Search Results (161)

Supramolecular inclusion complexes are widely used in drug delivery and other fields, with the advantages of controllable structures, high stability, excellent biocompatibility, and the ability to improve drug solubility and achieve controlled release. However, traditional screening methods rely on experimental trial and error, which suffer from long cycles, high costs, and low throughput, limiting research and development efficiency. In recent years, the development of artificial intelligence has provided new solutions for the screening of inclusion complexes. This paper systematically reviewed the core technological system of AI in the screening of inclusion complexes, focusing on two aspects: prediction and optimization of key properties and rational design of host molecules, summarizing their specific application progress. At the same time, we analyzed the current core challenges, including data scarcity, insufficient model interpretability, and limited generalization capabilities, and propose future development directions such as building standardized databases, integrating physicochemical principles (e.g., molecular mechanics and thermodynamics), and establishing closed-loop research and development platforms. This review aims to provide a systematic reference for the in-depth application of artificial intelligence in the field of supramolecular inclusion complexes. Full article

Primary open-angle glaucoma (POAG) is a leading cause of irreversible blindness driven by elevated intraocular pressure from compromised aqueous outflow. While genome-wide association studies have identified numerous risk loci, specific candidate proteins and their cellular mechanisms remain elusive. We employed a multi-omics framework integrating UK Biobank plasma proteomics (N = 53,022) and large-scale POAG GWAS summary statistics. We performed a Proteome-Wide Association Study, Mendelian Randomization, and Bayesian colocalization to infer causality. Identified candidates were mapped to human and mouse ocular scRNA-seq atlases to characterize cell-type specificity, followed by druggability assessments. We prioritized five putative causal proteins, with SEL1L and TFPI demonstrating the strongest evidence. Cross-species scRNA-seq revealed that SEL1L and SERPINF1 are robustly expressed in the trabecular meshwork (TM), particularly the juxtacanalicular tissue, implicating them in outflow resistance. Conversely, TFPI and SLC9A3R2 localize to Schlemm’s canal endothelium, suggesting a role in modulating barrier function. Pathway analyses highlighted endoplasmic reticulum protein processing and coagulation cascades. This study maps putative causal POAG proteins to conventional outflow pathway cells, highlighting SEL1L as a novel target for TM homeostasis and TFPI for drug repurposing, thereby providing data-driven hypotheses to facilitate precision glaucoma therapeutics. Full article

Background/Objectives: Due to the widespread problem of antimicrobial resistance (AMR), there is an urgent need to identify new antibacterial targets that act through mechanisms distinct from those of existing antibiotics. One of these targets is the essential cell division protein FtsQ, which is a central hub of the Gram-negative divisome, but the druggability of its extensive protein–protein interaction (PPI) interfaces remains poorly defined. Here, we present a comprehensive structure-based in silico characterization of Escherichia coli FtsQ aimed at identifying and prioritizing druggable regions for PPI modulation. Methods: We analyzed E. coli FtsQ in both apo and complexed states (FtsQB, FtsQL, and FtsQBL) using a combination of pocket-mapping tools (FTMap and SiteMap), evolutionary conservation analysis (ConSurf), and structure property assessment (BLAST, ProBiS) to map and evaluate potential binding pockets of FtsQ protein. Results: Eight potential binding sites were predicted across the β and POTRA domains of FtsQ. One previously unreported site within the POTRA domain was prioritized as a candidate site, characterized by favorable druggability scores, strong evolutionary conservation, and a putative role in the FtsQ–FtsW/FtsN/FtsI interaction network. In contrast, two highly conserved sites at the FtsQ–FtsB/FtsL interaction interface were structurally flat, indicating limited suitability for classical small-molecule binding and greater compatibility with alternative modalities such as macrocycles or peptidomimetics. Conclusions: Although FtsQ lacks deep canonical binding pockets, this study proposes several conserved and potentially tractable regions as candidate sites, supporting its potential as a non-classical but promising antibacterial target for disrupting bacterial cytokinesis. Full article

Cancer has become a major global health threat due to its high incidence and mortality. However, the development of anti-cancer drugs is limited by high costs, long cycles, and low success rates, slowing the progress of new treatments. As a method that simulates human cognitive functions, artificial intelligence (AI) has greatly improved the efficiency of drug development. Machine learning is a core part of AI and supports applications such as natural language processing and computer vision. This paper reviews recent advances in AI for optimizing anti-cancer drug discovery, development, and medication therapy management. First, we highlight the applications of AI in target identification, druggability assessment, drug screening, and repurposing. Second, we detail how AI optimizes drug combination therapy and clinical trial design. Finally, we describe the role of AI in treatment management, including nanoparticle delivery systems, personalized dosing, and adaptive therapy. AI greatly streamlines anti-cancer drug development and provides new directions for precision cancer therapy. Full article

