Search Results (4,102)

Background/Objectives: Molecular docking and molecular dynamics are accurate but computationally expensive, so the compounds entering them must be chosen well. The present study proposes CADT, a confidence-gated affinity–ADME-T docking-triage cascade that decides which compounds are worth docking. Methods: The gate combines an ensemble estimate of drug–target affinity with its epistemic uncertainty and an applicability-domain check. Predicted absorption, distribution, metabolism, excretion, and toxicity (ADME-T) developability is added as a soft flag. All components were trained on openly licensed Therapeutics Data Commons data. Ranking was assessed on the DAVIS and KIBA kinase panels and on BindingDB $K_d$, under three split protocols over five seeds. The routing decision was then examined against molecular docking, in which 407 compound–target pairs were docked into six withheld kinases. Results: A Morgan-fingerprint gradient-boosting model reached a concordance index of $0.866\pm 0.006$, with $0.813$ for unseen targets and $0.720$ for unseen drugs. Across eight ADME-T endpoints, the area under the ROC curve ranged from $0.65$ to $0.91$. On the cold-target split the cascade reduced the compounds sent to docking by $86\%$ while retaining $61\%$ of the true strong binders. Docking measured that reduction at $85\%$, and at an equal budget, the gate enriched true binders more than the docking score itself. Conclusions: A transparent pre-screen can prioritise compounds ahead of structure-based calculation at a fraction of its cost. However, the uncertainty and applicability-domain terms act as an abstention mechanism rather than an accuracy gain, and that abstention is not free. Full article

Background: Sarcopenia is an aging-related syndrome characterized by loss of skeletal muscle mass, strength, and function, with no approved pharmacological treatment. This study aimed to design, synthesize, and evaluate novel ML-167 derivatives for sarcopenia-associated muscle wasting. Methods: ML-167 derivatives were synthesized and characterized by ¹H NMR, ¹³C NMR, and mass spectrometry. Biological activity was evaluated in C2C12 myoblasts using MTT and Western blot assays. Selected compounds were evaluated in a dexamethasone-induced muscle wasting model. Muscle strength, mass, biochemical parameters, and histopathology were assessed. Structure–activity relationships were analysed using cell viability, molecular docking, and ligand efficiency data, alongside physicochemical properties. Results: Compounds 6b (116%), 3a (115%), 8d (114%), 4c (112%), 3m (112%), and 3c (111%) showed the highest C2C12 viability at 1 μM. Compounds 3a, 3c, and 6b increased MyH3 expression by approximately 1.6–1.7-fold, while MyoG remained near basal levels. In vivo, these compounds improved muscle strength, mass, and biochemical parameters without overt hepatic or renal abnormalities based on assessed serum and histopathological findings. Among the evaluated derivatives, compound 6b emerged as the most promising overall lead candidate, showing the greatest improvement in skeletal muscle mass and metabolic parameters, whereas compound 3c demonstrated the strongest histopathological protection and favourable effects on muscle strength with favourable physicochemical properties. Molecular docking supported the SAR trends, although did not consistently correlate with cellular activity. Conclusions: The findings identify 3a, 3c, and 6b as promising lead compounds and support further investigation of ML-167 derivatives as potential pharmacological approaches for sarcopenia-associated muscle wasting. Full article

