Search Results (6)

Helicobacter pylori urease (HpU) plays a central role in bacterial survival and virulence by hydrolyzing urea into ammonia and carbon dioxide, neutralizing gastric acidity, and facilitating host colonization. The increasing prevalence of antibiotic resistance underscores the need for alternative strategies targeting essential bacterial enzymes such as urease. In this study, a multistage computational pipeline integrating pharmacophore modeling, machine learning (ML), ensemble docking, and enhanced molecular dynamics simulations were applied to identify novel triazole-based HpU inhibitors. Starting from over seven million compounds in the ZINC15 database, pharmacophore- and ML-based filters progressively reduced the chemical space to 7062 candidates. Ensemble docking across 25 conformational frames of HpU, followed by quantum-polarized ligand docking (QPLD), identified seven promising ligands exhibiting strong binding energies and stable metal coordination. Molecular dynamics (MD) simulations under progressively relaxed restraints revealed three highly stable complexes (CA1, CA3, and CA6). Subsequent well-tempered metadynamics (WT-MetaD) simulations reconstructed free-energy landscapes showing deep, localized basins for CA3 and CA6, comparable to the potent reference inhibitor DJM, supporting their potential as strong urease binders. Finally, unsupervised chemical space mapping using the UMAP algorithm positioned these candidates within molecular regions associated with potent urease inhibitors, further validating their structural coherence and pharmacophoric relevance. An ADMET assessment confirmed that the selected candidates exhibit physicochemical and early safety properties compatible with subsequent in vitro evaluation. This multilevel screening strategy demonstrates the power of combining ML-driven classification, ensemble docking, and enhanced sampling simulations to discover non-hydroxamic urease inhibitors. Although the current findings are computational, they provide a rational foundation for future in vitro validation and for expanding the discovery of triazole-based scaffolds targeting ureolytic enzymes. Full article

Background/Objectives: In this work, a series of six new indazole-benzimidazole hybrids (M1–M6) were designed, synthesized, and fully characterized. The design of these compounds was based on the combination of two pharmacophoric units, indazole and benzimidazole, both known for their broad spectrum of biological activities. Methods: The molecular hybridization strategy was planned to combine these scaffolds through an effective synthetic pathway, using 6-nitroindazole, two 2-mercaptobenzimidazoles, and 1,3- or 1,5-dihaloalkanes as key precursors, affording the desired hybrids in good yields and with enhanced biological activity. Quantum chemical calculations were performed to investigate the structural, electronic, and electrostatic properties of M1–M6 molecules using Density Functional Theory (DFT) at the B3LYP/6-311++G(d,p) level. The antimicrobial activity efficacy of these compounds was assessed in vitro against four Gram-positive bacteria (Staphylococcus aureus, Enterococcus faecalis, Bacillus cereus, and Lactobacillus plantarum), four Gram-negative bacteria (Salmonella enteritidis, Escherichia coli, Campylobacter coli, Campylobacter jejuni), and four fungal strains (Saccharomyces cerevisiae, Candida albicans, Candida tropicalis, and Candida glabrata) using ampicillin and tetracycline as reference standard drugs. Results: Among the series, compound M6 exhibited remarkable antimicrobial activity, with minimum inhibitory concentrations (MIC) of 1.95 µg/mL against S. cerevisiae and C. tropicalis, and 3.90 µg/mL against S. aureus, B. cereus, and S. enteritidis, while the standards Ampicillin (AmB) (MIC ≥ 15.62 µg/mL) and Tetracycline (TET) (MIC ≥ 7.81 µg/mL) exhibited higher MIC values. To gain molecular insights into the compounds, an in silico docking study was performed to determine the interactions of M1–M6 ligands against the antimicrobial target beta-ketoacyl-acyl carrier protein (ACP) synthase III complexed with malonyl-COA (PDB ID: 1HNJ). Molecular modeling data provided valuable information on the structure-activity relationship (SAR) and the binding modes influencing the candidate ligand-protein recognition. Amino acid residues, such as Arg249, located in the solvent-exposed region, were essential for hydrogen bonding with the nitro group of the 6-nitroindazole moiety. Furthermore, polar side chains such as Asn274, Asn247, and His244 participated in interactions mediated by hydrogen bonding with the 5-nitrobenzimidazole moiety of these compound series. Conclusions: The hybridization of indazole and benzimidazole scaffolds produced compounds with promising antimicrobial activity, particularly M6, which demonstrated superior potency compared to standard antibiotics. Computational and docking analyses provided insights into the structure–activity relationships, highlighting these hybrids as potential candidates for antimicrobial drug development. Full article

