ACS Pharmacology and Translational Science最新文献

Drug-induced liver injury (DILI) remains a challenge in drug development, and interspecies differences in liver toxicity represent a need where comparative analyses may inform preclinical safety study design. In vitro testing for species-specific liver effects, especially in complex models such as microphysiological systems (MPS), may help predict toxicity before advancing from animal to human studies, or derisk spurious findings in preclinical species. This study assessed the utility of the perfusion-based PhysioMimix LC12 MPS as compared to 2D cultures and evaluated species-specific DILI using primary hepatocytes from human, monkey, rat, and dog. Functional, phenotypic, and transcriptional profiles were evaluated for up to 14 days. Also, cells were exposed to species-specific hepatotoxicants such as bosentan (BOS), fialuridine (FIAU), and a common hepatotoxicant for all species, chlorpromazine (CPZ)─in both PhysioMimix LC12 and traditional 2D cultures. Hepatocytes in PhysioMimix LC12 showed more stable albumin and urea production as compared to 2D cultures. Concentration–response studies with CPZ, BOS, and FIAU were performed in 2D; then, repeated (5 × every 2 days) exposures to sub-100 × C_max concentrations were tested in PhysioMimix LC12. Species-specific differences in cellular and molecular effects of the drugs were observed in both models; data from PhysioMimix LC12 were reflective of the expected effects in both animals and humans. Still, variability and low throughput are limitations of MPS for prospective studies of species-specific responses. Overall, this study confirms the utility of liver safety studies using PhysioMimix LC12 and also provides suggestions for experimental designs to overcome the limitations of more complex test systems.

Sickness behaviors are a natural response to inflammation and pathogenic shocks. However, current treatments have limitations, highlighting the need for novel anti-inflammatory agents. Aloifol I, which is a dihydrostilbenoid, was investigated as a potential candidate. Its anti-inflammatory properties were first evaluated in vitro using lipopolysaccharide (LPS)-induced RAW 264.7 macrophage and BV-2 microglial cells, followed by proteomic analysis to elucidate underlying mechanisms. In vivo efficacy was then evaluated in a mouse model of LPS-induced sickness behaviors at 12.5, 25, and 50 mg/kg doses. Central nervous system (CNS) safety was evaluated at 50 mg/kg by assessing the general behavior and motor coordination of mice. Results demonstrated that aloifol I significantly suppressed the LPS-induced IL-6 and TNF-α release in both macrophage and microglia. Proteomic analysis revealed that aloifol I downregulated proteins involved in translation, glycolysis, and cytoskeletal organization while upregulating proteins related to mitochondrial function, stress response, and inflammation resolution, suggesting its multifaceted anti-inflammatory mechanism. In vivo, aloifol I attenuated LPS-induced fever from 38.3 °C to the basal temperature of 36 °C, confirming its antipyretic effect. It also improved LPS-induced locomotor impairments in a dose-dependent manner, reflecting its ability to alleviate inflammation-associated behavioral impairments. Additionally, aloifol I significantly reduced LPS-induced pro-inflammatory cytokine levels of IL-6 and TNF-α in both plasma and brain tissues, suggesting peripheral and central anti-inflammatory effects. Importantly, no adverse effects on motor coordination or general behaviors were observed, supporting a favorable CNS safety profile. These findings collectively highlight the promising therapeutic potential of aloifol I as a potential anti-inflammatory agent for the treatment of inflammation-related sickness conditions.

Gut microbial dysbiosis-induced perturbations in bile acid (BA) metabolism are implicated in metabolic dysfunction–associated steatotic liver disease (MASLD), yet evidence remains largely associative. Using an optimized ex vivo fecal microbiota model, we modeled the metabolism kinetics of conjugated- and primary-BA between MASLD and healthy donors. Enzymes for known BA metabolic reactions were inferred using functional metagenomics. MASLD cultures exhibited impaired deconjugation capacity but preserved downstream primary-BA clearance and demonstrated a substrate-independent shift that favored oxidative metabolism over 7α-dehydroxylation. This was marked by increased formation clearance of 7-keto-deoxycholic acid (175%) and 3-oxo-cholic acid (51.7%) from cholic acid (CA) and 7-keto-lithocholic acid (77.9%) from chenodeoxycholic acid (CDCA). C7-oxidized BA constituted the major proportion of total BA clearance (CA = 56.0%, CDCA = 72.3%) in MASLD cultures. Enrichment of C3- and C7-hydroxysteroid dehydrogenases in MASLD compared to control corroborated the differential secondary BA profiles. Together, microbes catalyzing C7-oxidation warrants further investigation as potential pharmacological targets of MASLD.