Usutu virus is an emerging mosquito-borne flavivirus with an expanding geographic distribution and increasing public health relevance, yet no licensed vaccine is currently available. This study used an integrated reverse vaccinology strategy to identify conserved immunogenic regions from the Envelope protein and NS5 protein, and construct a multi-epitope vaccine. Following sequential computational screening, the retained T-cell and B-cell epitopes satisfied the predefined selection criteria, while selected T-cell epitopes achieved an estimated 96.41% global population coverage. The final vaccine consisted of 240 amino acids and incorporated an adjuvant together with peptide linkers. Computational characterization indicated favorable physicochemical features and a refined three-dimensional model with improved stereochemical characteristics. Receptor-binding analyses predicted favorable interactions with TLR2 and TLR4, producing weighted docking scores of −1326.1 and −1230.2, respectively. Molecular dynamics simulation further characterized the temporal behavior of the vaccine–TLR2 complex, while MM-GBSA analysis yielded an estimated binding energy of −74.78 kcal/mol. C-ImmSim predicted enhanced humoral and cellular immune-response patterns following repeated antigen administration, including increased simulated antibody levels and changes in immune-cell populations. All findings in this study are based on in silico analyses and represent computational predictions rather than experimentally confirmed results. Further experimental validation is required to verify the predicted properties, immunogenicity, and protective potential of the proposed vaccine candidate. Full article

Persistent aldehydic off-notes in fish products are influenced not only by lipid oxidation but also by protein-associated retention of odor-active aldehydes. A remaining question is how gingerol side-chain length and aldehyde structure jointly alter this apparent retention. Mackerel myofibrillar protein (MP) was therefore combined with (E)-2-decenal (T2D), (E,E)-2,4-decadienal (DDE), or trans-4,5-epoxy-(E)-2-decenal (E2D), with or without 6-, 8-, or 10-gingerol. Headspace solid-phase microextraction–gas chromatography–mass spectrometry, interaction disruptors, spectroscopy, molecular docking, and 100 ns molecular dynamics simulations were integrated. All three gingerols decreased the apparent aldehyde-binding ratio of MP. At 125 µmol/g protein, 10-gingerol reduced T2D, DDE, and E2D binding from approximately 81%, 72%, and 85% to 68%, 65%, and 68%, respectively. Spectroscopic responses were consistent with changes in the optical and conformational environment; fluorescence was interpreted as apparent quenching without numerical inner-filter correction, and CD band changes provided evidence of a treatment-related conformational response without assigning exact secondary-structure fractions. Docking ranked 8-gingerol most favorably, whereas the selected binary MYH7-10-gingerol trajectory showed greater pocket residence and a more favorable MM/GBSA estimate than the corresponding MYH7-DDE trajectory. The combined evidence supports a three-layer working model involving matrix partitioning, protein-level site accessibility, and pocket-level competition. These findings provide a mechanistic basis for sensory validation rather than direct proof of deodorization. Full article

Background/Objectives: The programmed death-1/programmed death-ligand 1 (PD-1/PD-L1) immune checkpoint is a key therapeutic target in cancer immunotherapy, but small-molecule inhibition remains challenging due to its shallow and dynamic interaction interface. This study aimed to develop an artificial intelligence (AI)-guided workflow to identify novel small-molecule inhibitors targeting the PD-L1 dimer interface. Methods: A combined computational and experimental approach was established. A support vector regression-genetic algorithm (SVR-GA) model was trained on a dataset of 1385 known PD-L1 inhibitors to predict activity and guide molecular generation. From 470 AI-generated candidates, docking and molecular dynamics (MD) simulations were used for virtual screening. Selected compounds were synthesized and evaluated for PD-1/PD-L1 binding disruption using homogeneous time-resolved fluorescence (HTRF) assays. Cytotoxicity was tested in MDA-MB-231 and 4T1 cell monocultures, and in vivo efficacy was assessed in an immunocompetent 4T1 tumor model. Results: Two hits, PD-L1-Ser and PD-L1-Ser-OEt, were identified. Both disrupted PD-1/PD-L1 binding in HTRF assays, with PD-L1-Ser-OEt showing higher potency (IC₅₀ = 0.2068 μM). Both compounds exhibited limited direct cytotoxicity in cancer cell monocultures, suggesting an immune-mediated mechanism. In the 4T1 syngeneic mouse model, both inhibitors suppressed tumor growth without causing body weight loss. PD-L1-Ser-OEt demonstrated superior antitumor efficacy and elevated serum levels of IFN-γ and IL-4. Conclusions: This AI-guided workflow combining machine-learning-based molecular generation with structure validation is feasible for discovering PD-L1 dimer-interface inhibitors. PD-L1-Ser-OEt represents a promising lead compound for further development as an immune checkpoint inhibitor. Full article

