Search Results (213)

Background/Objectives: Tuberculosis (TB), caused by Mycobacterium tuberculosis, remains a major global health challenge, exacerbated by the emergence of multidrug-resistant strains and limited efficacy of existing therapies. Given the involvement of multiple essential mycobacterial proteins, multitarget drug discovery represents a rational therapeutic strategy. Methods: In this study, an integrated in silico pipeline combining machine learning–based quantitative structure–activity relationship modeling, graph neural network–driven drug–target affinity prediction, molecular docking, molecular dynamics (MD) simulations, and pharmacokinetic–toxicity profiling was employed to identify potential antitubercular leads from natural products. Results: A curated library of over 0.69 million compounds from the COCONUT database was systematically screened against seven essential M. tuberculosis protein targets. Machine learning and heterogeneous graph neural network models effectively captured complex ligand–protein interaction patterns, enabling high-confidence multitarget prioritization. Structure-based docking and MM-GBSA analyses revealed favorable binding affinities, further supported by 100 ns Molecular Dynamics simulations demonstrating stable binding and conformational integrity. In silico ADMET and toxicity predictions identified pharmacokinetically balanced candidates, while density functional theory calculations corroborated favorable electronic properties. Conclusions: Notably, a myricetin-based flavonoid glycoside exhibited consistent multitarget binding and dynamic stability across all targets. Overall, this study underscores the potential of integrated artificial intelligence and structure-based approaches in accelerating natural product-based antitubercular drug discovery and supports further experimental validation of prioritized leads. 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

Coumarins represent a distinctive class of non-classical carbonic anhydrase inhibitors that interact with the entrance region of the catalytic pocket rather than directly coordinating the catalytic Zn²⁺ ion. In this study, a series of glycosylated coumarins was synthesized through a copper-catalyzed multicomponent reaction involving propargyl glycosides, salicylaldehyde, and tosyl azide, providing efficient access to iminocoumarin-based glycosides derived from natural carbohydrates. The inhibitory activity of the synthesized compounds was evaluated against human carbonic anhydrase isoforms I, II, IX, and XII using a stopped-flow CO₂ hydrase assay. The compounds showed negligible inhibition of the cytosolic isoforms hCA I and hCA II, while displaying moderate activity toward the tumor-associated isoforms hCA IX and hCA XII, with Ki values ranging from 12.9 to 41.8 μM. Among the series, 6-O-(2H-chromene-2-one-3-yl-methyl)-D-galactopyranose (10a) emerged as the most potent inhibitor of hCA IX and XII. Structure–activity relationship analysis indicated that deprotected glycosyl derivatives exhibit improved inhibitory activity compared to protected analogues. To rationalize these observations, molecular docking followed by molecular dynamics simulations and MM-GBSA binding free energy calculations were performed for both anomeric forms of compound 10a. The computational results revealed a clear preference for the β-anomer, particularly in hCA IX and XII, where favorable interactions with catalytic threonine residues and isoform-specific aromatic residues stabilize the ligand within the active-site entrance. These findings provide a molecular explanation for the experimentally observed selectivity and highlight glycosyl coumarins as potential starting points for further optimization toward selective inhibitors of tumor-associated carbonic anhydrases. Full article

Human cytomegalovirus (HCMV) remains a significant cause of morbidity in immunocompromised patients, necessitating the development of improved antivirals. Using an integrated in silico and in vitro approach, we identified a novel ligand (NL) as a letermovir analog with enhanced binding affinity and reduced cytotoxicity. A pUL56 terminase subunit model generated with AlphaFold 3 was used for the virtual screening of a 15,000-compound library. Among the 73 candidates with structural similarity to letermovir (Tanimoto ≥ 0.6), NL exhibited superior predicted binding affinity (ΔG_bind = −10.7 kcal/mol). In silico toxicity prediction (ProTox 3.0) classified NL as having low toxicity (class 4, LD50 ≈ 1000 mg/kg), which was confirmed in vitro, where NL demonstrated 158-fold less toxic (CC50 = 2.69 mg/mL) in MRC-5 cells than letermovir (0.017 mg/mL). Molecular dynamics simulations over 500 ns revealed that the pUL56-NL complex forms a more thermodynamically stable interaction, with a lower calculated free energy of binding (MMGBSA: −40.89 ± 7.40 kcal/mol vs. −32.76 ± 4.96 kcal/mol) and a narrower free energy landscape. These results establish NL as a promising, low-cytotoxicity candidate with enhanced target engagement, warranting further investigation as a potential anti-HCMV therapeutic. Full article