Background: Translational circuit neuroscience delivers many candidate neurons whose manipulation could ameliorate psychiatric symptoms. However, the translation of these cellular targets into molecular targets—proteins selectively expressed in those neurons that could be pharmacologically manipulated for treatment—remains scarce. To what extent such a translation is possible or is actually impeded by a lack of highly cell type-specific expression of druggable proteins is unknown. Methods: We performed combinatorial differential expression analysis for over 7200 putatively druggable genes (Illuminating the Druggable Genome database) on large-scale single-cell RNAseq datasets from mouse and human cortex (Allen Institute Cell Types Database) to identify selectively expressed genes in important cellular candidates: several pyramidal cell types and parvalbumin, somatostatin and VIP interneurons of the prefrontal and anterior cingulate cortex and hippocampus in mice, and the cingulate cortex in humans. Results: We identified dozens of targets, including some with psychiatric relevance and/or suitability to modulate neural activity, like ion channels, GPCRs and transporters. However, none of them were expressed with absolute specificity in any of the analysed target cell types but only stood out in some comparisons, not others. Generally, results depended strongly on selectivity criteria: less conservative approaches (such as moderate p-value adjustment or grouping of contrast cell sets) yielded more targets, whereas the introduction of additional plausible constraints (difference in proportion of expressing cells, beta; absence of expression in contrast cell type) drove numbers towards zero. Generally, interneurons showed more selectively expressed targets in comparison to cells of the same region compared to excitatory ones (intra-regional comparisons), whereas the reverse was found in inter-regional contrasts comparing the same cell type across regions. Conclusions: The lack of high selectivity in the expression of genes encoding druggable targets constitutes a principal biological limit for manipulating cortical neurons of one type, specifically to leverage therapeutic action. While, currently, this conclusion is limited to the investigated neocortical and hippocampal regions, it highlights the need to develop biological heuristics for identifying targets expressed with relative specificity. Full article

Background: Cancer has emerged as the primary cause of death worldwide in recent years. Current cancer treatment strategies require improvement, creating a pressing need for the development of novel therapeutic agents. This study investigated the anticancer effects of a series of newly synthesized tri- and difluoromethylated spiro[5.5]trienone compounds and evaluated the antitumor efficacy of a lead compound, 3s. Methods: The methyl thiazolyl tetrazolium (MTT) assay was used to assess the effect of the trienone compounds on the growth of cancer cells. Cell cycle distribution and intracellular reactive oxygen species (ROS) levels were analyzed by flow cytometry. Protein expression was examined by Western blot. A mouse xenograft model was utilized to test the anticancer effects and toxicity of 3s in vivo. Results: All 21 tri- and difluoromethylated spiro[5.5]trienones exhibited inhibitory effects on the growth of cancer cells. Among them, compound 3s showed the strongest inhibitory effect. It induced cell cycle arrest at the G2/M phase and promoted apoptosis. Mechanistically, 3s activated JNK and ERK signaling and elevated intracellular ROS levels. Furthermore, in a mouse xenograft model, 3s significantly inhibited tumor growth with minimal toxicity. Conclusions: Compound 3s exhibits potent anticancer efficacy both in vitro and in vivo. The discovery of 3s offers new potential for cancer therapy. Full article

The progression of prostate cancer to castration-resistant disease (CRPC) remains a clinical challenge in which oxidative stress intersects with the PI3K/AKT–androgen receptor (AR) axis. Quercetin (QRC) is a redox-active dietary flavonol, yet its mechanistic impact on CRPC is incompletely defined. Here, we tested whether QRC suppresses AR output by directly modulating AKT. C4-2B and 22Rv1 CRPC cell lines were treated with increasing QRC concentrations, with or without enzalutamide (Enz). Proliferation and viability were monitored by IncuCyte imaging and SYTOX Green incorporation. AKT phosphorylation (S473), AR phosphorylation (S210/213), AR abundance and localization, and prostate-specific antigen (PSA) secretion were assessed by immunoblotting, immunofluorescence, and dot blot, respectively. Docking and molecular dynamic simulations were performed to identify and evaluate a putative QRC-binding site on AKT. QRC produced a dose-dependent cytostatic effect (IC₅₀ 24.37 μM in C4-2B; 21.54 μM in 22Rv1) without marked cell death, reduced pAKT(S473) by up to 80%, decreased pAR(S210/213), and diminished nuclear AR and PSA secretion. Simulations suggested a putative druggable allosteric pocket in the AKT1 N-lobe, with G159 emerging as a potential anchor residue. Enz cotreatment with QRC did not produce additive effects, consistent with a model in which QRC acts upstream of ligand-driven AR activation and thereby limits the incremental benefit of AR antagonism under these conditions. These data support QRC as an AKT–AR axis modulator in CRPC and provide a target engagement framework beyond simple ROS scavenging. Full article

