB - identified aptosimon as a top-ranked compound candidate. Molecular dynamics simulations further showed ligand-dependent binding behavior, suggesting alternative binding modes distinct from the canonical substrate configuration. In vitro assays demonstrated consistent antiparasitic activity against intracellular T. cruzi amastigotes (IC = 3.52 {+/-} 0.023 {micro}g/mL) and Leishmania donovani promastigotes (IC = 13.06 {+/-} 0.018 {micro}g/mL), supporting the biological relevance of the aptosimon-related lignan chemotype, hinokinin, across two kinetoplastid parasite models. Together, these results support PPH as a structurally tractable and biologically relevant candidate target, while identifying an aptosimon-related lignan chemotype, represented experimentally by hinokinin, as a cross-species antiparasitic scaffold that warrants further biochemical target-validation studies.

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy characterised by a highly immunosuppressive tumour microenvironment and limited therapeutic responses. Tumour-derived extracellular vesicles (EVs) contribute to PDAC progression by transferring immunomodulatory molecules and tumour-associated signals, suggesting EV-associated processes as potential intervention opportunities. However, the heterogeneity of EV biology and the complexity of tumour-immune interactions make single-target intervention strategies challenging. Here, we developed a computation-driven dual-layer candidate-prioritisation framework to identify potential modulators associated with PDAC EV-mediated immune escape through complementary production-side and action-side strategies. For the production-side layer, we focused on upstream processes related to EV biogenesis, cargo regulation, inflammatory signalling, and tumour-associated pathways. An 88-gene PDAC EV-associated target framework was integrated with cell-type-resolved prognosis annotations from ctPANDA and predicted targets of 18 natural products derived from Scutellaria baicalensis, Epimedium spp., and Cornus officinalis to prioritise natural-product candidates with disease relevance and potential chemical tractability. In parallel, key targets with experimentally resolved ligand-binding structures were subjected to pocket-guided de novo small-molecule design based on co-crystal ligand-defined binding sites, followed by structural, docking-based, and physicochemical screening of generated compounds. For the action-side layer, VHH and scFv binders were computationally designed and screened against extracellular regions of MET and CD81 to prioritise candidates potentially suitable for EV recognition and capture. This study provides a computational strategy for narrowing candidate spaces across both EV-associated production pathways and released vesicle recognition. The resulting small molecules, antibody-like binder models, and screening workflows provide a resource for future experimental validation of strategies targeting PDAC EV-associated immune regulation. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=118 SRC="FIGDIR/small/740294v1_ufig1.gif" ALT="Figure 1"> View larger version (48K): org.highwire.dtl.DTLVardef@11829b0org.highwire.dtl.DTLVardef@158efb5org.highwire.dtl.DTLVardef@1e17cc5org.highwire.dtl.DTLVardef@c69696_HPS_FORMAT_FIGEXP M_FIG C_FIG

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.

Human African trypanosomiasis, caused by a protozoan parasite Trypanosoma brucei, is a neglected tropical disease for which well-tolerated, conveniently administered, and highly efficacious medicines are still missing. Previously, T. brucei Phosphofructokinase was targeted by small-molecule inhibitor development efforts. This approach has shown promise both in vitro and in vivo. In this study, we have used these wet-lab results, evaluated the compounds already characterised by Molecular Dynamics simulations, found relationships between in silico and wet-lab data and used these observations to evaluate compounds that we selected through several different approaches of virtual screens. We observed that inhibitor-ATP interactions are highly predictive of the inhibitory activity. Several compounds selected through virtual screens have outperformed previously characterised compounds.

