Integrative Structural and Energetic Profiling of Pathogenic Vitamin D Receptor Variants for Precision Oncology

Genetic variation in the vitamin D receptor (VDR) gene has been associated with altered receptor activity and may influence cancer susceptibility. Nevertheless, the pathogenic and clinical implications of numerous VDR variants remain unclear. An in-silico workflow was integrated in this manuscript to detect potentially pathogenic nonsynonymous single-nucleotide polymorphisms (nsSNPs) in VDR, and to investigate the potential impact of these variants on ligand binding. A variety of computational tools for functional impact, disease association, and structural stability were used to select candidate nsSNPs. Possible structural effects were then evaluated using mutation3D and Missense3D. The most promising vitamin D analogs and nutraceutical compounds were screened using molecular docking, and the best complex was subjected to molecular dynamics simulation and MMGBSA analysis. Further characterization of the electronic, pharmacokinetic, and safety properties of the selected ligands was achieved through density functional theory calculations, SwissADME profiling, and toxicity prediction. R343C and E269G were the most structurally disruptive variants, predicted to weaken key salt bridges, hydrogen-bonding networks, and local electrostatic interactions, and potentially destabilize the receptors. Paricalcitol was the best ligand in terms of docking to the wild-type VDR model, and it established stable hydrogen-bonding and hydrophobic interactions in the binding pocket. Molecular dynamics and MMGBSA results also supported the formation of the stable complexes, and the negative binding free energy was maintained throughout the simulation. On the whole, these results suggest that some VDR variants negatively affect receptor stability and that paricalcitol is a promising VDR-interacting ligand to study. But since all these findings are based solely on computational studies, any biological or therapeutic implications would first have to be validated experimentally before they could be confirmed.