Imane Yamari

The valorization of natural terpenes derived from Cedrus atlantica provides a sustainable pathway for the development of novel antiviral scaffolds. In this study, three new sesquiterpenes 4- (4-methylcyclohex-3-enyl)pent-3-en-2-one (1), 7-isopropyl-4,10-dimethylbicyclo[4,4,0]dec-4-en-1- ol (2), and 4-(1-hydroxy-4-methylcyclohex-3-en-1-yl)pent-3-en-2-one (3), were isolated from C. atlantica essential oil and structurally elucidated by 1H and 13C Nuclear Magnetic Resonance (NMR) spectroscopy. Semisynthetic modifications of these natural scaffolds yielded a series of seven-value terpene derivatives with enhanced chemical diversity. To rationalize and predict their antiviral potential, a comprehensive in silico workflow was employed, integrating structure-based molecular docking, pharmacokinetic profiling, and molecular dynamics simulation. The docked complexes with Human Immunodeficiency Virus (HIV-1) protease revealed strong binding affinities, with compounds 5 and 7 surpassing the FDA-approved inhibitor Fosamprenavir (ΔG = -8.6 kcal mol⁻¹ vs -7.8 kcal mol⁻¹). Absorption, Distribution, Metabolism, Excretion and Toxicology (ADME-Tox) profiling confirmed excellent oral bioavailability, metabolic stability, and absence of predicted toxicity, while 100 ns molecular dynamics simulations demonstrated stable protein-ligand interactions under nearphysiological conditions. Collectively, our findings establish C. atlantica as a reservoir of bioactive scaffolds and compound 7 as a lead HIV-1 protease inhibitor, exemplifying the synergy between natural product chemistry and in silico drug design.

Background/Objectives: Chromium contamination represents a major environmental challenge due to its detrimental effects on plant growth and agricultural productivity. Since dichromate uptake in plants occurs mainly through sulfate and phosphate transporters, identifying natural compounds capable of competitively inhibiting these transport pathways may provide an eco-friendly strategy for reducing chromium accumulation. This study aimed to investigate the inhibitory potential of phytochemicals from Djiboutian medicinal plants against sulfate and phosphate transporters using an integrated computational approach. Methods: 49 phytochemicals identified by GC–MS from ten Djiboutian medicinal plants were screened against the sulfate transporter (7LHV) and phosphate transporter (7SP5) using molecular docking. Binding interactions were compared with sulfate, phosphate, and dichromate ions to evaluate potential competitive inhibition. The most promising compounds were further assessed through ADMET prediction and 100 ns molecular dynamics simulations to evaluate their pharmacokinetic properties and complex stability. Results: Molecular docking revealed binding energies ranging from −7.04 to −2.91 kcal/mol for 7LHV and from −6.50 to −0.62 kcal/mol for 7SP5, indicating variable binding affinities among the screened phytochemicals. Several compounds exhibited favorable interactions with key amino acid residues involved in anion transport, suggesting their potential to compete with dichromate uptake. ADMET analysis identified multiple compounds with favorable toxicity and drug-likeness profiles. Among them, cyclohexanepropanoic acid from Aloe djiboutiensis demonstrated the strongest binding affinity toward both transporters. Molecular dynamics simulations confirmed the structural stability of the protein–ligand complexes throughout the 100 ns simulation. Conclusions: This study identifies naturally occurring phytochemicals, particularly cyclohexanepropanoic acid, as promising competitive inhibitors of dichromate transport in plants. These findings provide a theoretical foundation for developing sustainable phytochemical-based strategies to mitigate chromium accumulation in crops and support future experimental validation.

Diabetes mellitus remains a major metabolic disorder requiring the development of new and effective α-glucosidase inhibitors. The present study aimed to identify, design, and optimize novel 3-amino-2,4-diarylbenzo[4,5]imidazo[1,2-α]pyrimidine derivatives with promising inhibitory activity against the α-glucosidase enzyme using a comprehensive in silico strategy. Approximately 300 molecular descriptors were calculated to characterize a dataset of 32 compounds (Peytam et al.) and to investigate the structural factors governing their biological activity. Based on these descriptors, a multiple linear regression model was developed to predict the inhibitory activities of the compounds against alpha-glucosidase. The developed model demonstrated satisfactory predictive performance and was internally and externally validated to ensure its accuracy, robustness, and reproducibility. In addition, the applicability domain analysis confirmed the reliability of the predictions. Using the validated QSAR model, seven new derivatives were designed with predicted pIC₅₀ values exceeding the maximum activity of the parent compounds. The leverage analysis demonstrated that all newly designed compounds were located within the applicability domain of the model, supporting the reliability of the predictions. To further evaluate their inhibitory potential, molecular docking studies were performed to investigate the interactions between the designed compounds and the α-glucosidase active site. The docking results revealed favorable binding interactions comparable to those reported for known α-glucosidase inhibitors. Furthermore, ADMET analysis indicated generally favorable pharmacokinetic properties, although potential CYP3A4 inhibition-related pharmacokinetic risks were identified and discussed. Molecular dynamics simulations, including replicated runs and MM/GBSA binding free energy calculations, confirmed the stability of the most promising protein–ligand complexes throughout the simulation period. In conclusion, this study proposes a robust and integrated computational workflow combining descriptor generation, QSAR modeling, applicability domain analysis, molecular docking, ADMET prediction, and molecular dynamics simulations for the rational design of potential α-glucosidase inhibitors. The findings highlight the therapeutic potential of the designed derivatives and provide a valuable in silico framework for the future development of antidiabetic agents.