Glioblastoma multiforme (GBM) is an aggressive brain tumor with limited therapeutic options and a poor prognosis. We developed hybrid lipid-polymer nanoparticles (HLPNs) functionalized with tumor-homing C-end Rule peptide LinTT1 (LinTT1-HLPNs) to improve the GBM targeting. In vitro studies demonstrated that LinTT1-HLPNs bind selectively to GBM cells and significantly improved the cytotoxicity of the loaded temozolomide (TMZ) (LinTT1-HLPNs@TMZ) compared to that of the free drug. In vivo, intravenous injection of HLPNs in both infiltrative and noninfiltrative GBM murine models had an enhanced accumulation of TMZ in the tumor area, thus endorsing the selective targeting and tissue penetration of LinTT1-HLPNs. This nanoplatform combines the advantages of hybrid lipid–polymer nanoparticles with a GBM-specific targeting strategy, thus providing an improved drug delivery and therapeutic effect by a multistep targeting approach, which addresses the key challenge of GBM.

The limited translatability of animal models can be significantly amplified by integration of Artificial Intelligence (AI) and Machine Learning (ML). This Viewpoint represents a fresh paradigm in pharmacology and translational science, one that accelerates hypothesis testing, reduces resource burden, and improves clinical predictability. By aligning computational precision with experimental rigor, this integrated approach provides more ethical, scalable, and personalized cancer therapeutics.

Lung inflammation is a hallmark of several respiratory diseases and is frequently driven by proinflammatory cytokines such as interleukin-17A (IL-17A). IL-17A plays a critical role in amplifying inflammatory cascades, contributing to airway remodeling and tissue damage. This study investigated the therapeutic potential of ferulic acid (FA), a natural polyphenol with known antioxidant and anti-inflammatory properties, in mitigating recombinant IL-17A (rmIL-17A)-induced lung inflammation in BALB/c mice. Mice were intranasally exposed to rmIL-17A for seven consecutive days, while FA was administered orally from day 4 to day 7. FA treatment significantly downregulated IL-17A-mediated signaling pathways and restored the redox balance disrupted by rmIL-17A exposure. Additionally, FA markedly reduced proinflammatory cytokine levels, inflammatory cell infiltration, mast cell activity, mucus hypersecretion, and fibrosis in the lung tissue. Importantly, FA also decreased the expression of CD38 and restored CD206 expression, indicating a phenotypic shift toward anti-inflammatory macrophage polarization. Interestingly, FA also restored the expression level of occludin in the lungs of mice exposed to rmIL-17A. Overall, these findings demonstrate that FA effectively attenuates IL-17A-induced lung inflammation by modulating oxidative stress, cytokine production, and inflammatory cell responses. These outcomes show the potential of FA as a promising therapeutic option for regulating IL-17A-driven pulmonary inflammatory conditions.

Dysregulated immune responses to domestic allergens are underlying events in atopic dermatitis (AD), an inflammatory disease of humans and domestic companion animals characterized by itching and eczema. The house dust mite (HDM) allergome, notably the cysteine protease group 1 allergens, is an important trigger of AD. This protease activity is implicated in innate mechanisms which both initiate and reinforce allergic sensitization, prompting interest in the design of protease inhibitors as a novel allergy therapy. We examined pyruvamide chemotype protease inhibitors on intracellular reactive oxidant species (ROS) production induced by HDM allergen extracts in HaCaT keratinocytes and identified promising topical and orally bioavailable candidates. We then explored the wider signaling network affected by this allergen inhibition in keratinocytes and airway epithelial cells (AECs). Optimized pyruvamides with different properties (viz. neutral vs charged, cell-impermeant molecules) inhibited ROS generation evoked by HDM allergen extract, but biochemical potency against Der p 1 per se was not a direct indicator of cellular efficacy. ROS production was stimulated by Der p 1 through canonical activation of protease-activated receptor 1 which propagated the activation signal through a network involving ATP, purinoceptors, transient receptor potential channels, nitric oxide formation, and the ligation of Toll-like receptor (TLR) 4 and TLR 1/2 heterodimers by endogenous activators. These data reveal that inhibition of a single allergen in HDM allergenic extracts prevents an extensive signaling network which is coupled to the redox control of keratinocytes and AECs. These data underscore the exciting possibility that allergic responses can be inhibited at source.

