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.

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.

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.

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.