Kinema is a traditional fermented soybean food indigenous to the eastern Himalayan regions of Nepal and India. The fermentation process is primarily mediated by the bacterium Bacillus subtilis, which produces several bioactive compounds and enzymes with potential therapeutic applications. Considering the growing burden of cardiovascular diseases and the need for effective fibrinolytic agents for thrombolytic therapy, this study aimed to extract, partially purify, and evaluate the thrombolytic potential of kinemakinase derived from kinema prepared from white soybeans. Partial purification of the enzyme was achieved using ammonium sulfate precipitation. Thrombolytic activity was assessed in vitro using human blood clots, where three enzyme dilutions demonstrated clot lysis ranging from 66% to 68%, indicating considerable fibrinolytic potential. In silico analyses were also performed to investigate the structural and functional characteristics of the enzyme. The tertiary structure obtained from UniProt was modeled using the Robetta server and refined with GalaxyRefine. Docking with fibrin using ClusPro 2.0 and molecular dynamics simulations using iMODS confirmed favorable interaction and structural stability, while disulfide engineering enhanced protein stability. The findings suggest that kinema-derived kinemakinase may serve as a promising alternative thrombolytic agent, warranting further biochemical characterization and dosage optimization.

Hepatitis C virus (HCV) infection remains a major global health challenge despite the success of direct-acting antivirals (DAAs), which are limited by high cost, restricted accessibility, and the emergence of resistant strains. Natural products, particularly phytochemicals, represent a promising reservoir of antiviral agents with diverse mechanisms of action and favorable safety profiles. In this study, we combined wet-lab experimentation with computational approaches to identify plant-derived molecules capable of inhibiting HCV entry. Guided by ethnobotanical evidence, methanolic leaf extracts of Psidium guajava L., Plumeria alba L., Syzygium cumini L., and Tamarindus indica L. were prepared and evaluated for cytotoxicity in Huh7 hepatoma cells. Entry inhibition was assessed using EGFP-labelled HCV pseudoparticles (HCVpp) by qRT-PCR and confocal microscopy. Among the tested plants, Tamarindus indica extract significantly reduced KGFP expression (p < 0.05), confirmed by {Delta}{Delta}Cq analysis and impaired membrane fusion events, while Psidium guajava and Plumeria alba impaired intracellular trafficking without blocking initial attachment. Syzygium cumini showed no inhibitory effect under the tested conditions. Complementary in silico analyses included homology modelling, molecular docking, ADME/toxicity profiling, and molecular dynamics simulations of HCV E2-ligand complexes. Literature mining identified 39 candidate compounds, among which lupeol exhibited stable binding interactions with HCV E2 and favorable pharmacokinetic properties. Critically, in vitro binding assays confirmed that lupeol disrupted the E2-CD81 interaction, reducing bound E2-EGFP to 6% compared to controls. This was supported by HCV-pseudoparticle entry assays confirming inhibition of entry. Together, these findings establish Tamarindus indica and lupeol as potent HCV entry inhibitors.

Background: Subtype-selectivity predictions are scored against measured selectivity and judged against an assumed noise ceiling. We asked what an 2-adrenergic benchmark rewards and which controls change its interpretation. Research design and methods: On a frozen benchmark of 586 paired 2A/2C compounds we evaluated Glide SP docking, CNN rescoring, ligand-only fingerprint models, receptor descriptors and pose contacts, with dopamine D3/D2 as comparator, applying five controls: a measured ceiling, a cluster-identity null, a nonselective reference, a same-receptor floor and a trivial-descriptor baseline. Results: Five descriptors from SMILES reached Spearman 0.645, 72% of the measured ceiling, against 0.071 for Glide SP and 0.188 for CNN rescoring; receptor properties and pose contacts reduced to size under control, while a non-size signal of 0.258 survived. Measured rather than propagated noise raised that ceiling from 0.704 to 0.897; cluster identity alone reached R2 0.499 on D3/D2 and none on 2; a nonselective reference received +1.43 to +4.79 kcal/mol where zero is expected; and a same-receptor floor reached 1.77-fold against 1.88-fold across subtypes. Conclusions: Such benchmarks reward molecular size first; a method must exceed 0.645 before its score indicates structural reasoning. The controls are inexpensive; conclusions rest on two receptor pairs, a three-pair floor and static structures.

