Search Results (537)

Shuanghuanglian oral liquid (SHL) is widely used in companion animals and poultry, but its molecular mechanism in pneumonia–myocarditis comorbidity and heart–lung inflammatory crosstalk remains largely unclear. This computational study investigated the conserved AKT1/HIF1A-mediated immunoregulatory mechanism of SHL and its cross-species translational potential in veterinary medicine. Network pharmacology was integrated with GO, KEGG, and Reactome enrichment analyses, protein–protein interaction network construction, ADMET evaluation, cross-species sequence homology analysis (human, dog, cattle, and pig), molecular docking, and molecular dynamics simulation. A total of 61 active compounds, 251 putative targets, and 52 common targets associated with pneumonia and myocarditis were identified. These targets were mainly enriched in inflammation- and immune-related pathways, including TNF, IL-17, AGE–RAGE, and PPAR signaling. AKT1 and HIF1A showed high sequence conservation across species (85–98%). Key compounds exhibited favorable binding affinity to AKT1, and molecular dynamics simulation suggested the stability of the Baicalein–AKT1 complex. ADMET analysis suggested favorable pharmacokinetic properties and low predicted toxicity. These findings suggest that SHL may potentially alleviate pneumonia and myocarditis through modulation of the conserved AKT1/HIF1A axis and support its potential as a complementary therapeutic approach for managing heart–lung inflammatory diseases in multiple livestock species. This entirely computational study highlights promising mechanisms that should be further validated in vivo. Full article

Marburg virus (MARV), a highly pathogenic member of the Filoviridae family, causes severe hemorrhagic fever with a high case fatality rate and currently lacks effective therapeutics. The viral entry process, mediated by the interaction between the MARV glycoprotein (GP) and host receptor C-type lectin domain family 4 member M (CLEC4M) (L-SIGN), represents a critical target for early-stage intervention. The active compounds from BindingDB and the decoy from DUDE were used. The RDKit was used for feature engineering. Machine learning models were trained on an initial dataset consisting of 56 active chemicals and 1232 decoys. Among the tested algorithms, the Random Forest model demonstrated superior performance, achieving the highest discriminative ability (AUC = 0.93, MCC = 0.88) on the test set. Virtual screening of 11,032 phytochemicals resulted in 120 predicted actives, of which 42 compounds satisfied drug-likeness criteria. Subsequent molecular docking identified three lead compounds (PubChem IDs: 42608095, 5281601, and 11243993) with moderate-to-promising binding affinities (−6.3 to −6.5 kcal/mol) toward the CLEC4M binding site. ADMET analysis revealed favorable pharmacokinetic and toxicity profiles for the selected lead compounds. DFT calculations of the three compounds highlighted their electronic stability and reactive nature, indicating that PubChem IDs 42608095 and 5281601 possess particularly stable electronic properties conducive to favorable target interactions. Combining machine learning models with molecular docking and Molecular Dynamics (MD) simulations worked well in finding promising phytochemical inhibitors. The MM/GBSA binding free energy calculations further confirmed binding affinities, with values of −10.83 and −11.08 kcal/mol, respectively, suggesting favorable complex stability. These findings provide a pathway for developing new antiviral agents against MARV, pending further experimental validation and optimization. Full article

Background: Dental caries is a chronic disease mediated by biofilm, which is caused by Streptococcus mutans, and enamel genetics modulates susceptibility. The variants of ENAM might alter the adhesion of enamel and bacteria. One important anti-viral target is sortase A (SrtA), which restricts colonization but does not have an impact on bacterial survival. Aim: The aim of this study was to find out the relationship between ENAM rs3796704 and dental caries vulnerability among adult Iraqi Arab females and to assess the antibiofilm capacity of eugenol and cinnamic acid against S. mutans SrtA using molecular docking, ADMET prediction, and molecular dynamics modeling. Methods: A case–control study was done on 240 women (aged 25–30 years; 120 caries, 120 controls). HRM real-time PCR was done to genotype ENAM rs3796704. An analysis of allelic and genotypic distributions was done using chi-square tests and odds ratios (p < 0.05). An in silico docking analysis aimed at SrtA (PDB: 4TQX) was performed in AutoDock Vina, and this was followed by ADMET profiling and a 50 ns molecular dynamics simulation (OPLS4/TIP3P, NPT 300 K/1 atm). Results: The level of the G allele was found to be lower in the cases than in the controls (60% vs. 70; OR = 0.6429; p = 0.02), but the level of the A allele was found to be higher in the cases (40% vs. 30; OR = 1.5556; p = 0.02). Docking showed a minor difference in binding affinities with eugenol (−4.961 kcal/mol) and cinnamic acid (−4.939 kcal/mol) as compared with chlorhexidine (−4.692 kcal/mol). Both compounds showed stable binding for more than 50 ns as well as desirable predicted pharmacokinetics. Conclusions: The caries vulnerability in this sample was associated with ENAM rs3796704. Eugenol and cinnamic acid undergo stable dissociative interactions with SrtA and were found to have favorable safety profiles in silico. Therefore, they may be considered as adjunctive anti-virulence agents in the prevention of caries. Full article

