Search Results (260)

Acute inflammatory disorders, including acute lung injury, acute pancreatitis, ischaemia–reperfusion injury, and sepsis, are major clinical challenges characterised by rapid progression, a characteristic cytokine storm, and high mortality rates. The receptor for advanced glycation end-products (RAGE) serves as a pivotal multi-ligand pattern recognition receptor that integrates PAMPs and DAMPs. Excessive RAGE engagement triggers detrimental signalling cascades, notably NF-κB and MAPKs, which exacerbate hyperinflammation and lead to progressive organ dysfunction. Consequently, the RAGE axis represents a potent therapeutic target for mitigating hyperinflammation and improving clinical outcomes in acute inflammatory disorders. While initial pharmacological efforts focused on synthetic inhibitors and biologics, there is a shifting focus toward bioactive alternatives with high safety profiles. Here, we present recent molecular insights into RAGE-mediated pathogenesis in acute inflammatory disorders and evaluate current therapeutic strategies. Furthermore, we emphatically summarise the bioactive natural products, including terpenoids, flavonoids, alkaloids, and a xanthone, that prevent and treat acute inflammatory disorders by disrupting RAGE–ligand interactions and suppressing downstream oxidative stress and cytokine release. Integrating these molecular mechanisms with the pharmacological profiling of natural RAGE modulators provides a robust foundation for the development of next-generation therapeutic strategies to improve clinical outcomes in acute inflammatory disorders. Full article

Background/Objectives: First-generation CDK4/6 inhibitors (palbociclib, ribociclib, abemaciclib) target the conserved ATP-binding pocket of CDK4 and, despite clinical success, are limited by acquired resistance and insufficient exploration of alternative regulatory sites. This study aimed to identify a putative allosteric small-molecule candidate at the CDK4 αE-helix–Cyclin D1 α1-helix protein–protein interaction (PPI) interface within the CDK4/Cyclin D1/p21 ternary complex using RapidFunnel-AI, a decision-interpretable virtual-screening pipeline. Methods: Starting from 50,000 ChEMBL 33 molecules, the pipeline sequentially applied a Q-Fold/RapidFunnel topological Tanimoto scan based on clinical CDK4/6 inhibitor motifs, fragment-level electronic-property enrichment, ADMET/PAINS filtering, dry Vina-GPU docking, hydration-mediated AutoDock-GPU (Version 1.6) docking, explicit-solvent molecular dynamics, contact-retention analysis, and MM-GBSA energy decomposition. The Q-Fold Thermo-Core surrogate model provided fragment-level enrichment, predicting the HOMO–LUMO gap (R² = 0.93) and isotropic polarizability (R² = 0.98) on QM9. Candidate selection did not rely on the lowest docking or MM-GBSA score alone, but on pose persistence, contact continuity, and energy-component consistency. Results: The workflow reduced the initial library to 43 topologically prioritized candidates, 25 ADMET/PAINS-filtered ligands, and 9 docking-derived complexes for MD validation. Ligand_020 emerged as the only candidate that preserved a persistent binding mode at Site 2 during a 500 ns simulation—an interface engagement reproduced across three independent 500 ns replicates with no full dissociation in any replicate—with a protein Cα RMSD of 2.88 ± 0.32 Å, a ligand heavy-atom RMSD of 3.56 ± 0.28 Å, and a van der Waals-dominated MM-GBSA profile (ΔGbind = −28.23 ± 3.57 kcal/mol). In contrast, palbociclib and ribociclib, forcibly placed at Site 2 as negative controls, lost most initial contacts within 5 ns and tended to detach despite more favorable MM-GBSA values. Conclusions: These results suggest that single-score docking or MM-GBSA ranking can generate false positives at shallow PPI interfaces. By integrating AI-assisted prioritization, multipocket docking, explicit-solvent MD, contact-retention analysis, and energy-component consistency, RapidFunnel-AI nominated Ligand_020 as an experimentally testable putative allosteric hit targeting the CDK4/Cyclin D1 interface, offering a reusable platform for PPI-focused oncological drug discovery. Full article

