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Computational insights into oxysterols: MD and DFT applications in pharmaceutical research
Jan Kobierski1, Michał Świątek2, Wojciech Jawień2
1Faculty of Pharmacy, Jagiellonian University Medical College, Kraków, Poland. jan.kobierski@uj.edu.pl.
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Oxysterols, the oxidized derivatives of cholesterol, are biologically active molecules involved in a wide range of physiological and pathological processes. Small structural changes in the cholesterol backbone (such as additional hydroxyl or keto groups on the sterol rings or side chain) dramatically alter their biological effects, ranging from beneficial roles in cholesterol homeostasis and antiviral acivity to harmful contributions to diseases like atherosclerosis, neurodegeneration, and cancer. Molecular dynamics (MD) simulations and density functional theory (DFT) calculations have emerged as powerful tools to investigate these molecules at an atomic level. By complementing experimental studies, computational approaches reveal how oxysterols interact with membrane lipids, providing mechanistic insight into their function. This review highlights key findings from MD and DFT studies on various oxysterols - including 7-hydroxycholesterol epimers, 7-ketocholesterol, 22-hydroxycholesterol epimers, 24(S)-, 25- and 27-hydroxycholesterol - in the context of pharmaceutical and medical research. We discuss how these methods uncovered differences in orientation, hydration, and intermolecular interactions of oxysterols in model membranes, lipid rafts, and complexes, explaining phenomena such as membrane domain destabilization or stabilization, rapid transbilayer "flip-flop" translocation, and stereochemistry-dependent biological activity. Understanding these molecular details is crucial for pharmacists and medical researchers, as it connects oxysterol structure-function relationships to their roles as potential biomarkers, therapeutic targets, or bioactive compounds involved in disease pathophysiology. Computational chemistry thus provides a valuable complement to experimental pharmacology, enabling the prediction of oxysterol behavior in biological systems.
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