Malignant brain tumors are among the most aggressive and difficult to treat human cancers. Glioblastomas (World Health Organization grade IV gliomas) are particularly lethal and refractory to treatment. Few drugs exist that are even somewhat effective. Our investigation of the physiologic role of fatty acid (FA) activating enzymes (acyl-CoA synthetase; ACS) identified an ACS that was widely expressed in gliomas but not in normal glial cells. Depletion of this enzyme, ACSVL3 (very long-chain ACS3), by knockdown or knockout decreased the malignant behavior of several glioma cell models including U87MG and Mayo-22 cells both in culture and when grown as xenografts. Hypothesizing that ACSVL3 is a potential therapeutic target in glioma, we conducted a search for inhibitors of this enzyme and found that CB5 (grassofermata) was a promising candidate. Treating U87MG glioma cells with CB5 slowed growth in monolayer culture; the growth rate was similar to that seen in cells in which ACSVL3 was either knocked down or knocked out. CB5 inhibited growth in a dose-dependent manner over a narrow range, and concentrations above 10 M were toxic. Treatment at the lower dose of 3 M inhibited growth of U87MG cells but was reversible, suggesting that this dose was not toxic. CB5- treated U87MG cells exhibited an altered morphology with a larger size and longer projections. In contrast, normal human fibroblasts treated with 10 M CB5, a concentration that was toxic to U87MG cells, showed no effect on either growth rate or morphology. Treating U87MG cells with 3 M CB5 induced differentiation as shown by increased expression of the astrocyte-specific marker glial fibrillary acidic protein (GFAP). In contrast, GFAP levels remained low in ACSVL3 knockdown cells. CB5- treated U87MG cells were less invasive, and thus less malignant, than either untreated cells or ACSVL3 knockout cells when assessed by a scratch wound healing assay. Acute treatment of U87MG cells with 3 M CB5 decreased the ability of these cells to degrade FA of differing chain lengths from 16-24 carbons by {beta}-oxidation, suggesting that decreased ACS enzyme activity contributes at least in part to the drugs mechanism of action. NOD/SCID mice receiving up to 32 mg/kg/day CB5 by intraperitoneal injection showed no obvious side effects, suggesting that the drug was well-tolerated. Xenografts induced by subcutaneous injection of U87MG cells in the flanks of NOD/SCID mice were allowed to grow for 8 days after which half of the mice were treated with 2 mg/kg/day CB5. After 7 days of treatment, xenograft growth slowed in the treated mice and by 12 days tumor size had begun to decrease, suggesting therapeutic efficacy. When a similar study was done using xenografts induced by subcutaneous injection of Mayo-22 cells, which are maintained as subcutaneous tumors in mice rather than in cell culture, the effect of CB5 on tumor growth or weight at sacrifice was not statistically significant. The results of these studies suggest that CB5 may have therapeutic value in malignant glioma. Additional studies using other glioma models and other drugs chemically related to CB5 seem warranted.

