In Silico Mining of Potential Anti-cancer Liver X Receptor β Agonists
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Abstract
Cancer continues to be a leading cause of mortality worldwide, with the most common treatments such as chemotherapy and radiotherapy producing severe off-target effects. This study aims to identify potential therapeutic compounds by screening the Natural Products Atlas (NPAtlas) for potential agonists of the Liver X Receptor Beta (LXR-β). LXR-β is a nuclear receptor involved in lipid metabolism and is known to induce apoptosis in cancer cells when acted upon by an agonist. Screening of 36,310 compounds from the NPAtlas database was performed using molecular docking, pharmacokinetic filtering, absorption, distribution, metabolism, excretion, and toxicity (ADMET) profiling, and confirmatory molecular dynamics simulations. From the initial dataset, 9 candidates passed the docking and ADMET criteria, and molecular dynamics simulations successfully validated 7 of them. Among these, Cis-veramycin E (NPA033420) and Solanapyrone E (NPA010954) emerged as top candidates. Cis-veramycin E demonstrated a high docking score (–9.31 kcal/mol), low root mean square deviation (RMSD) of <1.0 nm, minimal root mean square fluctuation (RMSF) of <0.3 nm, and a favorable ADMET profile, including Ames safety, good absorption, and moderate clearance. Protein–ligand interaction profiling revealed a binding profile similar to known LXR-β agonists, including hydrogen bonding with Ser278, π–π stacking with Phe340, and hydrophobic contacts across core residues. Solanapyrone E exhibited comparable binding stability and engaged the critical His435–Trp457 electrostatic switch via a salt bridge, but was flagged as Ames toxic, indicating a need for structural optimization. The results support the recommendation to identify the compounds as lead candidates for LXR-β-targeted cancer therapy.
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