Background/Objectives: Guizhi Fuling Capsule (GZFL), a Traditional Chinese Medicine (TCM) formula, is widely used for primary dysmenorrhea and other blood-stasis gynecological disorders. This study aimed to characterize its material basis, elucidate its multi-component, multi-target mechanism against acute primary dysmenorrhea, and establish an integrated pharmacokinetic-pharmacometabolomic-pharmacodynamic (PK-PM-PD) framework for TCM efficacy evaluation. Methods: GZFL constituents and serum metabolites in an oxytocin-/estradiol-induced rat dysmenorrhea model were characterized by UPLC/Q-TOF-MS. Uterine effects of GZFL-containing serum were assessed ex vivo. The active components of GZFL were screened by Chinmedomics, with candidate targets investigated through network pharmacology, transcriptomics, and molecular docking. In total, 23 pharmacodynamic indicators were integrated by principal component analysis into an Efficacy Index (EI). Correlation analysis between pharmacometabolomic and pharmacodynamic data yielded a Metabolite-Efficacy Index (MEI), evaluated across a 21-day time course. Results: Among 197 constituents characterized in GZFL extract, 136 serum-exposed components were detected, with several key metabolites enriched via biotransformation. GZFL-containing serum bidirectionally regulated uterine contractility toward the control level. Integrated analyses revealed 68 candidate therapeutic targets. GZFL suppressed NF-κB/IKKβ signaling, down-regulated COX-2/iNOS, restored the PGF2α/PGE2 balance, and normalized inflammatory cytokines. Eleven efficacy-associated metabolites correlated with pharmacodynamic recovery were revealed and integrated, with MEI achieving the highest predictive performance among five integration strategies (AUC = 0.9) and robustly tracking the full 21-day disease-recovery trajectory. Conclusions: GZFL attenuates dysmenorrhea through coordinated regulation of inflammation, prostaglandin metabolism, and uterine functional homeostasis, rather than through inhibition of a single target. The PK-PM-PD framework, with EI and MEI, offers a reproducible paradigm for evaluating complex TCM therapies. Full article

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a chronic disorder characterized by dysregulated lipid handling and bile acid signaling, processes controlled by PPARs and FXR. We report that RT206, a 2-aryloxy-3-phenyl-propanoic acid derivative, combines partial PPARα/γ agonism with positive allosteric modulation of FXR. Transactivation assays and endogenous gene-expression profiling confirmed activation of PPARα/γ-responsive genes. RT206 showed no intrinsic FXR agonism, yet it robustly potentiated FXR-dependent gene transcription in HepG2 cells in the presence of structurally distinct orthosteric agonists. Grating-coupled interferometry revealed weak interaction with apo-FXR that was enhanced by orthosteric ligands, consistent with cooperative ternary complex formation. Docking and molecular dynamics supported a model in which RT206 engages the non-orthosteric FXR S2 site, while orthosteric agonists occupy the S1 primary pocket. Comparison with guggulsterone revealed distinct predicted S2 interaction patterns associated with divergent transcriptional outcomes in vitro. In fatty acid-loaded HepG2 cells, RT206 combined with FXR agonists modulated FXR- and PPAR-regulated metabolic genes and modestly reduced neutral-lipid accumulation. These findings identify RT206 as a proof-of-principle scaffold that integrates partial PPARα/γ agonism with ligand-dependent potentiation of FXR activity and support its further evaluation in more advanced liver models. Full article

