Acetylcholinesterase (AChE) is one of the main drug targets for treating Alzheimer’s disease. This current study relies on multiple molecular modeling approaches to develop new potent inhibitors of AChE. We explored a 2D QSAR study using the statistical method of multiple linear regression based on a set of substituted 5-phenyl-1,3,4-oxadiazole and N-benzylpiperidine analogs, which were recently synthesized and proved their inhibitory activities against acetylcholinesterase (AChE). The molecular descriptors, polar surface area, dipole moment, and molecular weight are the key structural properties governing AChE inhibition activity. The MLR model was selected based on its statistical parameters: R² = 0.701, R²test = 0.76, Q²CV = 0.638, and RMSE = 0.336, demonstrating its predictive reliability. Randomization tests, VIF tests, and applicability domain tests were adopted to verify the model’s robustness. As a result, 11 new molecules were designed with higher anti-Alzheimer’s activities than the model molecule. We demonstrated their improved pharmacokinetic properties through an in silico ADMET study. A molecular docking study was conducted to explore their AChE inhibition mechanisms and binding affinities in the active site. The binding scores of compounds M1, M2, and M6 were (−12.6 kcal/mol), (−13 kcal/mol), and (−12.4 kcal/mol), respectively, which are higher than the standard inhibitor Donepezil with a binding score of (−10.8 kcal/mol). Molecular dynamics simulations over 100 ns were used to validate the molecular docking results, indicating that compounds M1 and M2 remain stable in the active site, confirming their potential as promising anti-AChE inhibitors.

In response to the increasing prevalence of diabetes mellitus and the limitations associated with the current treatments, there is a growing need to develop novel medications for this disease. This study is focused on creating new compounds that exhibit a strong inhibition of alpha-glucosidase, which is a pivotal enzyme in diabetes control. A set of 33 triazole derivatives underwent an extensive QSAR analysis, aiming to identify the key factors influencing their inhibitory activity against α-glucosidase. Using the multiple linear regression (MLR) model, seven promising compounds were designed as potential drugs. Molecular docking and dynamics simulations were employed to shed light on the mode of interaction between the ligands and the target, and the stability of the obtained complexes. Furthermore, the pharmacokinetic properties of the designed compounds were assessed to predict their behavior in the human body. The binding free energy was also calculated using MMGBSA method and revealed favorable thermodynamic properties. The results highlighted three novel compounds with high biological activity, strong binding affinity to the target enzyme, and suitability for oral administration. These results offer interesting prospects for the development of effective and well-tolerated medications against diabetes mellitus.

Background: Angiogenesis is a crucial process in the growth and proliferation of cancer, enabling tumor growth through the formation of new vasculature and the supply of nutrients and oxygen to growing malignant cells. This disease-promoting process can be targeted through the inhibition of tyrosine kinase enzymes. Objectives: The objective of this study is to evaluate the anticancer potential of various Moroccan plants from different regions. While these plants have a rich history of traditional medicinal use, they have not been extensively investigated as anticancer therapies. Methods: This study employed a multifaceted approach to evaluate the anticancer potential of various Moroccan plants. Receptor–ligand docking and virtual screening were used to assess the binding affinity of phytocompounds to the EGFR and VEGFR2 receptors. Additionally, predictive pharmacokinetic analyses were conducted to evaluate the ADMET properties of the selected compounds, followed by molecular dynamics simulations to analyze the stability of the receptor–ligand complexes. Results: In our research, we identified three notable active compounds—catechin, 4-O-glucoside ferulic acid, and 3-glucoside resveratrol—in the Moroccan plant Ajuga iva L. These findings suggest that Ajuga iva L. may possess significant potential for cancer inhibition. Conclusions: This research highlights the potential of the Moroccan plant Ajuga iva L. as a source of active compounds with significant anticancer properties. Further investigation is essential to validate these findings and explore new therapeutic avenues based on these traditional resources.

Candida albicans and Aspergillus fumigatus are recognized as significant fungal pathogens, responsible for various human infections. The rapid emergence of drug-resistant strains among these fungi requires the identification and development of innovative antifungal therapies. We undertook a comprehensive screening of 297 naturally occurring compounds to address this challenge. Using computational docking techniques, we systematically analyzed the binding affinity of each compound to key proteins from Candida albicans (PDB ID: 1EAG) and Aspergillus fumigatus (PDB ID: 3DJE). This rigorous in silico examination aimed to unveil compounds that could potentially inhibit the activity of these fungal infections. This was followed by an ADMET analysis of the top-ranked compound, providing valuable insights into the pharmacokinetic properties and potential toxicological profiles. To further validate our findings, the molecular reactivity and stability were computed using the DFT calculation and molecular dynamics simulation, providing a deeper understanding of the stability and behavior of the top-ranking compounds in a biological environment. The outcomes of our study identified a subset of natural compounds that, based on our analysis, demonstrate notable potential as antifungal candidates. With further experimental validation, these compounds could pave the way for new therapeutic strategies against drug-resistant fungal pathogens.

