Search Results (570)

Atherosclerosis remains the principal underlying cause of myocardial infarction, ischemic stroke and peripheral artery disease, and its progression reflects a complex interplay between lipid accumulation, endothelial dysfunction, chronic vascular inflammation and maladaptive remodeling of the arterial wall. The Notch signaling pathway, an evolutionarily conserved juxtacrine communication system, has emerged as a central regulator of every cell type implicated in atherogenesis, including endothelial cells, vascular smooth muscle cells, monocytes/macrophages and T lymphocytes. Depending on the receptor–ligand pairing, the hemodynamic context and the cellular compartment involved, Notch signaling can be either atheroprotective or atherogenic, a duality that has complicated efforts to translate mechanistic insight into therapy. This review summarizes current knowledge of the molecular architecture of the Notch pathway in the vasculature, dissects its cell type-specific and stage-specific contributions to atherosclerotic plaque initiation, progression, calcification and destabilization, and critically appraises pharmacological strategies designed to modulate Notch activity, including γ-secretase inhibitors, ligand- and receptor-directed monoclonal antibodies, soluble decoy receptors, microRNA-based approaches and drug repurposing strategies such as statins. Particular attention is paid to the cardiovascular toxicities that have emerged from oncology trials of Notch pathway inhibitors, which illustrate both the pharmacological tractability and the narrow therapeutic window of this pathway. We conclude that Notch-directed therapy for atherosclerosis is mechanistically well justified but will require cell type-selective and context-selective delivery strategies to be clinically viable. Full article

Conventional oral and injectable drug administration still struggles with unstable plasma levels, weak targeting, and considerable systemic toxicity, problems that become especially acute in chronic disease management. Implantable and wearable biomedical devices offer one path around these limits, yet device-only platforms continue to fall short on drug loading, release control, and protection of fragile therapeutics. Integrating nanoparticle-based biomaterials into such devices has therefore moved from a research curiosity to a serious clinical strategy. As a result, understanding the design principles, translational challenges, and clinical potential of these hybrid platforms has become increasingly important. This review provides a comprehensive assessment of four major nanoparticle families—polymeric carriers (PLGA, chitosan, and micelles), lipid-based vehicles (liposomes, SLNs, and NLCs), inorganic systems (gold, mesoporous silica, iron oxide, and calcium phosphate), and hybrid composites—focusing on how their physicochemical properties govern drug encapsulation, release behavior, and tissue compatibility. These classes are then linked to specific implantable formats such as drug-eluting stents, nano-enabled scaffolds, and reservoir depots, and to wearable formats including transdermal patches, microneedle arrays, biosensor-coupled patches, and patient-actuated devices. A dedicated section addresses stimuli-responsive release driven by pH, enzymes, temperature, and electrical or magnetic fields, alongside closed-loop platforms that pair real-time biosensing with on-demand dosing. Surface engineering strategies, ligand targeting, antifouling coatings, antimicrobial layers, and immune-modulating chemistries are also discussed, together with the central translational hurdles: long-term stability, foreign body response, scale-up, sterilization, and regulatory classification of combination products. Finally, the review outlines near-term directions, including AI-driven dosing, 4D bioprinting, biomimetic nanocarriers, gene therapy delivery, and bioresorbable electronics, that together suggest where these hybrid platforms are likely to mature next. Full article

Background: The rapid escalation of multidrug-resistant P. aeruginosa necessitates anti-virulence strategies targeting quorum sensing rather than bacterial survival; however, integrating scaffold repurposing with generative AI to inhibit LasR remains underexplored. Here, we address this gap by combining triazole scaffold mining with transformer-based de novo molecular generation to systematically identify putative LasR inhibitors. Methods: An integrated computational pipeline involving Structure-based inhibitor design using Generative Transformer Architecture, deep learning-assisted GNINA rescoring, density functional theory optimization, and molecular dynamics simulations was employed, followed by MM-GBSA binding free energy estimation. Results: Screening of 2666 triazole derivatives and 19,861 DrugGPT-generated compounds yielded top hits with superior binding affinities (−11.59 to −13.81 kcal/mol) compared to the reference ligand (−8.50 kcal/mol). MD simulations yielded stable protein–ligand complexes with RMSD values of 2.24–3.01 Å, while key interactions involving residues Tyr50, Asp67, and Ser123 were consistently maintained. Binding free energy calculations further confirmed strong thermodynamic stability, with MM-GBSA ΔG_bind values significantly favorable, supporting robust ligand–receptor affinity. Conclusions: Collectively, these findings establish a powerful AI-integrated framework for anti-virulence drug discovery and identify structurally diverse, high-affinity triazole-based and de novo compounds as promising lead candidates for disrupting LasR-mediated quorum sensing in P. aeruginosa. Full article

