Computational Analysis of Artimisinin Derivatives on the Antitumor Activities

doi:10.1007/s13659-017-0142-x

应用天然产物 ›› 2017, Vol. 7 ›› Issue (6): 433-443.DOI: 10.1007/s13659-017-0142-x

Computational Analysis of Artimisinin Derivatives on the Antitumor Activities

Hui Liu, Xingyong Liu, Li Zhang

School of Chemical Engineering, Sichuan University of Science & Engineering, Zigong, China

收稿日期:2017-09-19 修回日期:2017-10-18 出版日期:2017-12-24 发布日期:2017-12-09
通讯作者: Hui Liu
基金资助:
We gratefully thank financial assistance from the Science and Technology Innovation Talent Project of Sichuan province (Grant Number 2016073).

Computational Analysis of Artimisinin Derivatives on the Antitumor Activities

Hui Liu, Xingyong Liu, Li Zhang

School of Chemical Engineering, Sichuan University of Science & Engineering, Zigong, China

Received:2017-09-19 Revised:2017-10-18 Online:2017-12-24 Published:2017-12-09
Contact: Hui Liu
Supported by:
We gratefully thank financial assistance from the Science and Technology Innovation Talent Project of Sichuan province (Grant Number 2016073).

摘要/Abstract

摘要： 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 q²=0.567, R²=0.968, ONC=5; q²=0.547, R²=0.980, ONC=7; q²=0.559, R²=0.921, ONC=7 and q²=0.527, R²=0.921, ONC=6. The predictive ability of CoMSIA with r²=0.991 is the best one compared with the other three approaches, such as CoMFA (r²=0.787), topomer CoMFA (r²=0.819) and HQSAR (r²=0.743). The final QSAR models can provide guidance in structural modification of artemisinin derivatives to improve their anticancer activities.

关键词: QSAR, CoMFA, CoMSIA, Topomer CoMFA, HQSAR, Artemisinin

Abstract: 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 q²=0.567, R²=0.968, ONC=5; q²=0.547, R²=0.980, ONC=7; q²=0.559, R²=0.921, ONC=7 and q²=0.527, R²=0.921, ONC=6. The predictive ability of CoMSIA with r²=0.991 is the best one compared with the other three approaches, such as CoMFA (r²=0.787), topomer CoMFA (r²=0.819) and HQSAR (r²=0.743). The final QSAR models can provide guidance in structural modification of artemisinin derivatives to improve their anticancer activities.

Key words: QSAR, CoMFA, CoMSIA, Topomer CoMFA, HQSAR, Artemisinin

Hui Liu, Xingyong Liu, Li Zhang. Computational Analysis of Artimisinin Derivatives on the Antitumor Activities[J]. 应用天然产物, 2017, 7(6): 433-443.

Hui Liu, Xingyong Liu, Li Zhang. Computational Analysis of Artimisinin Derivatives on the Antitumor Activities[J]. Natural Products and Bioprospecting, 2017, 7(6): 433-443.

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Computational Analysis of Artimisinin Derivatives on the Antitumor Activities

Computational Analysis of Artimisinin Derivatives on the Antitumor Activities

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