Alzheimer’s disease (AD) is a multifactorial neurodegenerative disorder characterized by cholinergic dysfunction, amyloid-β aggregation, mitochondrial stress, and aberrant kinase activity. Carotenoids, naturally occurring pigments with antioxidant and neuroprotective properties, have emerged as promising candidates for AD intervention. In this study, we performed a systematic stepwise computational screening of a large carotenoid library (n = 1191) to identify multitarget candidates against AD–related proteins. The workflow consisted of predefined ADMET filtering (oral absorption > 90%, Caco-2 > 0.9, logBB > −1, and absence of major CYP inhibition and toxicity alerts), reducing the dataset to 61 compounds, followed by multi-target molecular docking against AChE, BChE, BACE-1, MAO-B, and GSK3-β. Compounds were ranked using an aggregated mean docking score across all five targets, and the top-performing candidate was subjected to detailed mechanistic analyses. Hopkinsiaxanthin emerged as the highest-ranked multitarget carotenoid and was further evaluated using frontier molecular orbital (FMO) analysis, pharmacophore modeling, 100 ns molecular dynamics (MD) simulations, MM/PBSA binding free energy calculations, and per-residue decomposition. Docking predicted favorable estimated binding affinities toward all targets. MD simulations confirmed stable receptor–ligand complexes with low RMSD values (0.278–0.285 nm). MM/PBSA analysis indicated favorable binding free energies, particularly for GSK3-β (−22.73 kcal/mol) and AChE (−21.50 kcal/mol). Per-residue decomposition identified key hotspot residues driving stabilization. Overall, this structured computational framework identifies Hopkinsiaxanthin as a promising multitarget scaffold and supports its prioritization for experimental validation in AD models.

The African boxthorn (Lycium ferocissimum) is a medicinal plant belonging to the Solanaceae family that is used in traditional pharmacopeia. Here, its biological potential was assessed by analyzing the essential oil from its leaves (EOLF), extracted by hydro-distillation and major terpenes characterized by gas chromatography coupled to mass spectrometry (GC-MS). GC-MS analysis of EOLF identified fourteen compounds representing 99.95% of the total mass, which was dominated by carvacrol (35.96%) and sabinene (17.06%). EOLF exhibited antioxidant activity as characterized by several assays, including 2,2-diphenyl-1-picrylhydrazyl (DPPH), Ferric Reducing Antioxidant Power (FRAP), Total Antioxidant Capacity (TAC) and the β-carotene/linoleic acid test. According to the results obtained, EOLF exhibited antioxidant activity, as measured by the DPPH assay, with a mean IC₅₀ of 96 µg/mL, which is relatively close to that of quercetin (74 µg/mL) and BHT (49.16 µg/mL). Furthermore, the activity assessed using the FRAP method showed an EC₅₀ of 282 µg/mL, comparable to that of BHT (292 µg/mL). Based on the results of the TAC method, the antioxidant activity was 880 ± 4 µg AAE/mg, while the efficacy for inhibition of β-carotene was 80%. Effective antimicrobial activity against several bacterial and fungal strains was assessed by measuring inhibition zones and Minimum Inhibitory Concentrations (MICs). EOLF exhibited significant antimicrobial activity, particularly against Klebsiella pneumoniae, with an inhibition zone of 25.08 ± 0.93 mm and an MIC of 15.68 ± 0.83 µg/mL. For Staphylococcus aureus, an inhibition zone of 23.84 ± 0.88 mm and an MIC of 11.03 ± 0.27 µg/mL were recorded. Strong antifungal activity was also observed against Candida albicans, with an inhibition zone of 22.55 ± 0.87 mm and an MIC of 10.51 ± 0.47 µg/mL. The conducted in-silico analysis confirmed the affinity of the main compounds with key biological targets, suggesting their likely roles in the observed antimicrobial effects. The ADEM-Tox properties demonstrated that the analyzed compounds would only be lethal at very great concentrations, indicating low acute toxicity, and would not be expected to elicit toxic effects at therapeutic doses.