Recently, there has been great interest in AI-based approaches for de novo design of novel drug candidates. However, the generation of useful lead drug candidate compounds requires more than predicting engagement with the desired protein target. Candidate molecules must also be anchored in the real world of medicinal chemistry for their synthesis and modification as well as satisfying multiple drug development-related criteria. Here, we present Nevermore, an AI target-conditioned, database-grounded workflow for prioritizing candidate ligands from large compound libraries. Nevermore uses a geometry-aware protein–ligand affinity oracle to score target-specific binding and perform sparse integer edits in count-based Morgan fingerprint space. Nevermore then retrieves the most structurally similar molecules from public chemical databases. This design enables multi-objective search over predicted affinity and absorption, distribution, metabolism, excretion, and toxicity (ADMET) proxies while keeping all candidates anchored to valid database compounds. We evaluated Nevermore’s performance across three biologically distinct targets: Menin, a protein-interaction target relevant to leukemia; SARS-CoV-2 M^pro, a viral cysteine protease relevant to antiviral discovery; and epidermal growth factor receptor (EGFR), a kinase-superfamily oncology target with extensive experimentally tested compounds. Nevermore retrieved candidate sets with favorable predicted affinity–property trade-offs. These results support database-grounded fingerprint steering as a practical computational strategy for lead prioritization and for generating testable molecular hypotheses, although the prioritized candidates remain predictions, requiring follow-up experimental validation. Full article

Background: Ferrocene-containing compounds have gained attention in medicinal chemistry due to their unique redox and structural properties. This study investigates ferrocene-based analogues of imatinib and nilotinib to define their binding determinants within the ABL1 kinase domain using an integrated in silico approach, in relation to their previously reported cytotoxic activity. Methods: Ligand geometries were optimized at the B3LYP/def2-TZVP level with D3(BJ) dispersion and SMD solvation. Molecular docking against ABL1 (PDB ID: 2HYY) was performed using Glide SP, validated by re-docking and enrichment screening. Docked poses were refined using MM-GBSA (Prime, VSGB 2.1/OPLS4). The most active compounds (9 and 15a), together with the inactive control 15e, were subjected to three independent 500 ns molecular dynamics simulations (Desmond, OPLS4), followed by trajectory analysis including RMSD, RMSF, radius of gyration, SASA, and polar surface area. Results: Compounds 9 and 15a maintained stable binding within the ATP-binding pocket despite lacking the canonical hinge interaction with Met318, indicating hinge-independent binding. Their binding was mainly driven by interactions with Asp381 (DFG motif) and cation–π contacts with Lys271. In contrast, the compound 15e showed unstable binding, increased conformational flexibility, reduced pocket burial, and loss of key stabilizing interactions. Active compounds also preserved stable P-loop dynamics, with Tyr253 engagement suggesting a role in loop stabilization. Compound 9 exhibited the most constrained and reproducible binding mode among all analogues. Conclusions: Ferrocene-based analogues can sustain stable ABL1 binding via non-classical interaction networks independent of hinge recognition. The clear distinction between active compounds and the inactive analogue 15e supports the robustness of the proposed binding mode and provides a structural basis for their reported cytotoxic activity. These findings support further experimental evaluation of ferrocene-containing scaffolds as potential BCR-ABL1 inhibitors. Full article

