Development of Novel Inhibitors for Alzheimer's Disease from Erythrina variegata L. Extract-Derived Clusters Using Molecular Docking, QSAR Modeling, Quantum Chemical Calculations, and Molecular Dynamics Simulations
Abstract
The objective of this investigation is to identify and enhance compounds from the medicinal plant Erythrina variegata L. that possess potential inhibitory activity against acetylcholinesterase (AChE). Consequently, this investigation will contribute to the pursuit of supportive therapeutic agents for Alzheimer's disease. The initial research matrix was composed of nanocluster materials that were derived from the crude extract. The identification of 13 compounds was achieved by utilizing an ultraperformance liquid chromatography system in conjunction with quadrupole time-of-flight mass spectrometry for structural elucidation. Compound VN62 was chosen due to its favorable binding energy (ES = -8.038 kcal/mol) and RMSD = 1.388 Å, as evidenced by molecular docking simulations and analytical results with the AChE protein (PDB ID: 1EVE). The pIC50 values were predicted using reliable QSAR models, such as QSARGA‑MLR, QSARGA‑ANN, and QSARKPLS‑LF, which were constructed on this basis. Five novel derivatives (VN62N1-VN62N5) were designed from VN62, subsequently semisynthesized, and structurally confirmed using spectroscopic methods, guided by QSAR and docking results. The AChE inhibitory activity was assessed in vitro, and VN62 demonstrated an IC50 of 1.34 μg/mL (pIC50 = 5.498). Conversely, the newly designed derivatives demonstrated a trend toward enhanced activity. Furthermore, a multicriteria evaluation model integrating QSAR, docking, ADMET, and quantum descriptors identified…
Read the paper
Related studies
- Chaos and quantum thermalization
- The Dalton quantum chemistry program system
- Cord Blood Leptin and Adiponectin as Predictors of Adiposity in Children at 3 Years of Age: A Prospective Cohort Study
- Quantitative metabolomics by H-NMR and LC-MS/MS confirms altered metabolic pathways in diabetes
- Stable adiabatic quantum batteries
- A novel self-lipid antigen targets human T cells against CD1c(+) leukemias
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.