Symphytum officinale L. is a traditional medicinal plant widely used for wound healing and bone regeneration; however, comparative studies evaluating the biological activities of extracts prepared from different plant organs remain limited. The present study compared the antimicrobial and anti-inflammatory activities of organ-specific S. officinale extracts and investigated their potential molecular mechanisms of bioactivities using molecular docking. Antimicrobial activity was evaluated against six bacterial reference strains by broth serial dilution, whereas anti-inflammatory activity was assessed in a serotonin-induced paw oedema model in rats together with the determination of serum prostaglandin E₂ (PGE₂), tumour necrosis factor-α (TNF-α), and nitrotyrosine levels. Molecular docking was performed against bacterial peptide deformylases, cyclooxygenase-2 (COX-2), and 5-lipoxygenase (5-LOX). The 40% ethanolic leaf extract (S-7) and 70% ethanolic flower extract (S-13) exhibited the broadest antimicrobial spectrum, with pronounced activity against S. aureus, E. faecalis, E. coli, and L. monocytogenes. The 70% ethanolic leaf extract (S-8) demonstrated the strongest early anti-exudative activity (47.50%), whereas the 70% ethanolic flower extract (S-13) most effectively reduced PGE₂, TNF-α, and nitrotyrosine levels. Molecular docking suggested that kaempferol-3-O-glucoside may be the principal contributor to antimicrobial activity through interactions with bacterial peptide deformylases, while hyperoside, isoquercitrin, and rosmarinic acid exhibited favourable interactions with COX-2 and 5-LOX, indicating their key role in exerting anti-inflammatory effects. These findings demonstrate pronounced organ-specific pharmacological differences among S. officinale extracts and identify hydroethanolic leaf, flower, and root extracts as promising candidates for further development as multitarget wound-healing phytopharmaceuticals. Full article

Background/Objectives: Interstitial cystitis/bladder pain syndrome (IC/BPS) is a chronic inflammatory bladder disorder that lacks an effective treatment agent. Fucoidan (FUC), isolated from Fucus vesiculosus, is a sulfated polysaccharide that exhibits potent anti-inflammatory and anti-fibrotic activities. This study investigated the protective effects and underlying mechanisms of FUC in IC/BPS. Methods: NLRP3 inflammasome activation and AKT signaling were evaluated by Western blotting, qRT-PCR, immunofluorescence, pharmacological inhibition, gene silencing, and overexpression. Molecular docking assessed potential FUC–protein interactions. In vivo mouse model evaluated the protective effects and toxicity of FUC. Results: In SV-HUC-1 cells, FUC significantly attenuated TNF-α-induced expression of NLRP3 and cleaved caspase-1 and c-IL-1β expression at both the transcriptional and protein levels. Residual inflammasome activity after FUC treatment remained further suppressible by MCC950 or siNLRP3. FUC also reduced TNFα-induced AKT phosphorylation, whereas AKT silencing and overexpression enhanced and partially reversed the inhibitory effect of FUC on inflammasome signaling, respectively. The molecular docking results suggested potential interactions between FUC and key inflammasome-related proteins, including NLRP3, caspase-1, IL-1β, and AKT. In interstitial cystitis mice, FUC mitigated cyclophosphamide (CYP)-induced bladder injury, reduced bladder expression of inflammasome-associated markers, and exhibited no significant toxicity in major organs. Conclusions: These findings indicate that FUC alleviates urothelial inflammatory injury and experimental cystitis, at least in part, by suppressing the AKT/NLRP3 inflammasome axis, supporting its potential as a therapeutic candidate for IC/BPS. Full article