Prostate cancer (PCa) is the most common cancer and the second leading cause of death among men worldwide. Significant progress has been made in managing PCa by targeting the prostate-specific membrane antigen (PSMA), which holds great promise for improving the accuracy and effectiveness of diagnosis. Previously, we reported a high-affinity glutamate–urea–lysine (EuK)-based PSMA-targeting tracer, BQ0413, containing the maE₃ chelator for labeling with technetium-99m for single-photon emission tomography diagnostic imaging. BQ0413 demonstrated efficient tumor targeting in PCa patients with concomitant elevated activity retention in the kidneys, which is typical for EuK-based PSMA-targeting tracers. We hypothesized that a decrease in the tracer’s total negative charge, by substituting negatively charged glutamate residues in the maE₃ chelator with polar neutral serine, could decrease activity retention in the kidneys. The present study aimed to evaluate the tumor targeting and biodistribution profile of two new PSMA-targeting tracers, BQ0500 (maESE) and BQ0501 (maS₃), in comparison to BQ0413 (maE₃). Conjugates were successfully radiolabeled with technetium-99m and characterized in vitro and in vivo. [^99mTc]Tc-BQ0500 and [^99mTc]Tc-BQ0501 demonstrated PSMA-specific binding to PC3-pip cells with picomolar affinity; however, the affinity was 3–5-fold compromised in comparison with the reference [^99mTc]Tc-BQ0413. Full replacement of glutamate residues by serines in [^99mTc]Tc-BQ0501 resulted in an improved overall clearance from normal organs with a moderately increased accumulation of activity in the gastrointestinal tract. [^99mTc]Tc-BQ0501 demonstrated efficient tumor targeting and improved tumor-to-background ratios. These results suggest that chelator modifications, such as charge alteration, play a critical role in improving tumor targeting and pharmacokinetics for EuK-based PSMA-targeting tracers.

Selective chemical probes are essential for dissecting biological pathways and advancing drug discovery, yet developing high-quality probes for targets such as the aldehyde dehydrogenase (ALDH) family remains challenging. Here, we present a novel integrated approach combining experimental quantitative high-throughput screening (qHTS) with advanced machine learning (ML) and pharmacophore (PH4) modeling to rapidly identify selective inhibitors across multiple ALDH isoforms. We screened ∼13,000 annotated compounds against biochemical and cellular assays. We then utilized the data set to build ML and PH4 models to virtually screen a larger set of 174,000 compounds to enhance the chemical diversity of hits. This approach led to the expansion of chemically diverse isoform-selective inhibitors that are potent in both biochemical and cell-based assays. Validation through cellular target engagement assays further confirmed the selective activity of these compounds, leading to the discovery of ALDH1A2, ALDH1A3, ALDH2, and ALDH3A1 chemical probe candidates. Remarkably, this was achieved by employing just a single iteration of quantitative structure–activity relationship (QSAR) and PH4 modeling for virtual screening. This combined in vitro and in silico strategy not only enhances the discovery of biologically relevant chemical probe candidates but also significantly expands the chemical diversity accessible for probe development, establishing a new platform for the rapid and resource-efficient identification of chemical probes against the ALDH enzyme family. The data set generated, including hundreds of compounds thoroughly characterized across a spectrum of assays, is publicly available and can serve as a high-quality training set for future research initiatives and probe development efforts.

Antenatal depression, or depression during pregnancy, is a common psychiatric disorder and poses significant risks to both the mother and the fetus. Despite these risks, it is frequently left untreated due to fears of side effects caused by antidepressant medications which cross through the placental barrier. It is therefore desirable to develop formulation strategies to mitigate systemic exposure to psychotropics while maintaining their efficacy. In this work, we develop formulations of sertraline, a common antidepressant, to target delivery to the brain through intranasal administration. Formulation engineering enables successful solubilization of sertraline at high concentrations over months at room temperature. Using mice, we compare sertraline biodistribution following intranasal administration and standard oral administration. Intranasal administration of our candidate formulation provides comparable brain exposure at half the dose compared to oral treatment and lowers the maximum plasma exposure. These findings suggest that intranasal administration may provide selectivity for drug exposure in the central nervous system over systemic exposure.