Cancer remains one of the leading causes of morbidity and mortality worldwide despite advances in molecular oncology and targeted therapeutics. The growing demand for precision medicine has accelerated the development of radiotheranostics, an emerging paradigm that integrates molecular imaging and targeted radionuclide therapy. In parallel, medicinal chemistry continues to generate structurally diverse small-molecule scaffolds capable of modulating key oncogenic pathways. Increasing evidence indicates that certain chemical scaffolds possess intrinsic properties that extend beyond conventional anticancer activity and support their translation into radiotheranostic applications. This review examines major scaffold classes driving contemporary anticancer drug discovery, including thiosemicarbazones, heterocyclic compounds, metal-based agents, hybrid molecules, and multifunctional platforms. Particular attention is given to the structural features governing biological activity, target selectivity, metal coordination, and radiolabeling potential. The review further highlights the mechanistic convergence between scaffold-mediated anticancer effects and radionuclide-induced cytotoxicity, emphasizing shared pathways involving DNA damage, oxidative stress, inhibition of DNA repair, and modulation of oncogenic signaling. Based on these observations, a scaffold-centered framework for radiotheranostic development is proposed, with perspectives on hybrid molecular design, copper-based theranostic systems, and artificial intelligence-assisted ligand discovery. By integrating medicinal chemistry, molecular oncology, and nuclear medicine, this review outlines structural principles that may facilitate the rational design of next-generation precision anticancer agents and radiotheranostic platforms. Full article

Nanostructured drug-delivery materials—liposomes, polymeric nanoparticles, dendrimers, and inorganic carriers—have become central to pharmaceutical strategies for crossing the blood–brain barrier (BBB), where most candidate therapeutics fail to reach their targets. Their biological performance hinges on a coupled chain of vascular transport, BBB translocation, tissue diffusion, cellular uptake, and intracellular release, each of which is shaped by the nanocarrier’s size, surface chemistry, charge, and ligand functionalization. Physiologically based pharmacokinetic (PBPK) models describe this chain mechanistically but are limited by parameter uncertainty, simplified representations of the BBB, and coarse regional resolution. Machine learning (ML) can close these gaps by extracting nonlinear structure–transport–exposure relationships from heterogeneous experimental and clinical datasets. This review examines emerging ML–PBPK hybrid frameworks for predicting the brain biodistribution of nanostructured drug carriers. We compare regression, kernel, and deep learning approaches for parameter inference, model correction, and surrogate modeling; assess strategies for feature selection, uncertainty quantification, and interpretability; and discuss documented failure cases that bound the conditions under which these methods can be trusted. The review closes with recommendations on dataset standardization, software platform selection, and the responsible use of generative AI in pharmaceutical modeling, thus providing guidance for translating nanostructured material design into safer, more effective brain-targeted therapies. Full article

The Short Tandem Repeat 3D Structure Database (STR3SD) is a web-based database that provides a comprehensive resource for structural biology research of short tandem repeats (STRs) in cancers and neurodegenerative diseases. STR3SD contains three-dimensional (3D) structures of STRs surveyed from literature. The data are organized into three main categories, including 3D structures of nucleic acids only, nucleic acids–protein complexes, and nucleic acids–ligand complexes. Under these categories, each entry is annotated with repeat type, molecular type (DNA or RNA), sequence, PDB ID, structural component, ligand name, structural determination method, experimental conditions (temperature, pH, and ion), PubMed ID, and interactive 3D structure view. The database is built on direct literature investigation by human experts and serves as a crucial tool for studying structures and functions of STRs in cancers and neurodegenerative diseases, supporting research on structural polymorphisms and pathogenic mechanisms of STRs, and facilitating drug design targeting STRs for disease therapy. Full article

