Based on artificial intelligence-assisted generation and in-depth in-silico evaluation of potential inhibitors targeting Stearoyl-CoA desaturase 1 (SCD-1)

Stearoyl-CoA desaturase 1 (SCD-1), a key rate-limiting enzyme in lipid metabolism, catalyzes the conversion of saturated fatty acids to monounsaturated fatty acids. It regulates membrane fluidity and modulates ferroptosis by influencing cellular antioxidant systems. Frequently overexpressed in malignancies, SCD-1 promotes tumor progression by driving metabolic reprogramming, activating proliferative pathways such as PI3K-AKT-mTOR, and suppressing ferroptosis, thereby enhancing tumor survival, invasion, and chemotherapy resistance. Clinical evidence links elevated SCD-1 expression with advanced TNM stage, lymph node metastasis, and poor prognosis in various cancers. Although SCD-1 inhibitors exhibit promising antitumor efficacy in preclinical studies, their clinical translation is hampered by off-target toxicity and drug resistance. Developing tumor-specific SCD-1 inhibitors is therefore crucial. This study employed an artificial intelligence (AI)-aided drug design strategy using the MolProphet platform to generate 399 novel compounds. Virtual screening via molecular docking, molecular dynamics simulations (200 ns), and binding free energy calculations (MM-PBSA) identified four candidates (Cpd1-Cpd4) with stable binding modes, low RMSD (0.2-0.5 nm), and high binding affinity (MM-PBSA < - 40 kcal/mol). These results demonstrate the strong potential of the selected compounds as SCD-1 inhibitors, offering promising leads for targeted anticancer drug development and a robust AI-driven design framework.