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) enters host cells when the spike receptor-binding domain (RBD) engages angiotensin-converting enzyme 2 (ACE2). Cannabinoid scaffolds have recently been reported to bind S1/RBD, block spike-mediated membrane fusion, and modulate host inflammatory pathways, making them attractive candidates for entry inhibition. Here, we applied an integrated computational pipeline to prioritize cannabis-derived compounds as interfacial blockers of the RBD–ACE2 complex across variants. Eleven phytocannabinoids were docked into the wild-type (WT) RBD–ACE2 interface, identifying three cavities, with ligands preferentially occupying pocket 1. Complexes were subjected to triplicate 200 ns all-atom molecular dynamics (MD) simulations for WT, Delta, and Omicron BA.1 RBD–ACE2. Binding energetics were quantified using molecular mechanics/generalized Born surface area (MM/GBSA) and solvated interaction energy (SIE), and per-residue contributions were analyzed together with solvent-accessible surface area (SASA) and residue interaction networks. Among all compounds, cannabidiol (CBD) and cannabinol (CBN) were the only ligands that remained stably bound in pocket 1 for all variants. CBN showed the most favorable ligand–complex binding in WT, whereas CBD preserved favorable binding in Omicron BA.1 despite reduced interface burial, indicating that van der Waals/electrostatic complementarity and solvation, rather than surface coverage alone, govern affinity. Both ligands weakened modeled RBD–ACE2 binding by perturbing hot-spot residues centered on Y505 or N501Y in RBD and E37, A387, and R393 in ACE2. Overall, our results highlight CBD and CBN as tractable, variant-spanning interface disruptors and illustrate how MD-based free-energy calculations can support computational drug discovery against evolving viral protein–protein interfaces. Full article

Background/Objectives: Management of bipolar disorder is marked by variability in lithium response, with responders constituting a distinct clinical subgroup. Although pharmacogenetic studies implicate polymorphisms in neuroplasticity-related genes (BDNF) and hypothalamic–pituitary–adrenal (HPA) axis regulators (NR3C1), the underlying biophysical mechanisms remain poorly characterized. This study aims to bridge this structural–mechanistic gap by quantifying the atomic-level effects of key lithium-response polymorphisms on protein–protein interaction stability and conformational dynamics. Methods: Variant sequences for BDNF rs6265 and NR3C1 rs56149945 were generated and structurally modeled with SWISS-MODEL. Protein–protein interaction analyses focused on the BDNF–TrkB and NR3C1–FKBP5 systems. Structural alignment and conformational comparisons were performed with ChimeraX and US-align, while interaction energetics were evaluated with PRODIGY and HawkDock. Conformational flexibility was assessed using CABS-flex through RMSF analysis. Results: Structural validation showed acceptable model quality. Binding analyses indicated stronger interactions in the variant complexes. In the BDNF–TrkB complex, binding affinity shifted from −13.8 to −15.1 kcal/mol with an ~8.5-fold lower dissociation constant, while the NR3C1–FKBP5 variant complex shifted from −16.3 to −18.8 kcal/mol with an ~65-fold lower dissociation constant. MM/GBSA calculations supported increased stability, with binding energies changing from −61.98 to −83.91 kcal/mol (BDNF–TrkB) and from −18.88 to −31.25 kcal/mol (NR3C1–FKBP5). Structural superposition showed high conservation of global folds (pruned RMSD 0.779 Å and 0.310 Å; TM-scores 0.753 and 0.967). RMSF profiles were largely overlapping, indicating localized interface adjustments rather than global conformational changes. Conclusions: These findings suggest that lithium-response polymorphisms may modulate protein–protein interaction stability while preserving overall structure, providing a structural framework for exploring genetic influences on lithium treatment response. Full article