The triterpenoid and polysaccharide constituents of Ganoderma lucidum (GL) are believed to influence key pathogenic pathways in Alzheimer’s disease (AD). This study first examined the molecular rationale for GL’s neuroprotective properties by subjecting its principal triterpenoids, Ganoderic Acid A&B, to computational profiling. Molecular docking was performed against human acetylcholinesterase (AChE), TNF-α, COX-2, IL-6, caspase-3, Bcl-2, and the Keap1–Nrf2 complex using CB-Dock2, alongside SwissADME-based physicochemical and ProTox-3.0-based toxicological screening. These targeted pathways were then biologically validated in an in vitro AD model induced by Aβ_1–42 toxicity in SH-SY5Y cells, assessing AChE activity, apoptosis, ROS levels, mitochondrial membrane potential (MMP), and cytokine expression (COX-2, TGF-β1, IL-6, TNF-α, IL-10). Docking revealed high binding affinities of both triterpenoids toward all seven targets (Vina scores: −7.3 to −10.4 kcal/mol), predicting strong modulation of cholinergic, inflammatory, apoptotic, and antioxidant pathways. Consistent with these predictions, GL extract significantly reduced TNF-α, COX-2, and IL-6 mRNA and protein levels, attenuated ROS accumulation, preserved MMP except at 500 µg/mL, and exerted a concentration-dependent antiapoptotic effect. IL-10 and TGF-β1 showed complex, dose-dependent patterns, reflecting indirect regulatory responses. Together, these findings support GL’s neuroprotective potential against Aβ-induced toxicity through direct engagement of cholinergic, inflammatory, apoptotic, and antioxidant regulatory proteins. Full article

Background/Objectives: Polyendocrine metabolic ovarian syndrome (PMOS) is characterized by hyperandrogenism, particularly excessive testosterone, as a core clinical feature and a key pathogenic metabolite, yet its molecular mechanisms remain incompletely understood. Methods: This study integrated multi-omics data from Gene Expression Omnibus (GEO) databases with network toxicology, weighted gene co-expression network analysis (WGCNA), and machine learning to identify testosterone-associated core genes in PMOS. Results: Differential expression analysis and WGCNA yielded 42 candidate genes, from which five core genes, including GK5, CYP3A5, EGLN3, VCAM1, and AGTR1, were prioritized as top predictive features through ensemble modeling (RF + XGBoost). Molecular docking predicted favorable testosterone binding conformations. Regulatory network and drug enrichment analysis additionally predicted several upstream transcription factors, hub miRNAs, and potential repurposable drugs. Conclusions: These findings proposed a computational framework for a multi-target molecular landscape linking testosterone to PMOS. The identified genes, regulatory networks, and candidate drugs provided prioritized hypotheses for mechanistic exploration and future evaluation of potential diagnostic and therapeutic applications in hyperandrogenism-related PMOS. Full article

Imidazoles have been proven to be very effective pesticides, especially against phytopathogenic fungi and insects. Due to their negative effects on the environment, only a few imidazoles have been approved for use by the European Commission (EC). There is an urgent need to develop new imidazole derivatives with high efficiency and a wide spectrum of action against numerous pests that are, at the same time, safe for the environment and beneficial for organisms and humans. In order to reduce expensive and time-consuming experiments, an in silico approach based on quantitative structure–activity relationship (QSAR) models is valuable for predicting the toxicity of new or untested chemicals. In this study, we used the Vega and ChemFREE web platforms to evaluate the pesticide similarity, environmental risk properties, and ecotoxicological effects of imidazole derivatives designed for potential synthesis. Adamantane-, alkyl-, and triazole-amide, ester, carbamate, and ketone derivatives were filtered for the evaluated properties, and four alkyl-amides were highlighted as potentially effective and environmentally safe antifungal, herbicidal, and insecticidal agents. Molecular docking studies indicated the possible mechanism of action of the antifungal, herbicidal, insecticidal, and antibacterial activities of the observed compounds and revealed structural features important for binding to specific receptors. Full article