BackgroundCaspase-3 and -7 are key effector caspases in the apoptotic pathway, a form of programmed cell death, and their activities serve as a well-established biomarker for evaluating environmental chemical toxicity and informing chemical risk assessment. Loss of mitochondrial membrane potential is a key event in the activation of Caspase-3/7 signaling and the subsequent induction of apoptosis. Therefore, simultaneous assessment of mitochondrial membrane potential and Caspase-3/7 activity enables elucidation of the mechanisms and pathways through which apoptosis is initiated.. Rapid and accurate assessment of the potential toxicity of environmental chemicals and drugs remains a major challenge. Quantitative Structure-Activity Relationship (QSAR) modeling have been widely used for toxicity prediction. Graph-based approaches encode compounds directly as molecular graphs, allowing structure-activity relationships to be learnt from molecular topology without the information loss in binary fingerprints. While advanced graph models such as graph transformers (GTs) have shown outstanding performance in many domains, they have not been fully leveraged in QSAR modeling on Caspase and mitochondrial toxicity. MethodsWe propose a QSAR modeling pipeline that encompasses assay data preprocessing, feature representations (fingerprints and molecular graphs), and benchmarking machine learning (ML) models, including classic ML models, graph neural networks (GNNs), GTs, and their consensus ensembles. Based on in vitro Caspase and mitochondrial assays in PubChem, we applied the pipeline to predict Caspase-3/7 activation and mitochondrial membrane potential (MMP). Beyond in vitro assays, we also built in vivo QSAR modeling for FDA Drug-Induced Liver Injury (DILI) gold standard on human hepatotoxicity. Moreover, mechanistic analysis on Caspase-3/7 activation was conducted by comparing with MMP disruption to identify chemical substructures that may be responsible for dual activations. We also investigated cell-line-specific responses by identifying structural motifs that selectively induce Caspase-3/7 activation in individual cell lines. ResultsExperimental evaluations show that GTs and GNNs outperformed classic ML models when the number of active compounds is large, such as MMP disruption, while classic ML models and GTs performed good for highly imbalance data with limited active compounds, such as Caspase-3/7 activation. For DILI prediction, the full consensus model achieved the highest AUC 0.69 and Graphormer had the highest F1 score 0.79, both surpassing the previous best model with AUC 0.63 and F1 0.65 with a large margin. Our mechanistic analysis shows that phenolic compounds bearing a para-hydroxyphenyl motif, as well as members of the lipophilic chain family with long alkyl chains can trigger the collapse of MMP, leading to the activation of caspases-3 and -7. Human embryonic kidney (HEK293) was the only cell line with a distinct structural motif: 1,1-dichloroethane and chlorobenzene. Human neuroblastoma (SK-N-SH) is uniquely impacted by an epoxide fragment and rat hepatoma (H-4-II-E) is uniquely impacted by a tetramethylcyclohexene motif and an acetaldehyde fragment. ConclusionsThe proposed pipeline for QSAR modeling, including data preprocessing, feature representations, and incorporation of advanced graph ML approaches, is highly effective in predicting not only on Caspase-3/7 activation and membrane potential collapse, but also on FDA DILI human hetatotoxicity. As future research directions, we will leverage extra information, e.g., biological activity and findings in existing toxicity literature, and recent advances in large language models and agentic AI to further improve the predictive performance and enable a sensitive and specific framework for assessing human hepatotoxicity of environmental compounds.

Dengue Virus Serotype 2 is a human pathogenic flavivirus that encodes a non-structural protein 3 (DEN2-NS3) containing a helicase domain essential for viral replication. DEN2-NS3 utilizes energy derived from NTP hydrolysis to unwind dsRNA and dsDNA. A galloylated catechin, (-)-epigallocatechin gallate (EGCG), was previously reported to be highly potent against the Zika Virus NS3 helicase, with an IC50 value observed at 295.7 nM. This prompted an investigation to determine if three catechins, namely, (-)-epigallocatechin (EGC), (-)-epicatechin gallate (ECG), and EGCG, would act as potent inhibitors of DEN2-NS3. Enzyme-inhibition assays revealed that the helicase catalytic domain, DEN2-NS3(S171-K618), is strongly inhibited by these galloylated catechins. We observed Ki values of 400 {+/-} 86.6 nM for EGCG (mixed-mode inhibition with respect to ATP) and 550 {+/-} 250 nM for ECG (uncompetitive inhibition with respect to ATP). Furthermore, using a computational workflow starting with SiteMap, we provide evidence that a highly druggable pocket exists within the RNA-binding cavity, involving residues ASP290, ARG387, ASP409, MET429, HIS487, ASP541, ARG599, and ASP603. These catechins were each analyzed through 200-ns molecular dynamics (MD) simulations to evaluate the binding stability within the target DEN2-NS3 binding pocket. Computational results revealed that EGCG and ECG maintained high stability, forming shared, highly persistent amino acid contacts (>45% occupancy) with ASP603, ARG599, ASP541, and ARG387. In conclusion, we have demonstrated that EGCG and ECG achieve strong binding and allosteric disruption of the critical RNA-binding channel. We suggest that future structural optimization of these compounds into stable prodrug derivatives could yield promising antiviral therapies. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=99 SRC="FIGDIR/small/733882v1_ufig1.gif" ALT="Figure 1"> View larger version (41K): org.highwire.dtl.DTLVardef@2db363org.highwire.dtl.DTLVardef@5c2fdaorg.highwire.dtl.DTLVardef@49bf8eorg.highwire.dtl.DTLVardef@1bf31f1_HPS_FORMAT_FIGEXP M_FIG C_FIG