Respiratory syncytial virus (RSV) poses a substantial global health burden, particularly in infants and the elderly. The fusion (F) protein is a key therapeutic target for inhibiting RSV entry. In this study, we performed a structure-based virtual screening of the Comprehensive Marine Natural Products Database (CMNPD) to discover novel anti-RSV agents targeting the prefusion F protein trimer. Screening of 31,561 compounds via molecular docking, followed by stringent ADMET (absorption, distribution, metabolism, excretion, and toxicity) profiling and MM/GBSA (Molecular Mechanics/Generalized Born Surface Area) binding free energy calculations, identified 11 promising candidates. Among these, manzamine alkaloids exhibited the most favorable docking scores (as low as −13.3 kcal/mol) and promising Ligand Efficiency (LE) values. These molecules primarily interact with conserved hydrophobic residues (Phe140, Phe488) through hydrophobic interactions, π-stacking, and electrostatic forces. Our study highlights marine natural products, especially manzamine alkaloids, as promising leads for the development of novel, orally bioavailable RSV fusion inhibitors, potentially offering avenues to overcome existing drug resistance. However, these computational findings require in vitro validation to confirm efficacy. Full article

Background: Tubulin plays a pivotal role in cell division and other essential cellular processes, making it a key pharmacological target for cancer therapy, antiparasitic treatments, and neurodegenerative diseases. Numerous compounds have been developed to regulate microtubule polymerization through tubulin binding; however, most have shown significant limitations, including adverse side effects, poor bioavailability and limited specificity. In recent years, peptide-based therapies have gained considerable attention, particularly for their ability to modulate protein–protein interaction while offering improved selectivity and safety profiles. Methods: In this study, we employed an integrated computational–experimental approach combining molecular docking, molecular dynamics simulations, and MM-GBSA free energy calculations to design and evaluate 14 peptides derived from the αβ-tubulin dimer interface. Results: The peptide NH₂-P14-COOH emerged as the most promising candidate, displaying the stronger inhibition of tubulin polymerization activity (IC₅₀ = 11.24 ± 3.82 μM), selective cytotoxicity against NCI-H1299 lung carcinoma cells (IC₅₀ = 45.64 ± 3.20 μM), and no significant toxicity toward non-cancerous EA.hy926 endothelial cells (IC₅₀ > 100 μM). Flow cytometry analysis confirmed that NH₂-P14-COOH induces apoptosis, supporting a mechanism of action based on microtubule disruption. Conclusions: These findings highlight NH₂-P14-COOH as a selective antimitotic peptide with a favorable therapeutic index and demonstrate the potential of structure-guided peptide design for the development of novel microtubule-targeting agents with reduced off-target toxicity. Full article

Background: Skin cancer progression is driven by the dysregulation of key oncogenic signaling pathways, including EGFR, BRAF V600E, and TGF-β, which collectively promote tumor proliferation, invasion, and metastatic progression. Targeting these pathways using multitarget natural modulators represents a promising therapeutic strategy. Methods: In this study, forty-nine phytoconstituents from Cannabis sativa were evaluated using an integrated computational approach to explore their inhibitory potential against EGFR, BRAF V600E, and the TGF-β receptor. Molecular docking was performed to assess binding affinities and interaction profiles, followed by ADMET analysis to evaluate pharmacokinetic and safety properties. The top-ranked compounds were further investigated using 200 ns molecular dynamics simulations and MM-GBSA binding free energy calculations to assess the stability and strength of protein–ligand interactions. Results: Several phytoconstituents exhibited strong binding affinities toward the target proteins, formed stable interactions with key active-site residues, and demonstrated favorable pharmacokinetic profiles with acceptable safety characteristics. Molecular dynamics simulations confirmed the structural stability of the selected protein–ligand complexes, while MM-GBSA analysis supported their favorable binding energetics. Conclusions: These findings suggest that Cannabis sativa phytoconstituents may represent a promising source of multitarget modulators capable of attenuating EGFR, BRAF V600E, and TGF-β driven oncogenic signaling in skin cancer. This study provides a mechanistic framework that supports further in vitro validation and the development of cannabis-derived therapeutic candidates for targeted skin cancer management. Full article

