ACS Pharmacology and Translational Science最新文献

Prediction of monoclonal antibody (mAb) pharmacokinetics (PK) in drug development remains challenging due to the lack of a standardized method for predicting elimination based on mechanistic pathways. Among the processes implemented in the physiologically based pharmacokinetic (PBPK) models for large molecules, FcRn-mediated recycling constitutes the predominant mechanism influencing the elimination of mAbs. In the present study, we assessed the predictivity of a generic value for the dissociation constant (Kd) for FcRn (Kd_FcRn) in humans, identified based on clinical data, to provide means for mechanism-based PK projections for mAbs in first-in-human (FIH) trials. We compiled a database of digitalized linear PK profiles for 50 mAbs administered intravenously in humans. Subsequently, the database was randomly divided into a training and a test data set, using a 7:3 ratio. For each drug in the training data set, a generic PBPK model was set up in PK-Sim, and a drug-specific Kd_FcRn parameter was estimated through data fitting. The median of estimated drug-specific Kd_FcRn was 1.05 μM and was used for naïve predictions of the PK of the drugs in the test data set. Plasma exposure (AUC) and terminal half-life were accurately predicted for 80% and 60% of the drugs in the test data set, respectively, with a prediction error within the 0.80–1.25-fold range. Additionally, 100% of the test data set showed prediction errors within the 0.50–2.00-fold range for both plasma exposure and half-life. The median of the estimated drug-specific Kd_FcRn determined using the whole database with 50 mAbs was 1.07 μM and was retained after evaluation as a more accurate default Kd_FcRn value. The reported results provide a large database of mAbs PBPK models with estimated Kd_FcRn values using PK-Sim, and a validated default Kd_FcRn value of 1.07 μM to perform naïve predictions of mAbs linear PK in the context of FIH trials.

Fructose-1,6-bisphosphatase (FBPase) is a rate-limiting enzyme in gluconeogenesis, and its inhibition has the potential to improve glucose homeostasis. We characterize Cpd96, a novel inhibitor of FBPase, and demonstrate its multifaceted antidiabetic effects. In vivo, Cpd96 significantly improved glucose tolerance, enhanced insulin sensitivity, and promoted insulin secretion in type 2 diabetic (db/db and KKAy) mice. In vitro, Cpd96 potentiated insulin secretion in MIN6 cells and primary pancreatic islets by facilitating glucose uptake, elevating the ATP/ADP ratio, and activating the cAMP and AMPK/mTORC1/S6K signaling pathways. Notably, the insulinotropic effect of Cpd96 was FBPase-dependent, as it failed to promote insulin secretion in primary islets from β-cell-specific FBPase knockout mice. These findings suggest that Cpd96 improves insulin secretion through the metabolic reprogramming of β-cells and highlight its potential as a novel therapeutic strategy for diabetes treatment.

CD73 generates immunosuppressive adenosine in the tumor microenvironment and is a promising target for cancer immunotherapy. We have designed and systematically studied diverse 2-substituted 7-deazapurine ribonucleoside 5′-O-bisphosphonates bearing a variety of (het)aryl groups at position 6 and discovered their highly potent and selective CD73 inhibition activity. The most active compounds (with single-digit picomolar K_i) contained bicyclic (het)aryl groups at position 6 in combination with chlorine at position 2. Further optimization of pharmacokinetic properties identified inhibitors with low clearance, long half-life, high solubility, and excellent selectivity over CD39 and NTPDase3. They effectively suppressed adenosine formation in MDA-MB-231 cells, rescued CD8⁺ T cell activation, and were nontoxic to human fibroblasts. Overall, their profile compares favorably with AB680, a CD73 inhibitor currently in phase I/II clinical trials.