BackgroundCancer continues to pose a massive global health burden. While plant-derived phytochemicals offer promising therapeutic leads, existing natural product databases often lack cancer specificity, dataset downloadability, and integrated screening tools. MethodsWe developed Sanjeevani, an integrative web platform cataloguing 4,823 curated anticancer phytochemicals. Using a balanced dataset of 9,646 molecules, we trained Support Vector Machine (SVM), Random Forest, and K-Nearest Neighbours classifiers using a hybrid feature representation of RDKit descriptors and 2048-bit ECFP4 fingerprints. The platform also integrates AutoDock Vina for web-based molecular docking for binding affinity, poses prediction and ADMET-AI for pharmacokinetics estimation. ResultsThe SVM model demonstrated the strongest predictive capability, achieving a top test accuracy of 0.966 and a ROC-AUC of 0.992. Benchmarking across five docking tools confirmed that AutoDock Vina successfully balanced computational automation with literature-consistent binding affinity replication. The final architecture provides rapid interactive 2D/3D visualizations integrated with downstream analysis tools. ConclusionSanjeevani provides an open-access, one-stop pipeline that bridges the gap between raw natural product data and actionable computational screening, accelerating natural product-based oncology drug discovery. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC="FIGDIR/small/732344v1_ufig1.gif" ALT="Figure 1"> View larger version (17K): org.highwire.dtl.DTLVardef@77183borg.highwire.dtl.DTLVardef@d7e465org.highwire.dtl.DTLVardef@1d3dfd7org.highwire.dtl.DTLVardef@10cc94d_HPS_FORMAT_FIGEXP M_FIG C_FIG

Introduction: Thromboinflammation, which represents the pathological interplay between inflammation and thrombosis, is a leading cause of global mortality. Current therapies are frequently associated with an increased risk of bleeding and do not adequately address the inflammatory component of the disease. The African tree Guibourtia tessmannii represents a promising source of natural anti-inflammatory compounds. This study aimed to synthesize and characterize silver nanoparticles using an aqueous bark extract of G. tessmannii (GT-AgNPs) and to evaluate their anti-inflammatory and anticoagulant properties. Methods: GT-AgNPs were synthesized by reducing silver nitrate with an aqueous extract of G. tessmannii bark. The nanoparticles were comprehensively characterized using UV-Vis spectroscopy, FTIR spectroscopy, powder X-ray diffraction, and scanning electron microscopy. In vitro anti-inflammatory activity was evaluated through inhibition of bovine serum albumin denaturation, whereas in vivo anti-inflammatory activity was assessed using the carrageenan-induced rat paw edema model. Anticoagulant activity was investigated by measuring activated partial thromboplastin time (aPTT) and prothrombin time (PT), corresponding to the intrinsic and extrinsic coagulation pathways, respectively. Results: The synthesis successfully produced GT-AgNPs with an average particle size of approximately 20 nm. Both the aqueous extract and GT-AgNPs exhibited marked anti-inflammatory activity. The nanoparticles achieved 95% inhibition of protein denaturation in vitro and 95% inhibition of carrageenan-induced paw edema in vivo at a dose of 0.4 mg/kg body weight after 5 h. Furthermore, both the extract and GT-AgNPs demonstrated dose-dependent anticoagulant activity. Conclusion: The study demonstrated that GT-AgNPs, synthesized from the bark of G. tessmannii, possess significant anti-inflammatory and anticoagulant properties. These findings highlight the potential of GT-AgNPs as nanotherapeutic candidates for the management of thrombo-inflammatory disorders.