Background: The SARS-CoV-2 3CLpro is essential for viral replication and an attractive target for antiviral intervention. While most strategies target the catalytic site, recent studies suggest that the dimerization interface and cryptic allosteric pockets offer alternative mechanisms for inhibition. Objective: This study investigated lipid metabolites from the marine sediment-derived Streptomyces sp. DSD454^T as potential multi-site 3CLpro inhibitors. Methods: Metabolites were extracted from cultured biomass and characterized using LCMS-QTOF, MS/MS (LCMS-TQ), and ¹H NMR, with identities confirmed against authentic standards. 3CLpro inhibition was assessed using a FRET-based assay, and ligand–protein interactions were evaluated through molecular docking and MM/GBSA calculations. Lipid content and comparative lipidomic signatures were examined across bioactive Streptomyces strains through LCMS-TQ and BODIPY^TM 493/503 staining. Results: Palmitoleic and linoleic acids were identified as major constituents and inhibited SARS-CoV-2 3CLpro with IC₅₀ values of 1.59 µg/mL (6.25 µM) and 5.29 µg/mL (18.88 µM). Molecular docking predicted that both fatty acids bind not only to the catalytic site but also to the dimerization interface and cryptic allosteric pocket. Additional lipids, including 9-heptadecenoic acid, linolenic acid, 9-HODE, and monoacylglycerols such as aggrecerides A–C and glyceryl-based lipids, showed similarly favorable multi-site binding profiles. Streptomyces sp. DSD454^T also exhibited substantial lipid accumulation (~63% of crude extract). Across bioactive Streptomyces strains, a conserved lipid signature correlated strongly with 3CLpro inhibition. Conclusions: This study highlights the potential of microbial lipids as promising scaffolds for developing catalytic and allosteric SARS-CoV-2 3CLpro inhibitors and underscore marine Streptomyces as a valuable source of structurally simple yet mechanistically versatile antiviral metabolites. Full article

Pseudomonas aeruginosa is a Gram-negative pathogen with a remarkable capacity to acquire multiple resistance mechanisms, severely limiting current therapeutic options. Consequently, the identification of new antimicrobial agents remains a critical priority. In this study, an integrated in silico-guided strategy was applied to identify small molecules with antibacterial potential against P. aeruginosa, targeting the quorum-sensing regulator LasR (PDB ID: 2UV0) and elastase (PDB ID: 1U4G). Pharmacophore modeling was performed for both targets, followed by ligand-based virtual screening, structure-based virtual screening (SBVS), and MM-GBSA (Molecular Mechanics-Generalized Born Surface Area) binding free energy calculations. Top-ranked compounds based on predicted binding affinity were selected for in vitro cytotoxicity and antibacterial evaluation. Antimicrobial activity was assessed against three P. aeruginosa strains: an American Type Culture Collection (ATCC) reference strain, a clinically susceptible isolate, and an extensively drug-resistant (XDR) clinical isolate. SBVS yielded docking scores ranging from −6.96 to −12.256 kcal/mol, with MM-GBSA binding free energies between −18.554 and −88.00 kcal/mol. Minimum inhibitory concentration (MIC) assays revealed that MolPort-001-974-907, MolPort-002-099-073, MolPort-008-336-135, and MolPort-008-339-179 exhibited MIC values of 62.5 µg/mL against the ATCC strain, indicating weak-to-moderate antibacterial activity consistent with early-stage hit compounds. MolPort-008-336-135 showed the most favorable activity against the clinically susceptible isolate, with an MIC of 62.5 µg/mL, while maintaining HepG2 cell viability above 70% at this concentration and an half-maximal inhibitory concentration (IC₅₀) greater than 500 µg/mL. In contrast, all tested compounds displayed MIC values above 62.5 µg/mL against the XDR isolate, reflecting limited efficacy against highly resistant strains. Overall, these results demonstrate the utility of in silico-driven approaches for the identification of antibacterial hit compounds targeting LasR and elastase, while highlighting the need for structure–activity relationship optimization to improve potency, selectivity, and activity against multidrug-resistant P. aeruginosa. Full article

