The vitamin D nuclear receptor (VDR), a ligand-activated transcription factor, is integral to renal physiology and is implicated in the pathogenesis of diabetic nephropathy (DN). Targeting VDR with small-molecule selective VDR modulators (SVDRMs) represents a novel therapeutic strategy to attenuate DN progression. This study investigated Shikonin, a bioactive naphthoquinone, and a series of rationally designed derivatives as potential VDR antagonists. A scaffold hopping approach using the ADMETopt web server generated 100 Shikonin-based analogs optimized for pharmacokinetic properties. Structure-based virtual screening using Glide XP and MM/GBSA energy filtering identified four top-ranked candidates: Shikonin, Derivative₀2, Derivative₁2, and Derivative₃9. These compounds exhibited favorable binding free energies and key interactions within the VDR ligand-binding domain. Molecular dynamics simulations (500 ns) revealed that Derivative₀2 and Derivative₁2 exhibited superior structural retention and dynamic stability, with average ligand RMSD values under 2. 5 Å. Shikonin showed high pose retention, while Derivative₃9 displayed moderate flexibility, indicative of multistate binding. Free energy landscape (FEL) mapping and principal component analysis (PCA) showed that Shikonin and Derivative₀2 confined the receptor into energetically favorable conformations, while Derivatives₁2 and ₃9 promoted broader conformational sampling. MM/GBSA binding free energy decomposition revealed Derivative₁2 as the most thermodynamically favorable (ΔGbind = −59. 48 ± 6. 13 kcal/mol), driven by strong Coulombic and lipophilic interactions. Superimposition of extracted minima structures with initial docking poses confirmed RMSD values between 1. 180 and 1. 488 Å, indicating stable pose retention across all ligands. These results suggest that Shikonin and its derivatives, particularly Derivative₀2 and Derivative₁2, exhibit robust and energetically favorable binding to VDR. This work positions these compounds as strong candidates for further optimization and preclinical validation in the therapeutic targeting of DN.
Shantier et al. (Thu,) studied this question.