The dopamine D₃ receptor (D₃R) has long been considered a secondary target in the treatment of Parkinson’s disease (PD), with therapeutic strategies primarily focused on D₂ receptor–mediated motor control. However, accumulating evidence now supports D₃R as a functionally distinct dopaminergic receptor subtype with specific relevance to non-motor symptom domains and dopaminergic signaling under hypodopaminergic conditions. Recent advances in high-resolution structural biology have elucidated the molecular basis of D₃R/D₂R discrimination, revealing how subtle residue-level and microstructural differences within a conserved G protein–coupled receptor framework shape ligand recognition and receptor activation. In parallel, the emergence of ligand-dependent biased signaling has refined current understanding of D₃R pharmacology. Selected ligands can preferentially engage Gα_i/o-mediated pathways while limiting β-arrestin recruitment and associated regulatory processes, providing a mechanistic rationale for more stable modulation of mesolimbic dopaminergic circuits involved in affective and motivational regulation. Beyond symptomatic modulation, preclinical studies suggest that D₃R signaling may influence neuronal resilience, synaptic plasticity, and adaptive responses to dopaminergic injury; however, such effects remain experimental and have not been demonstrated in clinical PD. This review integrates recent structural, signaling, and functional insights into D₃R biology, with particular emphasis on biased agonism and emerging therapeutic concepts. Although D₃R-targeted strategies do not currently represent disease-modifying interventions, they offer a rational framework for the development of next-generation dopaminergic therapies aimed at improving precision, tolerability, and long-term signaling stability in Parkinson’s disease. Full article

Chronic low-grade inflammation is a hallmark of aging and a major driver of metabolic and degenerative diseases. While systemic immune dysfunction has been widely investigated, the contribution of barrier tissues to persistent inflammatory signaling remains incompletely defined. The oral mucosa represents a uniquely exposed barrier, continuously challenged by microbial, mechanical, and metabolic stressors and characterized by a specialized immune architecture. Here, we synthesize current evidence supporting the oral barrier as an active immunometabolic interface linking local immune activation to systemic inflammatory tone. Spatially organized epithelial, neutrophil, and antigen-presenting cell (APC) compartments coordinate immune responses tightly coupled to metabolic reprogramming, including hypoxia-inducible factor-1α (HIF-1α)-dependent glycolysis and mitochondrial reactive oxygen species (mtROS) production. In parallel, the oral microbiota provides ligands and metabolites such as lipopolysaccharide (LPS), short-chain fatty acids (SCFAs), and succinate, which activate pattern-recognition receptors (PRRs), including toll-like receptors (TLRs) and the NOD-like receptor pyrin domain-containing 3 (NLRP3) inflammasome, thereby sustaining nuclear factor kappa-light-chain-enhancer of activated B cell (NF-κB)-mediated inflammatory signaling. Barrier disruption and dysbiosis promote microbial translocation and persistent innate immune activation, while saliva and gingival crevicular fluid facilitate systemic dissemination of inflammatory mediators. Overall, sustained immunometabolic engagement at the oral barrier emerges as a key driver of chronic low-grade systemic inflammation and a potential therapeutic target in inflammaging. Full article

Toll-like receptor 3 (TLR3) is a double-stranded RNA sensor that plays a dual and context-dependent role in epithelial cancers, promoting either regulated cell death (RCD) or tumor-supportive programs. While TLR3 activation has been widely explored for its capacity to induce apoptosis or necroptosis and enhance antitumor immunity, accumulating evidence indicates that cancer cells can use TLR3 signaling to sustain proliferation, migration, stemness, and therapy resistance. In this review, we provide a comprehensive and mechanistic analysis of TLR3 signaling in epithelial cancers, encompassing canonical and non-canonical modules that regulate cancer cell fate. We examine how TLR3 activation engages interconnected RCD programs, including apoptosis, necroptosis, and immunogenic cell death, and contrast these with pathways driving tumor plasticity and progression. Importantly, we discuss the key determinants governing TLR3 signaling output, including signaling complex composition; ligand origin and delivery; TLR3 subcellular localization; and cancer cell-intrinsic factors such as genetic, epigenetic, and metabolic states. We propose an integrative framework in which TLR3 signaling influences cancer cell fate according to cellular and microenvironmental context. Full article