Vesicular monoamine transporter 2 (VMAT2) is an internal membrane protein found predominantly in the central nervous system that plays an integral role in the transport of biogenic monoamines (e.g., dopamine, serotonin, and norepinephrine) into synaptic vesicles for storage within the neuron. While multiple drugs that inhibit VMAT2 have been approved by the US Food and Drug Administration (FDA) for the treatment of hyperkinetic movement disorders, it has been reported that off-target interaction with VMAT2 may lead to neuropsychiatric consequences. In the present study an in vitro analysis was conducted for 257 chemically diverse compounds, most of which were FDA-approved drugs, to calculate the IC₅₀ values for inhibition of dopamine uptake at the VMAT2. The results of this study revealed that a total of 55 chemicals have strong inhibitory activities on dopamine uptake (IC₅₀ < 1 μM), some of which were not previously reported. Furthermore, 69 chemicals exhibited weak inhibitory activity on dopamine uptake between 1 and 10 μM, while 133 showed minimal to no impact on dopamine uptake (IC₅₀ > 10 μM). The IC₅₀ values and resulting inhibition categories were compared to the reported neurologic adverse events including deliria, Parkinson’s-related symptoms, dyskinesia, and suicidal ideation in the FDA Adverse Event Reporting System (FAERS) and drug labeling; however, no correlation was established between adverse events and VMAT2 inhibition. Additional analysis indicated that many of the compounds that inhibited dopamine uptake at VMAT2 were frequently known to interact with serotonin, dopamine, or adrenergic receptors; therefore, it is possible that a synergistic interaction between VMAT2 and one or more additional targets may be responsible for previously reported neurological adverse events.

Estrogen-related receptors (ERRs) are orphan nuclear receptors critical to the regulation of energy metabolism, mitochondrial biogenesis, and tissue-specific transcriptional programs. This review provides a comprehensive structural analysis of ERR isoforms (ERRα, ERRβ, and ERRγ), emphasizing insights from X-ray crystallography and NMR studies. We discuss the ligand-binding domains (LBDs), coactivator and corepressor interactions, and the molecular mechanisms underlying ligand-induced agonism or antagonism. Structural comparisons with estrogen receptors (ERs) reveal key amino acid determinants for ligand selectivity and functional activity. Furthermore, we highlight the development of isoform-selective synthetic ligands, including inverse agonists such as GSK5182, DN200434, and DN201000, with therapeutic potential in metabolic, neurodegenerative, and oncologic diseases. This synthesis of structural data provides a framework for rational drug design targeting ERRs, supporting the development of selective modulators to manipulate ERR signaling in a tissue- and disease-specific manner.

Acanthamoeba keratitis is a rare, vision-threatening corneal infection that remains difficult to diagnose and treat, with therapy often extending for many months. Despite recent advances, the management of Acanthamoeba keratitis still depends largely on empirical regimens combining biguanides, diamidines, and azoles. Outcomes vary widely, reflecting differences in pathogen virulence, drug penetration, host response, and timing of diagnosis. It is proposed that digital-twin technology offers a powerful new framework for studying and managing this disease. Digital twin is a data-driven computational approach that creates continuously updating virtual replicas of biological systems. By integrating multimodal clinical, imaging, and molecular data, digital twins could simulate corneal infection dynamics, drug diffusion, and cyst reactivation, providing clinicians with predictive insight rather than retrospective interpretation. Here, it is discussed how digital-twin models could be constructed for Acanthamoeba keratitis, challenges to implementation, and implications for precision ophthalmology.

Combining bioactivity data of assays against the same target, which are obtained from different sources, was recently shown to lead to considerable noise for training data sets of machine learning (ML) models. In this Viewpoint, we address the profound impact originating from often overlooked changes to an assay protocol relating to the buffer composition and experimental setup. We cover two examples of protein targets that undergo conformational changes driven by extrinsic factors: enzymes as catalytically active proteins, and viral surface proteins as structural targets. We discuss strategies to tackle this challenge for the case of enzyme inhibitors/binders, the utility of models based on deep learning (DL), and current limitations of computational studies assessing protein–ligand interactions. In an interview with an expert in the field of large language models (LLMs) and agentic AI, we explore how the latest developments in these areas can be leveraged to support drug discovery efforts.