Steroid sulfatase (STS) plays a crucial role in intratumoral estrogen biosynthesis and represents an attractive therapeutic target in estrogen receptor-positive breast cancer. In this study, a new series of potential STS inhibitors based on the quinone methide oxime scaffold, precisely 2-(4-hydroxyiminocyclohexa-2,5-dien-1-ylidene)-2-phenylacetonitrile framework, were designed and evaluated using an integrated in silico approach. A virtual library comprising 216 compounds (including syn/anti isomers) was screened by molecular docking against the human STS crystal structure (PDB ID: 8EG3). The binding affinities ranged from −7.077 to −9.726 kcal·mol⁻¹; however, only the best-performing compound 45-syn showed values comparable to those of the reference ligands. The top-ranked compound (45-syn) exhibited favorable interactions within the catalytic site, including polar contacts near the FGly–Ca²⁺ region and extensive hydrophobic and π–π interactions in the adjacent pocket. Structure–binding relationship analysis highlighted the importance of electron-withdrawing substituents at R¹ and aromatic moieties at R² for enhanced binding. Molecular dynamics simulations confirmed the stability of ligand–STS complexes and demonstrated reduced flexibility compared to the apo form. Additionally, in silico ADMET predictions indicated generally favorable drug-like profiles for selected candidates. Overall, the results highlight computationally prioritized scaffolds that merit further synthesis and biological evaluation as potential STS inhibitors. Full article

Background/Objectives: Protein kinases represent major therapeutic targets because dysregulation of their phosphorylation activity is associated with several diseases, including cancer, diabetes, and inflammatory disorders. Thus, many researchers in the pharmaceutical filed are making significant effort to design potent new protein kinase inhibitors (PKIs) as potential drugs. In this context, we aimed to identify new alternatives by exploiting the chemical space defined by ligands of the nucleotide-binding protein family for the discovery of novel protein kinase inhibitors. Protein kinases bind the nucleotide adenosine triphosphate (ATP) and belong to the nucleotide-binding protein group. Methods: All ligands of the nucleotide-binding protein family, excluding known kinase inhibitors, that were identified in the ChEMBL database were used in a structure-based virtual screening approach. From this set, we aimed to identify novel nucleotide-binding protein inhibitors (NBPIs) as novel kinase inhibitors. A total of 19,709 NBPI compounds that were dissimilar to known PKIs were docked on five protein kinases, and the 200 best scoring docking poses were retained for potential purchase. Results: Only 25 compounds were commercially available in stock and were evaluated experimentally on a panel of 10 diverse protein kinases. Three NBPI compounds, one of which had originally been identified as active against the ATP-binding cassette transporter ABCG2, were identified as Haspin kinase inhibitors with micromolar activity. Conclusions: This study presents an efficient computational approach to identifying novel kinase inhibitors from a database of ligands of the nucleotide-binding protein family, and the protocol could be applied to other protein target families. Full article

Graphene oxide (GO)-based nanomaterials functionalized with targeting ligands are promising platforms for selective cancer drug delivery. Among relevant targets, integrin α_Vβ₃ is a highly overexpressed receptor in several solid tumors and is commonly targeted using cyclic Arg-Gly-Asp (cRGD) peptides. However, the molecular details governing the interaction between cRGD-functionalized GO dots and integrins remain poorly understood. In this work, all-atom molecular dynamics simulations are employed to investigate the interaction between integrin α_Vβ₃ and a nanocarrier composed of a GO dot coated with polyethylene glycol (PEG) and functionalized with cRGD ligands. Multiple 1 μs simulation replicas are used to characterize both specific ligand recognition and non-specific nanocarrier/receptor interactions. The simulations show that cRGD binding within the integrin-binding pocket is stable, indicating that the nanocarrier does not impair receptor recognition. Beyond cRGD-mediated binding, both PEG-cRGD chains and GO itself establish additional contacts with the protein, whose nature and distribution are modulated by the relative orientation of the GO plane. Overall, the structural dynamics of integrin α_Vβ₃ remains preserved upon nanocarrier binding. These findings provide atomistic insights into the interplay between ligand-mediated and multivalent surface-mediated interactions of GO-based nanocarriers with integrins for the rational design of selective nanocarriers for cancer therapy. Full article

The voltage-gated sodium channel Nav1.7 is a strongly validated target for the development of novel, non-opioid analgesics due to its genetic link to pain signaling. To accelerate the discovery of safe Nav1.7 modulators, this study outlines an integrated computational pipeline to repurpose FDA-approved drugs. A structurally complete model of the Nav1.7 central pore was generated via homology modeling from a high-resolution cryo-EM structure (PDB: 7W9K) to ensure a physically consistent model suitable for dynamic simulations. We conducted a structure-based virtual screening of 2296 FDA-approved compounds, identifying four promising candidates (DB04868, DB00941, DB01419, and DB15982) with strong predicted affinities ranging from −11.38 to −12.57 kcal/mol. Interaction fingerprinting revealed that binding is predominantly driven by hydrophobic contacts with conserved pore-lining residues, including Phe1503, Leu1010, and Ile1500. To validate these static predictions, the top protein–ligand complexes were subjected to single-replica 250 ns molecular dynamics (MD) simulations. Comprehensive trajectory analyses, including RMSD, RMSF, and principal component analysis, revealed a notable discrepancy between static docking scores and dynamic stability. The highest-scoring docking candidate, DB04868, exhibited substantial conformational flexibility and reduced stabilization under simulated physiological conditions. Conversely, DB01419, despite a lower initial docking rank, demonstrated the highest structural stability across all metrics and uniquely formed intermittent stabilizing hydrogen bonds. These findings underscore the value of post-docking MD validation in computational drug discovery and nominate DB01419 and DB15982 as candidate scaffolds that warrant subsequent experimental validation, including electrophysiological characterization and Nav-isoform selectivity profiling. We emphasize that these are computational predictions: in silico binding stability is not equivalent to functional inhibition of Nav1.7 currents, and the lead designations reported here remain hypothesis-generating until confirmed by patch-clamp and biochemical assays. Full article