Background/Objectives: Osteoporosis remains a clinically important metabolic bone disorder with limited bone-forming therapeutic options. SET domain bifurcated protein 1 (SETDB1) is involved in osteogenic epigenetic regulation, but small-molecule discovery guided by SETDB1-associated structural regions remains limited. This study aimed to identify a candidate compound with in silico relevance to a SETDB1-associated ligand-bound pocket and assess its association with early osteogenic readouts. Methods: A computational–experimental workflow was used, including hierarchical molecular docking, MM-GBSA rescoring, ADMET-based prioritization, redocking validation, molecular dynamics simulations, and preliminary in vitro evaluation in MC3T3-E1 cells. Compound 271 (C271) was selected based on structure-based screening results and predicted developability-related properties. Cytocompatibility, alkaline phosphatase (ALP) activity and staining, selected molecular markers, and SETDB1–H3 molecular dynamics behavior were evaluated. Results: Redocking reproduced the reference binding mode, and molecular dynamics simulations indicated that C271 maintained a relatively persistent conformation around the predicted SETDB1-associated pocket. Comparative SETDB1–H3 simulations showed altered H3 dynamics and SETDB1–H3 contact patterns in the C271-containing system. In cell-based assays, C271 showed no appreciable cytotoxicity within the tested concentration range and was associated with increased ALP activity and staining. C271 treatment was accompanied by higher global H3K9me3 and Runx2 levels, whereas SETDB1 protein abundance remained largely unchanged. Conclusions: C271 was identified as a computationally prioritized SETDB1-related candidate compound associated with early osteogenic-associated cellular responses. The evidence supports computational plausibility and cell-level association, but does not establish direct SETDB1 engagement, SETDB1 enzymatic modulation, SETDB1-dependent causality, or late-stage osteogenic maturation/mineralization. Given the single-compound evaluation, further target-engagement, enzymatic, and functional studies are needed. Full article

Voltage-gated ion channels are central regulators of cardiac, neuronal, and skeletal muscle excitability, and their dysfunction underlies a wide spectrum of channelopathies, including arrhythmias and neuromuscular disorders. While conventional ion channel therapeutics typically target a single pore-binding site, emerging evidence supports the therapeutic potential of polypharmacological compounds capable of modulating multiple channel subtypes. ARumenamides represent a novel class of sulfonamide-based ligands originally identified as fenestration-targeting sodium channel modulators; however, their cross-family binding mechanisms and multitarget potential remain incompletely defined. Here, we employed an integrated structure-based computational workflow combining molecular docking, in silico ADMET profiling, and long-timescale (250 ns) molecular dynamics simulations to systematically evaluate 20 ARumenamide derivatives across 15 voltage-gated sodium, calcium, and potassium channel structures. Docking analyses revealed broad multitarget binding profiles, with several compounds exhibiting high predicted affinity across cardiac, neuronal, and skeletal muscle channel isoforms. ADMET predictions demonstrated favorable intestinal absorption and metabolic safety for most candidates, although solubility and mutagenicity liabilities were identified for select derivatives. Detailed molecular dynamics simulations of prioritized compounds (AR-310, AR-769, and AR-946) uncovered site-specific binding behaviors and conformational effects. AR-769 exhibited exceptional stability at both fenestration and central pore sites of Cav1.2, associated with persistent hydrogen-bond networks, reduced protein flexibility, and a well-defined free energy minimum. In contrast, AR-310 and AR-946 displayed selective stability within Nav1.4 fenestrations and the Kv4.3 central pore, respectively, highlighting how subtle chemical features bias binding site preference and dynamic retention. Collectively, these findings establish a structure–dynamics framework for rational design of ARumenamide-based multitarget ion channel modulators. Our results demonstrate that fenestration-focused binding can support sustained ligand engagement without obligatory pore occlusion, offering a mechanistically distinct strategy for developing next-generation polypharmacological therapeutics for cardiac and neuromuscular disorders. Full article