Background/Objectives: Poly (ADP-ribose) polymerase (PARP1) has emerged as a promising therapeutic target in human breast cancer particularly in BRCA1/2 mutation carriers where a synthetic lethal interaction leads to massive tumor cell death upon specific inhibitors’ administration. Current clinically approved PARP inhibitors (Talazoparib and Olaparib) show outstanding therapeutic capabilities but suffer from severe side effects. Most importantly, some of them can cause life-threatening cardiotoxicity through hERG off-target effects. Here, we performed an extensive study to identify lead compounds with improved binding modes and favorable predicted pharmacokinetics using an integrated computational strategy. Methods: An artificial intelligence-driven drug design (AIDDISON™ v2023) workflow was employed to search ultra-large chemical space libraries for active compounds, which were then optimized via computer-aided methods to form a PARP-Tailored Database (PTD). This database was then analyzed through a virtual screening workflow, molecular docking studies, molecular dynamics (MD) simulations, MM/GBSA binding free energy calculations, DFT analysis and ADME/Tox predictions using the Schrödinger suite (v2023-2), MobaXterm v25.2, Gaussian 16.0, ProTox-3 and Pred-hERG v5.0 respectively. Results: Three compounds (1a–1c) were identified as promising candidates. Among them 1a appeared to be the most active compound with a favorable docking score (−9.488 kcal/mol) that is not only higher than 1b and 1c but also higher than that of Talazoparib (−6.778 kcal/mol). MD simulations of 1a–1c in the active site revealed an average RMSD of ~2.5–3.6 Å which is better compared to the parent Talazoparib (5.6 Å). Interestingly, on the 250 ns extended MD study, 1a exhibited a slightly reduced RMSD between 2.4 and 3.2 Å, whereas Talazoparib retained higher fluctuations of ~5 Å to 6 Å. MM/GBSA binding energy analysis indicated 1a to have better predicted binding affinity (−67.820 kcal/mol), which is also better than Talazoparib (−63.734 kcal/mol). DFT calculations showed good electronic properties and in silico ADMET studies also indicated 1a to have good drug-likeness and lower predicted hepatotoxicity and cardiotoxicity risk. Conclusions: These findings identify compound 1a as a promising lead, while compounds 1b and 1c remain viable candidates for further optimization. However, experimental validation is critical to confirm the predicted biological activity and safety profiles. Full article

The incidence of levofloxacin and metronidazole resistance in H. pylori Indonesian strains is increasing. Conventional approaches to antibacterial discovery are often a protracted process. This study uses structure-based virtual screening to quickly discover anti-H. pylori. This study employed homology modeling, docking, ADMET prediction, and molecular dynamics simulation to evaluate phytochemicals against resistant H. pylori gyrA, gyrB, and rdxA structures from Indonesian strains. Three-dimensional structures were constructed from the amino acid sequences gyrA, gyrB, and rdxA of levofloxacin- and metronidazole-resistant H. pylori Indonesian strains. The results of redocking at the binding sites gyrA (0.13 Å), gyrB (0.0024 Å), and rdxA (0.5 Å) obtained a valid RMSD. Curcumin exhibited the lowest average binding scores across gyrA (−154.994 kcal/mol), gyrB (−159.2033 kcal/mol), and rdxA (−166.322 kcal/mol) compared to other compounds and standard therapies, including levofloxacin (−109.1553 and −122.5873 kcal/mol) and metronidazole (−85.6096 kcal/mol). Molecular dynamics simulation results revealed that the curcumin–gyrA complex exhibited comparatively more restrained fluctuation than the other complexes throughout the simulation, as indicated by a consistently low total RMSD value (4–7 Å). Curcumin demonstrated the most favorable computational interaction profile among the evaluated compounds. Full article