Plant metabolites are a promising source of new biopesticides, but their chemical diversity exceeds the capacity of experimental screening. Cannabis sativa is a particularly attractive crop for discovering such compounds, although its metabolome has not been systematically evaluated for biopesticidal potential. Here, we computationally analyzed 5211 compounds annotated as C. sativa metabolites in the Cannabis Compound Database (CCD) using an integrated framework combining graph-based molecular prediction and protein–ligand interaction analysis. Initial prioritization employed a directed message passing neural network (DMPNN) trained on molecular graphs augmented with RDKit descriptors. The DMPNN predictions were integrated with a CatBoost-derived docking-consistency score based on residue-level Vina interaction terms, reducing the false-positive rate by about 60% compared with the structural model alone. Informative ligand-residue interactions were identified using a random matrix theory (RMT) framework. The DMPNN identified 1010 compounds as DMPNN-positive (score $\ge 0.70$), indicating structural characteristics more consistent with the DS2 pesticide reference set than with the DS3 AChE-inactive reference set. Then, these compounds were filtered using annotations from the CCD to retain 44 secondary metabolites. Finally, the 44 compounds were ranked by the final ensemble score. Compared with reference pesticides, C. sativa metabolites showed higher predicted median oral LD₅₀ values and fewer organ-specific toxicity alerts at the dataset level, although not for all endpoints. Overall, the combined structural and docking-informed workflow identified a small, chemically diverse set of high-ranking C. sativa compounds that can now be prioritized for experimental validation. Full article

Diabetes mellitus is a long-term metabolic disease associated with elevated glucose levels in blood and still constitutes one of the major public health issues worldwide. Inhibition of carbohydrate-digesting enzymes like α-amylase and α-glucosidase has been found to be effective in controlling postprandial hyperglycemia. The current study focused on designing, synthesis, characterization, and evaluation of novel 2,4-thiazolidinedione derivatives (D1–D5) as potent antidiabetic drugs utilizing combined in silico, in vitro, and in vivo techniques. Results from drug-likeness and ADME analyses indicated that all synthesized derivatives met Lipinski’s rule of five and had desirable pharmacokinetics properties along with reduced toxicity. Molecular docking against maltase-glucoamylase (human; PDB ID: 3TOP) protein showed good binding affinities of both D1 and D5 derivatives (−7.74 and −7.40 kcal/mol respectively) due to stable interactions with catalytic residues of enzymes. Inhibition of enzymes in vitro showed that D1 and D5 had the highest inhibitory activities of all synthesized derivatives, with IC₅₀ of 33.86 ± 2.1 and 37.55 ± 1.7 μM against α-amylase and 29.81 ± 3.2 and 32.43 ± 1.2 μM against α-glucosidase, respectively. Cytocompatibility tests on L6 myoblast cells proved that the lead compounds were well tolerated. In addition, studies in a model of Drosophila melanogaster induced by a high-sugar diet revealed a significant decrease in the level of glucose concentration depending on the dose, especially for D1 and D5, indicating their antihyperglycemic activity in vivo. Thus, these data confirm that D1 and D5 can be regarded as promising lead compounds for the development of new antidiabetics acting via inhibition of carbohydrate-metabolizing enzymes. Full article

Hepatitis A virus (HAV) infection remains a global public health concern in both developing and developed countries. In the present study, we identified anti-HAV drugs, using AutoDock Vina Modeling software, and evaluated the compounds in vitro. Following cytotoxicity for Huh7 cells, 5 out of 10 compounds were selected. We evaluated effective HAV 3C protease inhibitors with activity against both HAV genotype IB HM175/18f and HAV genotype IIIA HA11-1299-infected human hepatoma cells. Among the five compounds, we identified only one (KCN-A-12), which had an inhibitory effect on both HAV genotype IB HM175/18f and HAV genotype IIIA HA11-1299 replication in human hepatoma Huh7 cells. KCN-A-12 has more effective inhibitory effects on the replication of HAV genotype IB HM175/18f than that of HAV genotype IIIA HA11-1299. This difference may be attributable to the fact that our discovery system depends on crystal structures from HAV 3C protease based on the HAV genotype IB HM175 strain. In conclusion, we observed that KCN-A-12 was able to inhibit HAV replication. In silico screening for HAV 3C protease inhibitors may be useful for further discovery of anti-HAV drugs. Full article