Sialic acids are a diverse class of widely distributed monosaccharides that are engaged in a wide range of biological processes. Sialin, a sialic acid/proton symporter, transports sialic acid across membranes between the lysosomal lumen and cytosol, playing a critical role in sialin metabolism. Taking advantage of recently published experimental structures of sialin, we report here the first computational study that probes the molecular mechanism of ligand transport through sialin, which is yet to be fully understood. In particular, we carry out steered molecular dynamics simulations of the transport of N-acetylneuraminic acid, the most widely spread natural derivative of sialic acids, through sialin with two key glutamate residues (E171 and E175) in various protonation states. The previously proposed model is refined with enriched atomistic details from this study for the cotransport of sialic acid and proton. With additional quantum calculations, our data suggest a possible explanation for why mutation R168A retains most of the transport activities, but R168K does not. Full article

As an emerging tire wear-derived environmental contaminant, 6PPD-quinone (6PPDQ) has raised significant concerns regarding its neurotoxic potential, particularly for children exposed to recycled tire crumb rubber in playgrounds. However, the molecular mechanisms by which 6PPDQ influences neurological disorders such as epilepsy remain poorly understood. In this study, we employed an integrative framework combining network toxicology, bulk analysis of human epileptic brain tissues, Mendelian randomization, and molecular dynamics simulations to elucidate these mechanisms. Our findings, validated through CETSA-WB and SPR, identify 6PPDQ as a direct ligand that binds to and stabilizes neuronal TP53. Through a synergistic double-hit mechanism, 6PPDQ directly engages the TP53 pathway while simultaneously triggering microglial interleukin-6 secretion. These converging pathways lead to the suppression of the master antioxidant regulator Nrf2, resulting in glutathione depletion, excessive reactive oxygen species accumulation, and exacerbated neuronal damage under excitotoxic stress. Experimental validation using glutamate-induced HT22 cell models and microglia–neuron crosstalk systems confirmed that targeting the TP53/Nrf2 axis or scavenging ROS significantly attenuates 6PPDQ-induced neurotoxicity. Our findings highlight critical risks to pediatric neurological health posed by tire-derived contaminants and identify the TP53/Nrf2 axis as a promising therapeutic target. Furthermore, this work provides a robust scientific basis for refining risk assessment frameworks and developing regulatory strategies to mitigate environmental exposure to 6PPDQ. Full article

Compound repurposing is an efficient method to save both time and costs by redirecting previously synthesized small molecules towards new biological targets. In this research, we employ computational methodologies to investigate and assess target engagement of small molecules as tyrosine kinase inhibitors (TKIs). Therefore, compounds TKI.2a, TKI.2b, TKI.6, TKI.16, TKI.19, and TKI.21b identified from our earlier research, undergo assessments of molecular similarity, docking studies, and pharmacophore modeling along with those discovered through database searches. Compounds TKI.2a, TKI.2b, TKI.6, and TKI.19 appear to exhibit multi-target tyrosine kinase inhibitory activities against VEGFR-2 (Vascular Endothelial Growth Factor Receptor), RET (proto-oncogene tyrosine–protein kinase receptor), PDGFRα (Platelet-Derived Growth Factor Receptor alpha), EGFR (Epidermal Growth Factor Receptor), and HER2 (Human Epidermal Receptor) receptors. Pharmacophore models were applied for ligand-based virtual screening using defined parameters to discover candidate compounds that exhibit drug-likeness with FDA (Food and Drug Administration)-approved tyrosine kinase inhibitors. Molecular docking studies identified lead compounds for each biological target based on their overall affinity values and established interactions. Compound ChEMBL2170947 was found to be the most promising candidate for the VEGFR-2 receptor, ChEMBL5019511 for PDGFRα, ChEMBL2216869 for EGFR, and ChEMBL3355044 for HER2. Full article

