Screening and Activity Evaluation of SMYD2 Inhibitors Based on Deep Learning
Two deep learning models,Chemprop and RTMScore,were used to screen for potential SMYD2 inhibi-tors from the TopScience commercial database.The inhibitory activity of the potential compounds was then deter-mined using the CCK-8 method,and their effects on the anti-proliferation and migration of A549 cells were assessed using cell cloning and cell scratch,respectively.Finally,the binding ability of the compound 5 bound to SMYD2 was verified using cellular thermal shift assay and Wesrern blotting.The results showed that compound 5,identified by the deep learning model,exhibited significant inhibitory effects on the proliferation of A549 cells(inhibition rate≥80%)with a IC50 value of 10.89 μmol/L.Treatment with 10 μmol/L of compound 5 resulted in a significant reduction in both the number of clones formed and the migration area of A549 cells compared to the control group(P<0.05).The cellular thermal shift assay confirmed that compound 5 could bind to SMYD2.
deep learningSMYD2 inhibitorproliferation inhibition
万方数据
维普