Pseudomonas aeruginosa elastase LasB accelerates refrigerated food spoilage through proteolytic degradation of muscle and milk proteins. While Marrubium vulgare essential oil terpenes exhibit antimicrobial activity, their weak potency and nonspecificity limit direct food preservation applications. This computational study aimed to rationally redesign terpene scaffolds into predicted selective LasB inhibitors. A virtual library of 635 terpene–peptide–phosphinic acid hybrids (expanded to 3940 conformers) was evaluated using consensus molecular docking (Glide/Flare) against LasB (PDB: 3DBK) and three human off-target proteases. Top candidates underwent duplicate 150 ns molecular dynamics simulations with MM/GBSA binding free-energy calculations. Computational screening identified thymol–Leu–Trp–phosphinic acid as the lead candidate with predicted binding affinity of −12.12 kcal/mol, comparable to reference inhibitor phosphoramidon (−11.87 kcal/mol), and predicted selectivity index of +0.12 kcal/mol representing a 2.3 kcal/mol advantage over human proteases. Molecular dynamics simulations indicated exceptional stability (98.7% stable frames, 0.12 Å inter-replica RMSD) with consistent zinc coordination. Structure–activity analysis revealed phosphinic zinc-binding groups (+1.57 kcal/mol), Leu–Trp linkers (+2.47 kcal/mol), and phenolic scaffolds (+1.35 kcal/mol) as predicted optimal structural features. This in silico study provides a computational framework and prioritized candidate set for developing natural product-derived food preservatives. All findings represent computational predictions requiring experimental validation through enzymatic assays, food model studies, and toxicological evaluation. Full article

Background: The development of Multi-Target-Directed Ligands (MTDLs) has emerged as a significant strategy for addressing complex, overlapping pathologies such as cancer and Alzheimer’s disease (AD). This study aims to provide a robust computational framework for the design of dual-target inhibitors. Methods: This study presents an integrated and rigorous computational pipeline combining Quantitative Structure–Activity Relationship (QSAR) modeling, Molecular Docking, and Molecular Dynamics (MD) simulations with Dynamic Cross-Correlation Matrix (DCCM) analysis. Using a dataset of 57 known tubulin inhibitors, two high-performing QSAR models were developed to guide the rational design of 16 novel trimethoxyphenyl-based analogues. Results: Following ADMET and drug-likeness filtering, Lead Candidates 15 and 16 were identified. Quantitative activity predictions confirmed their enhanced potency thresholds, which were subsequently validated through static docking against β-tubulin (PDB: 4O2B) and Acetylcholinesterase (PDB: 1EVE). In total, 100 ns MD simulations and MM-GBSA calculations demonstrated superior binding stability and energetically favorable profiles for both targets, while DCCM analysis confirmed the functional synchrony of the protein–ligand complexes. Conclusions: The results provide a validated structural hypothesis for dual-target inhibition. The identified leads, 15 and 16, demonstrate strong predictive potential and are prioritized for chemical synthesis and in vitro biological evaluation. Full article