Biophysical sensing technologies have become central to modern drug discovery because they enable direct, quantitative characterization of ligand–target interactions. In contrast to conventional biochemical and cellular assays that infer binding from downstream functional responses, biophysical methods detect interaction events through measurable physical changes such as refractive index, heat, fluorescence, mass, or protein stability. This review surveys the major classes of biophysical sensors used in drug discovery, including surface-based optical methods, calorimetry, solution-state spectroscopic techniques, mass spectrometry-based approaches, and cellular target engagement assays. For each modality, we outline the measurement principle, the key parameters obtained, and its value across hit identification, hit validation, lead optimization, and mechanism-of-action studies. We also emphasize the growing importance of combining orthogonal methods to improve confidence in binding data, resolve assay artifacts, and strengthen early decision-making. Finally, we discuss how biophysical measurements are increasingly integrated with structural biology and computational analysis to support more predictive and mechanism-driven discovery workflows. Collectively, these technologies provide a richer and more reliable understanding of molecular recognition and thereby improve the progression of drug candidates. Full article

The surface receptor DEC205 (alias CD205, NLDC-145, Ly75) has long been a marker for murine dendritic cells and Langerhans cells and functions as receptor to facilitate antigen uptake. We revisited the tissue expression pattern of DEC205 in mice and revealed expression by endothelial cells (ECs) in the central nervous system. Using the murine brain-derived EC line bEnd.3, we could show that DEC205 serves as an endocytic receptor that directs potential ligands to lysosomal compartments. As for its function in ECs, upon engagement by anti-DEC205 antibodies, DEC205 seems to guide Claudin 5, a component of endothelial junctions, away from the surface of ECs to a LAMP-1⁺, degradative compartment. This opens endothelial junctions, eventually allowing leukocytes to migrate from blood to tissue sites. In aggregate, by regulating the blood–brain barrier, DEC205 in ECs may contribute to the regulation of inflammatory processes in the central nervous system. Full article

Background/Objectives: Immune evasion remains a critical barrier to effective hepatocellular carcinoma (HCC) therapy. Lactate dehydrogenase A (LDHA) drives lactate accumulation and histone lysine lactylation (Kla), reshaping the immunosuppressive microenvironment, while bromodomain-containing protein 4 (BRD4) sustains B7-H3 transcription via super-enhancer occupancy. Despite their synergistic roles in the lactate–Kla–B7-H3 immunosuppressive axis, no dual-target inhibitor simultaneously engaging both proteins has been reported. This study aimed to discover dual LDHA/BRD4 inhibitors from natural product libraries using an integrated AI-driven computational pipeline. Methods: We established a multi-tier virtual screening cascade comprising Lipinski/QED drug-likeness filtration, DiffDock-based AI docking, QuickVina binding energy validation, PLIP interaction profiling, 200 ns all-atom molecular dynamics simulations, MM-GBSA binding free energy calculations, and density functional theory analysis. Natural product libraries from COCONUT and CMNPD databases (84,730 compounds post-filtration) were screened against both targets. Results: High-throughput DiffDock screening identified 11 dual-target hits, from which CNP0038114.1 and CMNPD16582 emerged as prioritized lead candidates. All four protein–ligand complexes maintained structural stability throughout MD simulations, with MM-GBSA binding free energies ranging from −27.24 to −32.45 kcal/mol, predominantly driven by van der Waals interactions. DFT calculations revealed distinct electronic profiles: CNP0038114.1 exhibited a narrow HOMO–LUMO gap (2.718 eV) favoring charge-transfer reactivity, whereas CMNPD16582 displayed a larger gap (4.822 eV), suggesting superior chemical stability. Conclusions: This computational study furnishes two novel natural product leads for targeting the lactate–Kla–B7-H3 immunosuppressive axis in HCC, establishing a generalizable AI-driven workflow for dual-target inhibitor discovery. Full article