Examining Prenylated Xanthones as Potential Inhibitors Against Ketohexokinase C Isoform for the Treatment of Fructose-Driven Metabolic Disorders: An Integrated Computational Approach.

Background/Objectives: Fructose-driven metabolic disorders, such as obesity, non-alcoholic fatty liver disease (NAFLD), dyslipidemia, and type 2 diabetes, are significant global health challenges. Ketohexokinase C (KHK-C), a key enzyme in fructose metabolism, is a promising therapeutic target. α-Mangostin, a naturally occurring prenylated xanthone, has been identified as an effective KHK-C inhibitor, prompting exploration of its analogs for enhanced efficacy. This study aimed to identify α-Mangostin analogs with improved inhibitory properties against KHK-C to address these disorders. Methods: A library of 1383 analogs was compiled from chemical databases and the literature. Molecular docking, binding free energy calculations, pharmacokinetic assessments, molecular dynamics simulations, and quantum mechani-cal analyses were used to screen and evaluate the compounds. α-Mangostin's binding affinity (37.34 kcal/mol) served as the benchmark. Results: Sixteen analogs demonstrated binding affinities superior to α-Mangostin (from -45.51 to -61.3 kcal/mol), LY-3522348 (-45.36 kcal/mol), and reported marine-derived inhibitors (from -22.74 to -51.83 kcal/mol). Hits 7, 8, 9, 13, and 15 not only surpassed these benchmarks in binding affinity, but also exhibited superior pharmacokinetic properties compared to α-Mangostin, LY-3522348, and marine-derived inhibitors, indicating strong in vivo potential. Among these, hit 8 emerged as the best performer, achieving a binding free energy of -61.30 kcal/mol, 100% predicted oral absorption, enhanced metabolic stability, and stable molecular dynamics. Conclusions: Hit 8 emerged as the most promising candidate due to its superior binding affinity, favorable pharmacokinetics, and stable interactions with KHK-C. These findings highlight its potential for treating fructose-driven metabolic disorders, warranting further experimental validation.