Background: Human noroviruses are the leading cause of foodborne gastroenteritis worldwide. Accumulating evidence suggests that food matrices containing fucosylated or histo-blood group antigen (HBGA)-like glycans may facilitate viral attachment and persistence, yet the molecular mechanisms underlying these interactions remain unclear. Methods: In this study, we performed a comparative computational analysis of norovirus–glycan interactions by integrating AlphaFold3-based structure prediction, molecular docking, and molecular dynamics simulations. A total of 182 P-domain models representing all genotypes across five human norovirus genogroups (GI, GII, GIV, GVIII, and GIX) were predicted and docked with a lettuce-derived core-fucosylated hexasaccharide (H₂N₂F₂) previously identified by our group. The three complexes exhibiting the most favorable docking energies were further examined using 40 ns molecular dynamics simulations, followed by MM/GBSA binding free energy calculations and per-residue decomposition analyses. Results: Docking results indicated that the majority of modeled P proteins were able to adopt energetically favorable interaction poses with H₂N₂F₂, with predicted binding energies ranging from −3.7 to −7.2 kcal·mol⁻¹. The most favorable docking energies were observed for GII.6_S9c_KC576910 (−7.2 kcal·mol⁻¹), GII.3_MX_U22498 (−7.1 kcal·mol⁻¹), and GII.4_CARGDS11182_OR700741 (−6.8 kcal·mol⁻¹). Molecular dynamics simulations suggested stable ligand engagement within canonical HBGA-binding pockets, with recurrent residues such as Asp374, Gln393, and Arg345 contributing to electrostatic and hydrophobic interactions, consistent with previously reported HBGA-binding motifs. MM/GBSA analyses revealed comparatively favorable binding tendencies among these complexes, particularly for globally prevalent genotypes including GII.3, GII.4, and GII.6. Conclusions: This work provides a large-scale structural and energetic assessment of the potential interactions between a naturally occurring lettuce-derived fucosylated hexasaccharide and human norovirus P domains. The results support the notion that core-fucosylated food-associated glycans can serve as interaction partners for diverse norovirus genotypes and offer comparative molecular insights into glycan recognition patterns relevant to foodborne transmission. The integrative AlphaFold3–docking–dynamics framework presented here may facilitate future investigations of virus–glycan interactions within food matrices. Full article

Background: Saffron (Crocus sativus L.) corms, often discarded as agricultural by-products, are a promising and sustainable source of bioactive metabolites with potential therapeutic relevance. However, their anticancer potential remains largely underinvestigated. Objectives: This study aimed to compare the phytochemical composition of hydroethanolic extracts from fresh (HEEF) and stored (HEES) saffron corms and to evaluate their anticancer effectiveness against colorectal cancer cells. Methods: Phytochemical profiling was performed using HPLC-ESI-QTOF-MS/MS. Cytotoxicity against T84 and SW480 colorectal cancer cell lines was determined by the crystal violet assay. Apoptosis-related protein modulation was assessed by Western blotting. Additionally, molecular docking, molecular dynamics simulations, and MM/GBSA calculations were used to investigate ligand–target binding affinities and stability. Results: Both extracts contained diverse primary and secondary metabolites, including phenolic acids, flavonoids, triterpenoids, lignans, anthraquinones, carotenoids, sugars, and fatty acids. HEES showed higher relative abundance of key bioactive metabolites than HEEF, which was enriched mainly in primary metabolites. HEES showed significantly greater dose-dependent cytotoxicity, particularly against SW480 cells after 24 h (IC₅₀ = 34.85 ± 3.35). Apoptosis induction was confirmed through increased expression of caspase-9 and p53 in T84 cells. In silico studies revealed strong and stable interactions of major metabolites, especially 3,8-dihydroxy-1-methylanthraquinone-2-carboxylic acid with COX2 and crocetin with VEGFR2. Conclusions: Stored saffron corms possess a richer bioactive profile and show enhanced anticancer effects in vitro compared with fresh saffron corms, suggesting that they may represent a promising source of compounds for the future development of colorectal cancer therapeutics. Full article