Exploration of novel plumbagin derivatives as anti‐liver cancer inhibitors of VEGFR‐2: Designing, ADMET, QSAR models, and molecular docking

Abstract A series of novel compounds of plumbagin (PLG) derivatives from Plumbago Zeylanica Linn were identified in this investigation as potential inhibitors against the HepG2 cell line‐derived liver cancer. The quantitative structure‐activity relationship (QSAR) models were used to design novel plumbagin derivatives. The QSAR models were constructed using multiple linear regression (MLR) and artificial neural network (ANN) techniques based on the chemical descriptors and the IC 50 values of experimental plumbagin derivatives. As a result, six descriptors that are key features of the QSAR MLR model satisfy the following statistical requirements: R 2 train = 0.835, R 2 adj = 0.818, and Q 2 LOO = 0.787. The QSAR ANN model with the architecture of I(6)‐HL(5)‐O(1) was constructed based on variables of the QSAR MLR model, with statistical data: R 2 train = 0.988; Q 2 validation = 0.937, and R 2 test = 0.964. Consequently, twenty plumbagin derivatives (PLG1‐PLG20) within the applicability domain (AD) exhibited promising IC 50 values as calculated by both QSAR models, of which 11 derivatives met the criteria of drug‐likeness by using Lipinski‐5 and Veber rules. The derivatives underwent ADME analysis to assess their drug‐likeness. Subsequently, they were docked into the VEGFR receptor to identify potential inhibitors, of which 9 of 20 PLG derivatives are potential inhibitors for anti‐liver cancer. The findings may be helpful in the development of novel medications for the treatment of liver cancer.