Harmful algal blooms pose a persistent threat to the integrity of freshwater ecosystems and public health. However, there are no selective chemical control agents available to suppress cyanobacterial growth without damaging beneficial phytoplankton. In this study, ten structurally diverse monoterpenes were assessed in vitro for their differential activity against the potent toxin-producing cyanobacterium Microcystis aeruginosa and the ecologically valuable microalga Chlorella sorokiniana using disc diffusion (DDM) and minimum inhibitory concentration (MIC) assays. Inhibition zones against M. aeruginosa ranged from 6.9 to 43.6 mm, with thymol recording the largest zone (43.6 mm). MIC values ranged from 0.25 to >1 mg/mL for both organisms, and selectivity indices identified camphor and carvone as the most cyanobacterium-preferential compounds, while carene and α-pinene showed the inverse selectivity pattern. Molecular docking against six AlphaFold2-predicted target proteins, photosynthetic complexes, Adenosine Triphosphate (ATP) synthase subunits, and superoxide dismutase (SOD) from both organisms, revealed binding affinities between −3.9 and −6.2 kcal/mol. Phenolic monoterpenes consistently engaged active-site glutamate and aspartate residues via hydrogen bonds and Pi–Anion interactions, most strikingly in the M. aeruginosa ATP synthase, whereas the M. aeruginosa SOD represented the least amenable target for all compounds. Computational ADMET profiling confirmed favorable pharmacokinetic properties and low predicted toxicity for the full panel. Full article

A series of 1,2,3-triazole-linked-thiazolidine-2,4-dione hybrids (SDP1–SDP15) were designed, synthesized, and evaluated for their antidiabetic potential. All structures were characterized by FT-IR and NMR spectroscopy (¹H and ¹³C). All derivatives exhibited significant in vitro inhibition of α-glucosidase (IC₅₀: 24.17–46.41 µg/mL) and α-amylase (23.25–50.66 µg/mL), comparable to the standard drug acarbose (IC₅₀: 25.18 and 32.53 µg/mL) and superior to the reference drug pioglitazone (IC₅₀: 84.24 and 79.74 µg/mL) for α-glucosidase and α-amylase, respectively. Molecule SDP8 emerged as the most potent with an IC50 of 24.17 and 23.25 µg/mL for α-glucosidase and α-amylase, respectively. Further, SDP8 exhibited a higher docking score of −10.7 kcal/mol and −10.4 kcal/mol against α-glucosidase and α-amylase than pioglitazone (−8.1 kcal/mol and −7.7 kcal/mol, respectively), suggesting that interaction with these two enzymes may be the cause for its antidiabetic activity. Furthermore, DFT analysis revealed favorable electronic properties with a low HOMO-LUMO energy gap, whereas ADMET predictions revealed moderate drug-like characteristics with some limitations, such as poor solubility, relatively high lipophilicity, and partial noncompliance with drug-likeness regulations. Overall, these results highlight triazole-linked thiazolidinedione hybrids as promising candidates for further development in T2DM, with SDP8 serving as a preliminary lead requiring additional optimization and validation. Full article

Alzheimer’s disease (AD) is a multifactorial neurodegenerative disorder characterized by the accumulation of the toxic protein amyloid-β, formation of tau-containing neurofibrillary tangles, neuroinflammation, and synaptic dysfunction, highlighting the need for new therapeutic strategies capable of modulating multiple pathological pathways simultaneously. In this study, a structure-based in silico approach was applied to evaluate the multi-target potential of two previously reported pyrrole-based compounds (pyrrole 1 and pyrrole 2) with known monoamine oxidase-B (MAO-B) inhibitory activity and low neurotoxicity. Molecular docking studies were performed against a panel of key AD-related targets, including GSK-3β, APP, MAO-B, BACE1, AChE, BChE, COX-2, GABA-B receptor, NMDA receptor, and E3 ubiquitin ligase CHIP, using Glide XP docking. The results revealed that compound pyrrole 1 may have favorable predicted binding affinities across several targets, with relatively strong docking scores for GSK-3β and COX-2. The binding mode analysis indicated that pyrrole 1 adopts poses consistent with interaction patterns commonly observed for ATP-competitive GSK-3β inhibitors and COX-2 ligands. In silico ADMET profiling using the software SwissADME and ProTox 3.0 indicated distinct pharmacokinetic and safety profiles for the two compounds, with pyrrole 2 showing superior drug-likeness and predicted blood–brain barrier penetration, while pyrrole 1 displayed a more favorable overall toxicity profile. Collectively, these findings identify pyrrole 1 as a theoretically promising multi-target candidate for AD requiring experimental validation, while providing a strong structural basis for further optimizations and subsequent experimental confirmation. Full article