Retinal ischemia–reperfusion (I/R) injury results in irreversible vision loss largely through retinal ganglion cell (RGC) death, with ferroptosis being a key mechanism. This study evaluated the therapeutic potential of the ferroptosis inhibitor Liproxstatin-1 (Lip-1) and deciphered its underlying mechanism. Using a mouse retinal I/R model and primary RGC cultures subjected to oxygen–glucose deprivation/reoxygenation (OGD/R), we demonstrated that Lip-1 effectively inhibits ferroptosis. Lip-1 treatment preserved retinal architecture (as assessed by H&E staining and SD-OCT) and partially restored visual function (as measured by electroretinography). Integrated molecular analyses—including immunofluorescence, Western blotting, and RNA sequencing—showed that Lip-1 downregulates early growth response 1 (EGR1), thereby inhibiting p53 and consequently restoring solute carrier family 7 member 11 (xCT) expression. Crucially, lentivirus-mediated EGR1 knockdown attenuated OGD/R-induced ferroptosis, confirming its pivotal role. Our work defines a coherent EGR1–p53–xCT signaling axis driving ferroptosis in retinal I/R injury and identifies Lip-1 as a neuroprotective agent targeting this pathway. These findings establish a druggable ferroptotic cascade and provide a mechanistic rationale for targeting EGR1 in the treatment of ischemic retinopathies. Full article

Background: Polysaccharide-based dynamic hydrogels are promising for wound management due to their biocompatibility, injectability, and tunable biofunctionality. The integration of therapeutic gasotransmitter donors offers a strategy to modulate the wound microenvironment. Objectives: This study aimed to develop an injectable, self-healing carbohydrate hydrogel capable of sustained hydrogen sulfide (H₂S) release for burn wound therapy, and to evaluate its physicochemical properties, in vivo efficacy, and mechanism of action. Methods: A dynamic hydrogel (ACMOD) was fabricated via Schiff-base crosslinking between oxidized dextran (OD) and carboxymethyl chitosan (CMCS), incorporating the H₂S donor 5-(4-hydroxyphenyl)-3H-1,2-dithiole-3-thione (ADT-OH). Rheological and recovery tests characterized its mechanical and self-healing properties. Efficacy and mechanisms were assessed in a rat full-thickness burn model, analyzing wound closure, histology, oxidative stress, macrophage polarization, angiogenesis, and collagen deposition. Results: ACMOD exhibited shear-thinning, rapid self-healing, and strong tissue adherence. Sustained H₂S release from ACMOD significantly accelerated wound closure and improved tissue regeneration compared to controls. Mechanistically, H₂S attenuated oxidative stress, promoted a pro-regenerative M2 macrophage phenotype, enhanced angiogenesis via VEGF upregulation, and fostered organized collagen deposition and extracellular matrix remodeling. Conclusions: This work demonstrates a versatile, carbohydrate-based dynamic hydrogel platform that synergizes polymer network dynamics with bioactive H₂S delivery to effectively promote burn wound healing. The findings underscore the potential of polysaccharide hydrogels with integrated gasotransmitter release for regenerative therapy and biomaterials applications. Full article