The need to solvate and encapsulate hydro-sensitive molecules drives noticeable trends in the applications of cyclodextrins in the pharmaceutical industry, in foods, polymers, materials, and in agricultural science. Among them, β-cyclodextrin is one of the most used for the entrapment of phenolic acid compounds to mask the bitterness of wheat bran. In this regard, there is still a need for good data and especially for a robust predictive model that assesses the bitterness masking capabilities of β-cyclodextrin for various phenolic compounds. This study uses a dataset of 20 phenolic acids docked into the β-cyclodextrin cavity to generate three different binding constants. The data from the docking study were combined with topological, topographical, and quantum-chemical features from the ligands in a machine learning-based structure–activity relationship study. Three different models for each binding constant were computed using a combination of the genetic algorithm (GA) and multiple linear regression (MLR) approaches. The developed ML/QSAR models showed a very good performance, with high predictive ability and correlation coefficients of 0.969 and 0.984 for the training and test sets, respectively. The models revealed several factors responsible for binding with cyclodextrin, showing positive contributions toward the binding affinity values, including such features as the presence of six-membered rings in the molecule, branching, electronegativity values, and polar surface area. Full article

Currently, G protein-coupled receptors (GPCRs) constitute a significant group of membrane-bound receptors representing more than 30% of therapeutic targets. Fluorine is commonly used in designing highly active biological compounds, as evidenced by the steadily increasing number of drugs by the Food and Drug Administration (FDA). Herein, we identified and analyzed 898 target-based F-containing isomeric analog sets for SAR analysis in the ChEMBL database—F_iSAR sets active against 33 different aminergic GPCRs comprising a total of 2163 fluorinated (1201 unique) compounds. We found 30 F_iSAR sets contain activity cliffs (ACs), defined as pairs of structurally similar compounds showing significant differences in affinity (≥50-fold change), where the change of fluorine position may lead up to a 1300-fold change in potency. The analysis of matched molecular pair (MMP) networks indicated that the fluorination of aromatic rings showed no clear trend toward a positive or negative effect on affinity. Additionally, we propose an in silico workflow (including induced-fit docking, molecular dynamics, quantum polarized ligand docking, and binding free energy calculations based on the Generalized-Born Surface-Area (GBSA) model) to score the fluorine positions in the molecule. Full article

Polyphenols are a large family of naturally occurring phytochemicals. Herein, oxyresveratrol was isolated from ethanolic crude extracts of Artocarpus lacucha Buch.-Ham., and chemically modified to derive its lipophilic analogues. Biological screening assays showed their inhibitory potency against cyclooxygenase-2 (COX-2) with very low cytotoxicity to the MRC-5 normal cell lines. At the catalytic site of COX-2, docking protocols with ChemPLP, GoldScore and AutoDock scoring functions were carried out to reveal hydrogen bonding interactions with key polar contacts and hydrophobic pi-interactions. For more accurate binding energetics, COX-2/ligand complexes at the binding region were computed in vacuo and implicit aqueous solvation using M06-2X density functional with 6-31G+(d,p) basis set. Our computational results confirmed that dihydrooxyresveratrol (4) is the putative inhibitor of human COX-2 with the highest inhibitory activity (IC₅₀ of 11.50 ± 1.54 µM) among studied non-fluorinated analogues for further lead optimization. Selective substitution of fluorine provides a stronger binding affinity; however, lowering the cytotoxicity of a fluorinated analogue to a normal cell is challenging. The consensus among biological activities, ChemPLP docking score and the binding energies computed at the quantum mechanical level is obviously helpful for identification of oxyresveratrol analogues as a putative anti-inflammatory agent. Full article

Malolactic fermentation (MLF) is responsible for the decarboxylation of l-malic into lactic acid in most red wines and some white wines. It reduces the acidity of wine, improves flavor complexity and microbiological stability. Despite its industrial interest, the MLF mechanism is not fully understood. The objective of this study was to provide new insights into the role of pH on the binding of malic acid to the malolactic enzyme (MLE) of Oenococcus oeni. To this end, sequence similarity networks and phylogenetic analysis were used to generate an MLE homology model, which was further refined by molecular dynamics simulations. The resulting model, together with quantum polarized ligand docking (QPLD), was used to describe the MLE binding pocket and pose of l-malic acid (MAL) and its l-malate (−1) and (−2) protonation states (MAL⁻ and MAL²⁻, respectively). MAL²⁻ has the lowest ∆G_binding, followed by MAL⁻ and MAL, with values of −23.8, −19.6, and −14.6 kJ/mol, respectively, consistent with those obtained by isothermal calorimetry thermodynamic (ITC) assays. Furthermore, molecular dynamics and MM/GBSA results suggest that only MAL²⁻ displays an extended open conformation at the binding pocket, satisfying the geometrical requirements for Mn²⁺ coordination, a critical component of MLE activity. These results are consistent with the intracellular pH conditions of O. oeni cells—ranging from pH 5.8 to 6.1—where the enzymatic decarboxylation of malate occurs. Full article