Parkinson’s disease is strongly linked to lysosomal dysfunction, particularly reduced activity of glucocerebrosidase (GCase) encoded by the GBA1 gene. Stabilizing GCase using small-molecule modulators represents a promising therapeutic strategy. In this study, phytochemicals from Xylia xylocarpa (Roxb.) Taub., a medicinal plant with reported neuroprotective potential, were profiled using LC-QTOF-MS and evaluated as GCase stabilizers through an integrated computational approach. LC-MS analysis in positive and negative modes tentatively identified 19 metabolites, of which 13 low-molecular-weight compounds (<500 Da) were selected for molecular docking against human GCase. Docking revealed six compounds with higher predicted binding affinity than the reference activator Pyrrolopyrazine. Pharmacokinetic screening based on Lipinski’s rule of five and ADMET predictions identified Senbusine A as a viable lead candidate. It exhibited favorable binding interactions, forming stabilizing contacts within a non-catalytic inter-monomer interface associated with structural modulation of GCase. PASS analysis suggested a high probability of neuroactive properties. Molecular dynamics simulations (200 ns) confirmed stable binding and reduced conformational fluctuations compared to apo and control systems. Overall, computational predictions identify Senbusine A as a potential pharmacological chaperone-like stabilizer of GCase, exhibiting a favorable pharmacological profile and warranting further experimental validation. 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

Background: Diabetes mellitus remains a major public health concern, particularly in sub-Saharan Africa where type 2 diabetes predominates. In West Africa, Uvaria chamae P. Beauv. is traditionally used for diabetes management. This study investigates previously reported metabolites from Uvaria chamae using an integrated in silico approach to explore their potential antidiabetic activity and underlying mechanisms. Methods: A comprehensive literature survey identified 106 phytochemicals from stems, roots, leaves, and seeds. Diabetes-related protein targets were retrieved from the RCSB Protein Data Bank, while ligand structures were obtained from PubChem and the COCONUT database. Molecular docking, MM-GBSA rescoring, induced-fit docking, QSAR, and ADMET analyses were performed to evaluate interaction profiles, predicted activity, and developability. Results: The integrated analysis supports a polypharmacological mixture-based profile with organ-associated trends. Stem- and root-derived flavonoids, particularly isouvaretin and diuvaretin, showed the most consistent profiles for PPARγ-related pathways, while uvarinol was associated with PTP1B. Leaf alkaloids were mainly linked to DPP-4 and digestive enzyme inhibition. These compounds displayed more favorable predicted pharmacokinetic and toxicity profiles compared to acetogenins, which, despite favorable binding energies, were not prioritized as drug-like candidates due to their high lipophilicity, low QED values, and predicted toxicity liabilities, but may contribute to extract-level activity. Conclusion: These findings provide a hypothesis-generating and hierarchical framework for the prioritization of Uvaria chamae metabolites and extracts, supporting further experimental validation through enzymatic, cellular, and gene expression studies. Full article

Psoriasis is a chronic, immune-mediated inflammatory skin disease for which the development of structurally novel and accessible small-molecule candidates remains of considerable interest. In this study, a series of juglone-derived naphthoquinone analogs was synthesized to explore the influence of substitution pattern on anti-inflammatory activity and cytotoxicity. Their biological profiles were first evaluated in LPS-stimulated HaCaT cells by combining cytotoxicity assessment with nitric oxide (NO) screening. Most derivatives showed reduced cytotoxicity compared with juglone, and preliminary structure–activity relationship analysis indicated that retention of a free hydroxyl group at the C-2 position was generally favorable for both reduction in NO release and cellular safety, whereas C-3 alkyl substitution tended to weaken activity and increase cytotoxicity. Among the tested compounds, compound 11 showed the most favorable balance between reduction in NO release and low cytotoxicity. Further evaluation showed that compound 11 reduced the protein levels of several inflammatory mediators in the culture supernatants of LPS-stimulated HaCaT cells, including TNF-α, IL-6, IL-1β, IL-17A, and IL-23, under the tested conditions. In an imiquimod-induced psoriasis-like mouse model, topical administration of compound 11 partially alleviated IMQ-induced psoriasis-like skin lesions, improved histopathological changes to some extent, and reduced selected inflammatory cytokine levels in serum and skin tissues under the tested conditions. Exploratory target prediction, molecular docking, and in silico ADMET analyses provided supportive computational insight into the biological profile of compound 11. Overall, these findings suggest that juglone-derived naphthoquinones may serve as useful natural-product-inspired scaffolds for further anti-inflammatory optimization, and compound 11 warrants further investigation in psoriasis-related experimental models. Full article

