Computational Analysis of Artimisinin Derivatives on the Antitumor Activities
Hui Liu, Xingyong Liu, Li Zhang · Natural Products and Bioprospecting · 2017
The study on antitumor activities of artemisinin and its derivatives has been closely focused on in recent years. Herein, 2D and 3D QSAR analysis was performed on the basis of a series of artemisinin derivatives with known bioactivities against the non-small-cell lung adenocarcinoma A549 cells. Four QSAR models were successfully established by CoMSIA, CoMFA, topomer CoMFA and HQSAR approaches with respective characteristic values q 2 = 0.567, R 2 = 0.968, ONC = 5; q 2 = 0.547, R 2 = 0.980, ONC = 7; q 2 = 0.559, R 2 = 0.921, ONC = 7 and q 2 = 0.527, R 2 = 0.921, ONC = 6. The predictive ability of CoMSIA with r 2 = 0.991 is the best one compared with the other three approaches, such as CoMFA (r 2 = 0.787), topomer CoMFA (r 2 = 0.819) and HQSAR (r 2 = 0.743). The final QSAR models can provide guidance in structural modification of artemisinin derivatives to improve their anticancer activities.