Objectives: Thiocarbohydrazones represent an important class of Schiff base derivatives with versatile chemical and biological properties. Methods: Herein, we present a combined in silico spectroscopic and molecular docking investigation of N′-benzylidenehydrazinecarbothiohydrazide (1). Results: Conformational docking studies were conducted against cathepsin B, acetylcholinesterase, HER2, protein kinase C, and protein kinase A. The compound displayed favorable binding affinities and key interactions within the catalytic sites of all targets, with the strongest predicted binding observed for acetylcholinesterase. Notably, all conformers exhibited higher affinity for protein kinase C than the reference inhibitor balanol, and hydroxylation led to an approximately 10% enhancement in docking performance. Density functional theory (DFT) calculations were employed to analyze vibrational properties, and IR and Raman spectra were computed to elucidate structural features and conformational behavior. Conclusions: The integrated spectroscopic and docking analyses provide mechanistic insights into ligand–target interactions and support rational drug design. These findings identify thiocarbohydrazone derivatives as promising multi-target candidates for the development of enzyme inhibitors relevant to neurodegenerative, oncological, and inflammatory diseases. Full article

Precise site-specific ligand design remains a major challenge in structure-based drug discovery. Most existing approaches screen ligands against binding pockets identified from static protein structures obtained by X-ray crystallography, NMR spectroscopy, cryo-electron microscopy, or AlphaFold predictions. However, protein function is governed by a structure–dynamics–function relationship, and ligand screening that does not account for binding competition across the protein surface or the receptor’s dynamic, substrate-dependent conformational states remains incomplete. Substrate-specific conformations are underexplored and may offer new opportunities for selective ligand design, although systematic workflows to identify and exploit such states remain limited. Previously, we showed that collagen alters matrix metalloprotease-1 (MMP1) dynamics and that R405 is a collagen-specific allosteric residue exhibiting strong dynamic correlations with the catalytic site. Here, we present a computational framework for substrate-specific allosteric ligand design using collagen-bound MMP1 as a model system. We characterized the conformational dynamics of free and collagen-bound MMP1 by all-atom molecular dynamics simulations, clustered the resulting conformational ensembles, and identified conformations unique to the collagen-bound state. These conformations were used as structural templates for machine-learning-based generation of approximately 150,000 candidate ligands, which were subsequently docked against both the R405-centered region and all detectable binding pockets on the MMP1 surface. Several candidate ligands were predicted to dock preferentially at the R405 region by at least 0.3 kcal/mol compared with competing surface pockets. Together, these results establish a generalizable computational workflow for identifying candidate ligands predicted to preferentially dock to substrate-specific allosteric conformations and provide a foundation for future experimental validation of selective allosteric modulation. Full article

Pyrazole derivatives have attracted considerable interest in medicinal chemistry as adaptable frameworks for developing cholinesterase inhibitors, owing to their advantageous physicochemical properties and structural flexibility. The heteroaromatic characteristics of the pyrazole core allow for various substitution patterns, promoting selective interactions with both the catalytically active site (CAS) and the peripheral anionic site (PAS) of cholinesterase enzymes. These attributes enable pyrazole-based drugs to be viable candidates for the therapy of cognitive disorders, especially Alzheimer’s disease. This study aims to systematically describe medicinal chemistry studies on pyrazole-based cholinesterase inhibitors conducted from 2020 to 2025. The focus is on structural alterations of the pyrazole core and their impact on the inhibitory action against acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) using structure–activity relationship (SAR) analysis. Recent advancements in in vitro enzymatic inhibition studies, molecular docking, kinetic analysis, ADME predictions, and multi-target-directed ligand (MTDL) techniques are rigorously evaluated to elucidate trends in potency, selectivity, and drug-like characteristics based on information retrieved from three search engines: Scopus, PubMed, and Google Scholar. This review addresses significant challenges in pharmacokinetics, blood–brain barrier permeability, and safety while delineating prospects for integrating rational design, computational modeling, and biological validation to expedite the development of clinically relevant pyrazole-based cholinesterase inhibitors for Alzheimer’s disease. Full article