Alternaria fungi produce various structurally diverse mycotoxins, several of which exhibit immunomodulatory properties. Among these, alternariol monomethyl ether (AME), alternariol (AOH), alterperylenol (ALTP), altertoxin I (ATX-I), and altersetin (AST) have been reported to suppress lipopolysaccharide (LPS)-induced inflammatory responses. However, the precise molecular mechanisms underlying these effects remain unclear. The present study aimed to elucidate how these selected Alternaria mycotoxins (0.1-50 M) target the NF-{kappa}B signaling pathway in THP-1 monocytes. Key components of the NF-{kappa}B cascade were analyzed by immunofluorescence microscopy, Western blotting and qRT-PCR. Nuclear translocation of NF-{kappa}B p65 and its phosphorylated form (p- NF-{kappa}B p65) was assessed by Western blot, while cytokine responses were determined at transcript (qRT-PCR) and protein (ELISA) levels. Moreover, in silico docking analyses were performed to investigate potential interactions of the toxins with IKK{beta}, and receptor-mediated crosstalk was studied using the glucocorticoid receptor (GR) antagonist RU486. Co-treatment with RU486 attenuated the immunosuppressive effects of 1 and 5 M AOH, indicating partial involvement of GR-dependent mechanisms. AME, AOH, ALTP, ATX-I, and AST increased total I{kappa}B levels while reducing its phosphorylated form. Additionally, AST and ALTP decreased the protein levels of Toll-like receptor 4 (TLR4), the I{kappa}B kinase (IKK) complex, NF-{kappa}B p65, and p- NF-{kappa}B p65. While AOH (5 M) and AST (25 M) reduced nuclear translocation of p65 and p-p65, ALTP (2 M) enhanced nuclear localization despite decreasing cytokine expression. Together, these findings suggest toxin-specific interference at multiple regulatory levels of NF-{kappa}B signaling and provide novel mechanistic insight into the immunomodulatory effects of Alternaria mycotoxins.

The MDM2-p53 protein-protein interaction is a validated oncology target, yet no food-derived linear peptide has been documented to engage the canonical three-anchor MDM2-p53 interface. We developed a multi-stage computational pipeline (PepVeg) to screen 22 plant and fungal proteomes (337,646 proteins) for MDM2-binding peptides, applying sequential in silico hydrolysis, physicochemical filtering, ESM-2 embedding-based dimensionality reduction, and pharmacophore-driven selection. Twenty-six candidates were evaluated by AlphaFold 3 (AF3) co-folding against MDM2(25-109), yielding 15 binders (iPTM >= 0.75; 58% of evaluated). A 36-peptide benchmark with 29 hard negatives confirmed AF3 discriminative power (Cohens d = 3.41; 95% CI: 1.94-4.88; Hedges g = 3.32; zero overlap). The lead candidate, SPAFESTWDILK -- a tryptic fragment of Zingiber officinale histone deacetylase (UniProt A0A8J5FLH2) -- was evaluated by eight computational assessments: AF3 Server (iPTM 0.83, SD 0.01), Protenix (iPTM 0.923), Chai-1 (iPTM 0.891), EvoEF2 (-55.57 EEU), two GROMACS simulations (no dissociation across two force fields), and two MM-PBSA calculations (-75.30 (SD 4.92) and -55.07 (SD 2.86) kcal/mol). The W8A point mutant produced an iPTM drop of 0.201, closely paralleling the p53 W23A drop of 0.193; we predict W8A substitution will abolish binding. SPAFESTWDILK ranked only #890/2,000 by ESM-2 similarity and was recovered solely through pharmacophore matching, demonstrating that no single pipeline stage alone is sufficient. To our knowledge, this is the first food-database-derived linear peptide with multi-convergent computational evidence supporting engagement of the canonical three-anchor MDM2-p53 interface. Experimental validation by SPR/ITC is warranted.