Background: This study evaluates the translational relevance of free computer-assisted ADMET platforms in drug discovery by comparing SwissADME and FAF-Drugs4 predictions with regulatory and curated reference data for approved anticancer drugs. Methods: Fourteen approved anticancer agents representing diverse chemical classes were analyzed using SwissADME and FAF-Drugs4. We compared predicted physicochemical, pharmacokinetic, and toxicity-related properties with information extracted from FDA- and EMA-approved product information, DrugBank, and PubChem. We evaluated the concordance for oral absorption, permeability, metabolic stability, and toxicity-related trends. Results: The platforms showed good concordance for broad descriptor-driven properties, particularly oral suitability and physicochemical trends. Strong agreement was observed for intravenously administered taxanes, which displayed unfavorable oral drug characteristics, and for several orally active small molecules with generally compatible profiles. Partial concordance was observed for compounds such as temozolomide, whose clinical behavior is influenced by factors not fully captured by descriptor-based models. Toxicity outputs were informative as early warning signals, with vandetanib showing the clearest alignment between predicted elevated risk and documented safety concerns. Conclusions: Free computational ADMET tools are valuable computer-assisted drug discovery resources for early triage, predictive toxicology, and prioritization of repositioning candidates, but they should complement rigorous experimental and clinical evaluation. Full article

Βackround/Objectives: The rising global burden of cardiometabolic disorders and chronic low-grade inflammation underscores the need for therapies capable of modulating multiple interconnected pathways. Methods: In this work, a ligand-based virtual screening campaign centered on a previously reported scaffold (compound 1a) was combined with molecular docking, 200 ns molecular dynamics simulations and ADMET prediction to identify and prioritize small-molecule multitarget candidates against PCSK9, GLP1R, FGFR1, GIPR, NF-κB and NLRP3. Results: Among the screened analogs, D4Z emerged as the most balanced lead, displaying consistently favorable binding profiles, stable interactions within functionally relevant pockets and a drug-like physicochemical and pharmacokinetic profile with high predicted oral absorption. Conclusions: Although these findings remain purely computational, they support D4Z as a prioritized multitarget lead for synthesis and experimental validation and illustrate the potential of rational multitarget design for addressing the cardiometabolic–inflammatory axis. Full article

Marine natural products, including seaweeds, sponges, and marine microorganisms, have emerged as promising sources of bioactive compounds with diverse pharmacological properties. We investigated the antibacterial and antioxidant potential of ethanol extracts (30%, 60%, and 90%) from Saccharina japonica collected from two Korean coastal regions, Gijang and Wando, and evaluated their bioactive metabolites through integrated in vitro and in silico approaches. Among the extracts, the 60% ethanol fraction exhibited the highest total phenolic content and strongest 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical-scavenging activity, indicating superior antioxidant capacity. Antibacterial assays revealed selective concentration-dependent inhibition against Staphylococcus aureus, while limited effects were observed against Escherichia coli. Kinetic analysis further demonstrated growth suppression of S. aureus at higher concentrations. Molecular docking was performed against multiple bacterial proteins, including DNA gyrase, topoisomerase IV, and tyrosyl-tRNA synthetase. Sterol compounds, particularly fucosterol and 24-methylene cholesterol, showed strong binding affinities across key targets, suggesting their potential role as multitarget antibacterial agents. ADMET predictions indicated favorable pharmacokinetic properties, although high lipophilicity and potential hERG II inhibition were noted. Overall, while the antibacterial effects observed were moderate, these findings suggest that marine-derived sterols from S. japonica may represent compounds of interest for further mechanistic investigation and optimization in complementary antibacterial strategies. Full article