Objectives: Visceral leishmaniasis (VL), caused by Leishmania donovani and Leishmania infantum, is a life-threatening neglected tropical disease, particularly in endemic regions such as Djibouti. Current therapies are constrained by toxicity, high cost, and limited availability, highlighting the urgent need for safe, effective, and affordable alternatives. This study aimed to identify novel antileishmanial candidates from Djiboutian medicinal plants using an integrated in silico approach. Methods: A total of 136 phytoconstituents isolated from local medicinal plants were screened via molecular docking against validated protein targets (6UAK and 2JK6). Promising candidates were further analyzed for interaction patterns, drug-likeness according to Lipinski’s Rule of Five, and ADMET properties. Molecular dynamics (MD) simulations over 100 ns were performed to assess the structural stability of selected protein–ligand complexes. Results: Compound C41 emerged as a leading candidate, showing binding affinities of −8.3 kcal/mol and −7.5 kcal/mol toward 6UAK and 2JK6, respectively, comparable to reference drugs. Interaction analysis revealed stable hydrogen bonds and hydrophobic contacts within the catalytic sites. Drug-likeness assessment confirmed compliance with Lipinski’s Rule, while ADMET predictions indicated high intestinal absorption and favorable safety profiles for several candidates. MD simulations corroborated the structural stability of the 2JK6-C41 complex throughout the 100 ns trajectory. Conclusions: These findings underscore Djiboutian medicinal plants as a valuable source of potential antileishmanial leads. Among them, Compound C41 represents a promising candidate for future experimental validation, supporting the development of innovative, safe, and cost-effective therapies against visceral leishmaniasis.

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.

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.

Background/Objectives: Diabetes mellitus is a serious global disease characterized by chronic hyperglycemia, resulting from defects in insulin secretion, insulin action, or both. It represents a major health concern affecting millions of people worldwide. This condition can lead to severe complications significantly affecting patients’ quality of life. Due to the limitations and side effects of current therapies, the search for safer and more effective antidiabetic agents, particularly from natural sources, has gained considerable attention. This study investigates the antidiabetic potential of seaweed-derived compounds through structure-based virtual screening targeting α-glucosidase. Methods: A library of compounds derived from the Seaweed Metabolite Database was subjected to a hierarchical molecular docking protocol against α-glucosidase. Extra Precision (XP) docking was employed to identify the top-ranked ligands based on their binding affinities. Drug-likeness was assessed according to Lipinski’s Rule of Five, followed by pharmacokinetic and toxicity predictions to evaluate ADMET properties. Density Functional Theory (DFT) calculations were performed to analyze the electronic properties and chemical reactivity of the selected compounds. Furthermore, molecular dynamics simulations were carried out to examine the stability and dynamic behavior of the ligand–enzyme complexes. Results: Following XP docking and ADMET prediction, four promising compounds were selected: Colensolide A, Rhodomelol, Callophycin A, and 7-(2,3-dibromo-4,5-dihydroxybenzyl)-3,7-dihydro-1H-purine-2,6-dione. Molecular dynamics simulations further confirmed the structural stability and strong binding interactions of these compounds within the α-glucosidase active site. Conclusions: This investigation demonstrated the important role of seaweed-derived compounds in inhibiting α-glucosidase activity. Further experimental validation is warranted to confirm their biological activity and therapeutic potential.

This study aims to repurpose sericin in combating non-small lung cancer cells (A549 and H460) by combining it with dactolisib or vitamin D to reduce the dose of dactolisib and boost the anticancer effectiveness of dactolisib and vitamin D. Therefore, the binding affinities of individual and combined drugs were examined using in silico and protein-protein interaction studies, targeting NF-κB, Cyclin D1, p-AKT, and VEGF1 proteins. The findings manifested remarkable affinities for combinatorial drugs compared to individual compounds. To substantiate these findings, the combined IC₅₀ for each combination (sericin + dactolisib and sericin + vitamin D) were determined, reporting 31.9 and 41.8 µg/ml, respectively, against A549 cells and 47.9 and 55.3 µg/ml, respectively, against H460 cells. Furthermore, combination indices were assessed to lower the doses of each drug. Interestingly, in vitro results exhibited marked diminutions in NF-κB, Cyclin D1, p-AKT, and VEGF1 after treatment with sericin + dactolisib and sericin + vitamin D compared to control lung cancer cells and those treated with a single drug. Moreover, A549 and H460 cells treated with both combinations demonstrated augmented caspase-3 levels, implying substantial apoptotic activity. Altogether, these results accentuated the prospective implementation of sericin in combination with dactolisib and vitamin D at low doses to preclude lung cancer cell proliferation.

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.