Epigenetics regulate cell-cycle kinetics, differentiation, apoptosis, and migration. Nuclear receptor-binding SET Domain (NSD) histone methyltransferases represent a family of oncoproteins with aberrant expression in cancer. Emerging reports suggest that NSD1 could be an attractive target as its expression is correlated with poor prognosis and tumorigenesis. Previously, we reported the target validation and structure-based virtual screening against NSD1, leading to the selection of several hit molecules with relatively high docking and MMGBSA delta G Bind scores. One of the best-fit molecules identified was 5-O-sulfamoyl adenosine (5-SA) and was compared with the S-Adenosyl-l-Cysteine (SAC), a structural analog of S-Adenosyl-l-Methionine (SAM) for its inhibitory activity against NSD1. IC50 values for 5-SA and SAC against NSD1 were 53.819 {micro}M and 115.003 {micro}M respectively. 5-SA significantly reduced the viability of DU145 and HepG2 cells with IC50 values calculated as 198{micro}M and 168.3 {micro}M respectively. It also reduced the RNA and protein expression levels of NSD1 and subsequently prevented dimethylation of lysine 36 on histone H3 (H3K36me2). Furthermore, 5-SA impeded proliferation, and migration, altered the cell cycle phase, and induced cell apoptosis. Interestingly, 5-SA potentiated the anticancer activity of 5-Fluorouracil (5-FU) against cancer cells. The xenograft model of prostate cancer also showed that 5-SA significantly reduced the tumor growth kinetics. However, the combination of 5-SA and 5-FU synergistically reduced tumor growth and improved survival of animals. To the best of our knowledge, we report for the first time that 5-SA mediated inhibition of NSD1 enhanced the tumor sensitivity to 5-FU and thereby, improved the tumor growth and progression. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=160 SRC="FIGDIR/small/731397v1_ufig1.gif" ALT="Figure 1"> View larger version (50K): org.highwire.dtl.DTLVardef@e2f0bdorg.highwire.dtl.DTLVardef@12b2ca6org.highwire.dtl.DTLVardef@1807613org.highwire.dtl.DTLVardef@c7f8f0_HPS_FORMAT_FIGEXP M_FIG C_FIG

Glioblastoma remains a highly aggressive and therapy-resistant brain tumor, with limited benefit from the current standard-of-care regimen combining surgery, radiotherapy, and temozolomide. Overcoming chemoresistance therefore represents a critical unmet clinical need. Here, we investigate the anticancer potential of Succisa pratensis and its ability to enhance TMZ efficacy in GBM models. Treatment with S. pratensis markedly reduced cell proliferation and migration while significantly increasing sensitivity to TMZ. Integrated multi-omics analyses revealed extensive metabolic rewiring, characterized by suppression of central carbon metabolism and activation of stress-adaptive pathways. Mechanistically, we identify the Pregnane X Receptor, a key regulator of drug metabolism and chemoresistance, as a central node affected by treatment. Although S. pratensis increased PXR expression, this was not accompanied by induction of canonical downstream targets, including MDR1 and ALDH1A1, indicating a functional impairment of PXR transcriptional activity. Consistently, pharmacological inhibition of PXR using the antagonist SPA70 further potentiated the cytotoxic effects of S. pratensis and TMZ. Docking analyses suggest that specific secondary metabolites, including apigenin-derived compounds, may interact with the PXR ligand-binding domain, providing a potential molecular basis for this effect. Collectively, our findings indicate that S. pratensis enhances TMZ efficacy by inducing metabolic vulnerability and functionally impairing PXR signaling. These results highlight the therapeutic potential of plant-derived metabolites as adjuvant strategies to overcome chemoresistance in glioblastoma. Article HighlightsO_LISuccisa pratensis enhances temozolomide efficacy in glioblastoma by reducing proliferation, migration, and clonogenic growth. C_LIO_LIIntegrated proteomic and metabolomic analyses reveal extensive metabolic rewiring, with suppression of central carbon metabolism and induction of stress-adaptive pathways. C_LIO_LIPregnane X Receptor (PXR), a key regulator of chemoresistance, is functionally impaired despite increased expression, resulting in reduced activation of drug-resistance genes. C_LIO_LIPharmacological inhibition of PXR further potentiates the antitumor effects of Succisa pratensis and temozolomide, promoting apoptotic cell death. C_LIO_LIApigenin-derived metabolites show high affinity for the PXR ligand-binding domain and emerge as promising candidates to overcome temozolomide resistance in glioblastoma. C_LI

