Metabolic disorders such as dyslipidemia and cholesterol-related diseases in pediatric populations have become a major concern, highlighting the need for effective therapeutic strategies. Liver X Receptor (LXR) is one of the key factors that control lipid metabolism and can be used as the treatment target. The aim of this study was to discover possible LXR inhibitors to use in pediatric metabolic disorders through an in-silico method, which combines molecular modeling, quantum chemical analysis, and molecular dynamics simulations. Molecular docking was performed to screen compounds from the ChEMBL database and quantum chemical analysis to determine electronic properties of the screened compounds. MD simulations over 100 ns confirmed the stability of the protein–ligand complex, supported by consistent RMSD, RMSF, and hydrogen bonding profiles. DFT analysis further indicated suitable electronic properties for receptor interaction. ADMET predictions suggested favorable pharmacokinetic and toxicity profiles. However, experimental validation is required to confirm the biological activity and therapeutic potential of the identified compounds. This study provides a computational framework for the discovery of LXR inhibitors targeting pediatric metabolic disorders.
Chen et al. (Thu,) studied this question.