β-thalassaemia (β-thal) is part of a group of diseases, the β-hemoglobinopathies, affecting the levels or functionality of the β-globin subunit of hemoglobin, which are the most widespread monogenic diseases throughout the world. The severity of β-thal is determined by different genetic factors, but in the gravest form, affected patients are constrained to a program of blood transfusion and iron chelation regimens for their entire life. Although definitive cures, such as bone marrow transplantation or gene therapy, are now available, they are still far from being applied worldwide. Therefore, there is growing attention towards the use of drugs to cure or ameliorate β-thal disorder. Among all the strategies, pharmacological increase of fetal HbF and/or adult HbA2 can represent an advantageous approach as high levels of both hemoglobins are effective against β-thal. Therefore, the identification of therapeutic targets that can modulate, by the use of drugs, these hemoglobins is increasingly urgent. In this paper, we analyze the effects of the absence of the CCND3 gene, a druggable target associated with HbF and HbA2 levels, in a humanized mouse model of β-thal to assess the impact against the disorder. Upregulation of γ- and δ-globin levels in mice lacking Ccnd3 expression contributes to partial restoration of the α/β balance, with a consequent increase in hemoglobin levels, improvement of iron levels, and reduction of splenomegaly. Moreover, we present data supporting the enhancement of erythropoiesis. Our data indicate the CCND3 gene as a possible target for drugs against β-thal. Full article

Objective: Rare-earth elements are extensively employed across diverse industrial sectors, increasingly raising concerns about their potential health hazards in both occupational and environmental contexts. Samarium oxide (Sm₂O₃), a routinely processed rare-earth product, reproducibly precipitates pulmonary fibrosis in experimental models, yet the molecular circuitry that transduces its fibrogenic signal remains almost entirely unmapped. This study aims to elucidate the role of miR-214-3p in Sm₂O₃-induced pulmonary fibrosis and to investigate its regulatory mechanism at the molecular level. Methods: A murine model of pulmonary fibrosis was established via intratracheal instillation of Sm₂O₃, and histopathological changes were assessed using hematoxylin and eosin (H&E) and Masson’s trichrome staining. RNA sequencing was performed on lung tissues to identify differentially expressed mRNAs. Leveraging our previously generated miRNA landscape of Sm₂O₃-exposed lungs, we subjected the dataset to Gene Ontology and KEGG enrichment analyses, which convergently identified miR-214-3p as the top-ranking candidate regulator of the fibrogenic MAPK axis. The direct targeting of MAP2K3 by miR-214-3p was validated using a dual-luciferase reporter assay. Expression levels of fibrotic markers (α-SMA, Collagen I) and key components of the MAPK signaling pathway (MAP2K3, p-MAPK14, MST1) were quantified in both in vivo and in vitro models using qRT-PCR and Western blotting. Gain- and loss-of-function studies, complemented by rescue assays, were performed in human embryonic lung fibroblasts (HELFs) via transient transfection of miR-214-3p mimics, inhibitors, or MAP2K3-overexpression plasmids. Cell proliferation was evaluated using the EdU assay, and TGF-β1 secretion was measured by ELISA. Results: Sm₂O₃ exposure induced significant pulmonary fibrosis in mice, accompanied by marked downregulation of miR-214-3p and upregulation of MAP2K3 in lung tissues. Overexpression of miR-214-3p or silencing of MAP2K3 effectively suppressed Sm₂O₃-induced fibroblast activation, including reduced cell proliferation, decreased expression of α-SMA and Collagen I, and inhibition of p38 MAPK phosphorylation. Notably, ectopic overexpression of MAP2K3 reversed the protective effects conferred by miR-214-3p, confirming a functional rescue. Conclusions: miR-214-3p directly silences MAP2K3, thereby blunting p38 MAPK-driven fibrogenesis after Sm₂O₃ exposure. Our data unveil a miR-214-3p–MAP2K3–p38 MAPK axis that constitutes a readily druggable target for rare-earth-element-induced pulmonary fibrosis. Full article

Precise drug target discovery is pivotal to mitigating the escalating costs and high attrition rates that characterize pharmaceutical research and development. Given that traditional single-omics methods often fail to elucidate the systemic complexity of human diseases, deep learning (DL)-enabled multi-omics integration has emerged as a transformative frontier. This review systematically summarizes the advancements in DL-driven multi-omics integration for drug target discovery. First, the multi-omics data foundation and integration strategies are delineated, followed by an exploration of the DL architectures utilized for processing such data. Subsequently, the efficacy of DL-driven multi-omics integration is examined regarding the identification of novel disease drivers, prediction of synthetic lethality interactions, and prioritization of therapeutic targets. Finally, addressing persistent challenges related to data sparsity, model interpretability, and target druggability and validation hurdles, emerging opportunities driven by Generative AI, Large Multimodal Models (LMMs), Explainable AI (XAI), and multidimensional feasibility assessment frameworks are discussed in the context of advancing precision medicine. Full article

