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Molecular Insights into the Interaction of Orexin 1 Receptor Antagonists: A Comprehensive Study Using Classical and
Caio Sena1, Pedro Albuquerque1, Jonas Oliveira2
1Instituto de Química, Universidade Federal do Rio Grande do Norte, Natal 59072-970, RN, Brazil.
None:
Sleep disorders, such as insomnia and narcolepsy, significantly impact quality of life. They are often associated with long-term health consequences, including cardiovascular disease, immune dysfunction, and cognitive impairment. While traditional treatments, such as sedatives and hypnotics, can be effective, they are limited by issues of tolerance and dependence. The orexinergic system, particularly the orexin 1 receptor (OXR1), has emerged as a promising therapeutic target due to its central role in regulating sleep-wake cycles. In this study, we investigate the molecular interactions of three OXR1 antagonists-daridorexant, lemborexant, and suvorexant-using an integrated computational approach combining molecular dynamics (MD) simulations, density functional theory (DFT) calculations, and the molecular fractionation with conjugate caps (MFCC) methodology. The MFCC approach enabled the precise quantification of interaction energies between ligands and key receptor residues, providing detailed insights into the contributions of specific amino acids to binding stability. Our results reveal that residues such as GLU204, HIS216, and ASN318 play critical roles in stabilizing ligand-receptor interactions, with a marked decrease in binding energy magnitude as dielectric constants increase. Daridorexant exhibited the strongest interaction energy, driven by hydrogen bonds and hydrophobic contacts, while lemborexant and suvorexant showed distinct stabilization patterns mediated by hydrophobic interactions. These findings provide a robust molecular basis for the rational design of next-generation OXR1 antagonists with improved efficacy and safety profiles. By elucidating drug-receptor interactions at the atomic level, this research underscores the impact of integrated computational approaches in drug discovery. It supports the development of precise targeted therapies for sleep disorders.
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