Selective α7 nicotinic acetylcholine receptors (α7 nAChRs) have emerged as therapeutic targets for managing various pain conditions, including inflammatory pain. Activation of α7 nAChRs by selective agonists has been shown to exert both antinociceptive and anti-inflammatory effects. In this study, we investigate the pharmacological effects of 3-(4-Hydroxyphenyl-1,2,3-triazol-1-yl)quinuclidine (QND8), a selective and potent α7 nAChR agonist, in a murine model of carrageenan-induced inflammatory pain and evaluated its central nervous system (CNS) safety profile. QND8 significantly alleviated thermal and mechanical hyperalgesia at doses of 1, 3, and 10 mg/kg, and reduced carrageenan-induced paw edema at doses of 10 mg/kg. Importantly, QND8 exhibited these effects without impairing motor coordination and general behaviors, as demonstrated by the rotarod test and automated home cage behavioral analysis. These findings highlight QND8 as a promising preclinical analgesic candidate with anti-inflammatory efficacy and a favorable CNS safety profile. Computational modeling further revealed a stable and high-affinity binding of QND8 within the orthosteric site of α7 nAChR, consistent with its selective agonist activity. The results support further development of QND8 as a selective α7 nAChR-targeting therapeutic for inflammatory pain.

Antibiotics inhibit bacterial reproduction by blocking cell wall synthesis, protein synthesis, and nucleic acid synthesis as well as altering the cell membrane. Bacteria live in hosts like normal flora. However, they can become pathogenic depending on the pathogen’s resistance and the host’s susceptibility. A significant gap exists in understanding the off-target toxicity of antibiotics, particularly their unintended interactions with the host nucleic acid machinery. Addressing this is essential for an effective treatment. This review highlights evidence of antibiotics that off-target host RNA, a less-explored but clinically significant phenomenon. The limitations of conventional design within the 3Rs principle are also explored. Evidence from the literature suggests exploiting natural compounds for antibiotics due to their low off-target toxicity. The clinical utility and role of computational tools in speeding up the identification of natural analogues to existing antibiotics are highlighted. The article proposes leveraging natural compounds to mitigate off-target toxicity and to intervene in drug-induced toxicity. Additionally, this emphasizes the importance of interdisciplinary computational methods for identifying analogues. Structural and functional features are prioritized in high-throughput screening to reduce off-target effects, offering a promising approach to drug development.

Toll-like receptors (TLR) 7 and 8 are pattern recognition receptors expressed in immune cells, such as dendritic cells (DC) and macrophages, that respond to viral and bacterial infections. TLR7/8 activation triggers a pro-inflammatory immune cascade that leads to T cell and NK cell activation. Hence, synthetic imidazoquinoline-structured TLR7/8 agonists were developed and demonstrated as potent immunotherapy candidates for cancer and as infectious disease vaccine adjuvants. However, whether antagonizing TLR7/8 can induce the opposite effect, which is to produce anti-inflammatory cytokines and induce immunosuppressive cellular phenotypes, is a gap in our knowledge. In this study, we investigated the immunosuppressive efficacy of a novel TLR7/8 antagonist (termed “621”) using cellular and animal models of inflammation. The potent TLR7/8 agonist 558 was employed as a control group to contrast the underlying immune mechanisms induced by TLR7/8 antagonist 621. Using mouse DC assays, we found that 621 was a potent inducer of the anti-inflammatory cytokine IL-10 without triggering pro-inflammatory TNF production. When administered systemically, 621-treated mice showed an increased serum IL-10 and decreased serum TNF. 621-treated mice also showed increased frequencies of regulatory T cells (Treg) and M2 macrophages when challenged with immunostimulants such as TLR4 agonist lipopolysaccharide (LPS) or the canonical TLR7/8 agonist resiquimod (RESQ). Further, 621 therapy mitigated the DSS-colitis model by reducing colon pro-inflammatory cytokines and increasing splenic Tregs. Combined, our data suggest that 621 can facilitate robust anti-inflammatory and immunosuppressive immune responses and therefore can be applied as a novel therapy for inflammatory diseases.