Background: Pyroptosis, a pro-inflammatory programmed cell death process, is a key player in tumor biology, including in triple-negative breast cancer (TNBC). Inhibiting G9a has been proven to exert anticancer effects; however, the molecular mechanism of the effects remains unclear. The study aimed to illustrate whether inhibiting G9a can suppress the process of TNBC cells by promoting pyroptosis and investigate the underlying mechanisms. Methods: MCF-10A, MDA-MB-231 and SUM159PT cell lines were used for in vitro study. CCK8 and EdU staining assay were used to examine the cell proliferation, and flow cytometry assay was performed to evaluate cell death. Inflammatory factors were measured by ELISA kits. The mRNA and protein expression levels were analyzed by qRT-PCR, Western blot, and immunofluorescence staining. Transmission electron microscopy was used to observe the morphological changes in cells. Results: We found that knockdown of G9a suppressed the growth and the abilities of invasion and migration, induced pyroptosis, and increased the expression of RIG-I, p-STAT1, and GSDME of TNBC. Furthermore, a RIG-I inhibition Cyclo (Phe-Pro) partially rescued the activation of pyroptosis enhanced by knockdown of G9a. Conclusions: These findings indicate that inhibiting the function of G9a induces pyroptosis in TNBC cells by the RIG-1/STAT1/GSDME pathway, which provides a new therapeutic target for TNBC treatment. Full article

Alginate-based hydrogels, derived from brown seaweed, represent biocompatible and biodegradable materials whose properties are systematically controlled through molecular structure (M/G composition), crosslinking strategy, and compositional modification. This review synthesizes recent advances in alginate hydrogel design, encompassing fundamental structural properties, three primary crosslinking approaches—ionic coordination with divalent cations (Ca²⁺, Ba²⁺, Sr²⁺), covalent chemical linkages, and hybrid multi-crosslinking systems—and strategic modification strategies including chemical derivatization, polymer blending, and nanoparticle incorporation. These modifications address inherent limitations of native alginate, namely insufficient mechanical strength and biological inertness, thereby expanding applicability. The review examines applications across biomedical domains (drug delivery, tissue engineering, wound healing), environmental remediation, food industry systems, and emerging technologies including flexible electronics and soft robotics. Advanced fabrication techniques—3D/4D printing, microfluidics, and electrospinning—enable improved architectural control. Current evidence from preclinical and clinical studies demonstrates feasibility in specific applications, while important challenges persist, including predictable degradation kinetics, mechanical property optimization, standardization of characterization protocols, regulatory compliance, and manufacturing scalability. This review aims to provide a systematic assessment of alginate-based hydrogel development and identify areas requiring further investigation to advance clinical translation. Full article

Background/Objectives: Tuberculosis (TB) remains a major global health threat. Current administration methods for anti-TB drugs, including oral or intravenous, suffer from systemic side effects, low lung distribution, and poor patient compliance. Dry powder inhalers (DPIs) offer a promising alternative. This study investigates the aerodynamic performance of co-spray-dried DPIs containing rifampin or pyrazinamide and amino acids by using machine learning. Methods: Firstly, 72 formulations were prepared by varying drug-amino acid combinations, molar ratios, and spray-drying parameters. Subsequently, the aerodynamic performance of all 72 formulations was evaluated using a Next Generation Impactor, and the solid-state characterizations of optimal DPIs were carried out. Finally, four machine learning (ML) models were successfully developed and were utilized to predict the fine particle dose (FPD), FPF, MMAD, and geometric standard deviation (GSD) of DPIs based on the high-quality in-house data above. Results: Key results showed that the aerodynamic performance of DPIs was highly dependent on the specific drug-amino acid combination, with rifampin-L-lysine acetate and pyrazinamide-L-leucine formulations achieving the highest fine particle fraction (FPF, 73.37%, 87.74%) and optimal mass median aerodynamic diameter (MMAD, 2.59 µm, 1.88 µm). Notably, XGBoost (v3.1.3) exhibited the best predictive performance, with R² values ranging from 0.894 to 0.991 in the testing set for the four prediction tasks. Meanwhile, SHapley Additive exPlanations (v0.50.0) was used for model interpretability analysis. The molecular weights and LogP of the drug and amino acid were identified as two of the most important features affecting the prediction of FPD, FPF, MMAD, and GSD. Conclusions: This work demonstrates the feasibility of ML in accelerating the development of inhalable spray-dried anti-TB drugs by enabling the prediction of DPI formulations. Full article