Ethnopharmacological relevance: Australian Indigenous medicinal plants represent a valuable yet underexplored source of bioactive compounds with potential therapeutic relevance. The Iningai community of Central Queensland has traditionally used native plants to manage conditions associated with inflammation, pain, infection, and general illness. Scientific evaluation of these plants may provide evidence for their customary applications and identify bioactivities relevant to anticancer biodiscovery. Aim of the study: This study evaluated leaf and stem extracts of seven medicinal plants-Pittosporum angustifolium, Alphitonia excelsa, Calytrix microcoma, Geijera parviflora, Melaleuca uncinata, Gossypium australe, and Eucalyptus similis-traditionally used by the Iningai community, focusing on three biological processes relevant to cancer: oxidative stress, inflammation, and cellular proliferation. Materials and methods: Antioxidant activity was assessed using DPPH radical-scavenging and ferric reducing antioxidant power (FRAP) assays. Anti-inflammatory activity was evaluated in lipopolysaccharide (LPS)-stimulated THP-1 macrophage-like cells by profiling IFN-, TNF-, IL-6, IL-12, IL-18, and IL-23. Antiproliferative activity was assessed using MTT-based viability assays in human and murine liver cancer cell lines (Huh7, Hep3B, Hep-55.1c, and A52). Results: The extracts exhibited distinct biological activity profiles. G. parviflora stem and C. microcoma leaf extracts showed the strongest antioxidant activities, whereas P. angustifolium stem exhibited the weakest radical-scavenging capacity. Cytokine responses were extract-specific, with E. similis leaf extract demonstrating broad and pronounced suppression of multiple LPS-induced pro-inflammatory cytokines. Several extracts produced concentration-dependent reductions in liver cancer cell viability, with P. angustifolium stem exhibiting the most consistent and potent antiproliferative activity across the cell lines tested. Notably, strong antioxidant or anti-inflammatory activity did not necessarily correspond with antiproliferative activity. Conclusion: Australian Indigenous medicinal plant extracts demonstrated distinct antioxidant, immunomodulatory, and antiproliferative activities rather than uniform bioactivity across experimental systems. The divergent activities of G. parviflora, C. microcoma, E. similis, and P. angustifolium highlight the importance of integrated biological screening and support the value of Indigenous knowledge-guided biodiscovery. These plants represent promising sources for further investigation of selective bioactive compounds with potential relevance to anticancer drug discovery.

Structure-based drug discovery is known to apply computational methods in a tiered hierarchy, with each layer narrowing the candidate set and refining the binding picture before committing to the next, more expensive step. We present a four-tiered computational benchmarking study evaluating five engines against a panel of 36 compounds targeting B-secretase 1 (BACE1), a validated Alzheimer's disease target with extensive co-crystal ground truth. This study evaluates Flexible Docking and Boltz2 Cofolding as the primary tier, followed by Ensemble Docking, and then Protein-Ligand MD with MM/PBSA and MM/GBSA post-processing. This is then concluded with Relative Binding Free Energy Perturbation (RevFEP) as the terminal refinement layer. Each method was benchmarked against the experimental binding free energies derived from the co-crystal structures spanning -7.85 to -11.35 kcal/mol. Our findings revealed that Flexible Docking reproduced the co-crystal binding mode for 35 of 36 ligands (97.2% within 2.0 A RMSD) but did not rank potency at this resolution. Boltz2 CoFolding provided an orthogonal structural cross-check with a receptor backbone RMSD of 0.293 A against the experimental co-crystal structure. Ensemble Docking identified the optimal receptor conformation for downstream FEP setup. MD with MM/GBSA decomposition identified van der Waals complementarity as the primary potency driver (Pearson r = +0.855, R2 = 0.732 on a 10-compound subset). RevFEP delivered the highest affinity correlation of any method (Pearson r = +0.662, R2 = 0.438, Spearman p = +0.624, mean absolute error 1.02 kcal/mol across all 36 ligands), resolving potency differences within a narrow 3.5 kcal/mol congeneric window that no other engine could discriminate. We characterize what each engine contributes independently and where RevFEP delivers signals no other engine achieves.