The clinical success of cisplatin has significantly spurred the exploration of new organometallic complexes in oncology. In this quest, repurposing of auranofin as an anticancer agent has diverted the research interest from platinum to gold complexes, as gold offers unique chemical features; among them, thioredoxin reductase (TrxR) inhibition is one of the most extensively studied anticancer pathways. In this study, we have compiled the major ligand modifications reported for gold(I) complexes and categorized them into various groups, which include sulfur-based ligands, nitrogen-containing heterocyclic ligands, carbon-derived ligands, and N-heterocyclic carbene-based ligands. Also, a few structurally distinct ligands, including propargyl-, allene-, tricarbene-, and urea-functionalized NHC frameworks, have further extended structural diversity and functional potential. The in vitro evaluation of these newly synthesized gold complexes against various cancer cell lines exhibited enhanced biological potential compared to conventional metal complexes. Comparative evaluation of the reported cytotoxicity data revealed distinct structure–activity relationships among different ligand classes, with phosphine-carbon donor and bis-NHC frameworks emerging as the most promising ligand for achieving potent anticancer activity, highlighting the critical role of ligand design in modulating anticancer activity. In addition, the use of bioactive pharmacophores derived from natural products and active pharmaceuticals has emerged as a promising design strategy for developing multitarget gold(I) complexes with enhanced therapeutic efficacy. Among the reviewed compounds, complex 68 containing a bis-NHC ligand exhibited the highest potency against HL-60 leukemia cells (GI₅₀ = 0.017 μM), while complex 49 bearing a carbon-donor ligand demonstrated remarkable activity against A549 lung cancer cells (IC₅₀ = 0.02 μM). Several other gold(I) complexes also exhibited submicromolar activity against diverse cancer cell lines, further emphasizing the importance of rational ligand engineering in enhancing anticancer efficacy. Collectively, gold(I) complexes have emerged as a promising class of anticancer agents, and the comparative evaluation presented herein provides a valuable framework for identifying potent ligand scaffolds and guiding the rational development of next-generation gold-based therapeutics. Future advances in ligand engineering may facilitate targeted drug delivery, controlled release, and multi-mechanistic therapeutic strategies to overcome toxicity and drug resistance while enhancing therapeutic efficacy. Full article

Small cell lung cancer (SCLC) has historically been treated as a single, uniformly aggressive disease defined by neuroendocrine differentiation, near-universal loss of TP53 and RB1, and the absence of classical druggable oncogene addictions. Two converging lines of evidence are now reshaping that view. First, transcriptomic profiling has resolved SCLC into molecular subtypes—SCLC-A (ASCL1-driven), SCLC-N (NEUROD1-driven), SCLC-P (POU2F3-driven), and SCLC-I (inflamed)—with distinct immune microenvironments, surface-antigen expression patterns, and emerging therapeutic vulnerabilities, although intratumoral heterogeneity and phenotypic plasticity complicate clean subtype assignment. Second, the development of delta-like ligand 3 (DLL3)-directed therapies provides a natural experiment: the same validated surface antigen failed as an antibody–drug conjugate (rovalpituzumab tesirine, three negative randomized trials) yet succeeded as a bispecific T-cell engager (tarlatamab, which received FDA accelerated approval in 2024 and subsequent traditional FDA approval in 2025 following positive confirmatory phase 3 data). In this review, we integrate the current first-line standard of care—chemoimmunotherapy with atezolizumab- or durvalumab-based regimens followed by maintenance intensification with lurbinectedin–atezolizumab (IMforte)—with the molecular framework of subtypes and biomarkers, and we use DLL3 as a case study to propose that delivery modality is an important determinant of therapeutic success in SCLC and should be considered alongside target biology and tumor heterogeneity. Rapid proliferation, antigen heterogeneity, subtype plasticity, and a relatively less immunogenic microenvironment systematically penalize modalities dependent on payload accumulation and cell-cycle progression and reward modalities that recruit catalytic, cell-cycle-independent cytotoxic effectors. The emerging B7-H3 and SEZ6 programs—including ifinatamab deruxtecan and ABBV-706—are the next test of this framework. We discuss implications for biomarker development, trial design, and the operational challenges of subtype-guided precision oncology in a disease where tissue is scarce and biology shifts under therapy. Full article