Anticancer agents of kaempferol-3-O-methylether and kaempferol-3-O-(2,4-O-diacetyl-alpha-L-rhamnopyranoside) in leaf of plants Zingiber zerumbet SM using 2D, 3D descriptors

Bui Thi Phuong Thuy, Nguyen Thi Ai Nhung, Vo Thanh Cong, Phung Van Trung, Hoang Thi Kim Dung, Tran Duong, Pham Van Tat

Abstract


The plants are an alternative resource for studying anti-cancer drugs and the natural products isolated from them can point out a direct impact on eliminating cancer cells and also reduce cancer side effects. Recently, we isolated two kaempferols in flavonoid group from leaves of Zingiber zerumbet Sm in Vietnam, with stronger cytotoxin relatively for Hela cancer cells. In this QSAR study on cancer Hela cell line, the techniques of multiple linear regression (MLR) and the artificial neural network (ANN) were integrated with artificial neural network to construct the different QSAR models such as the QSARMLR and QSARANN models. The best linear model QSARMLR with 9 independent variables and values R2train of 0.955 and R2pred of 0.745 was also found by using a multiple linear regression technique. The artificial neural network QSARANN with structural style I(9)-HL(5)-O(1) exhibited a better quality in statistical values R2train of 0.8963 and R2pred of 0.8883. The anti-cancer activities of the flavonoids in the test group and kaempferol-3-O-methylether and kaempferol-3-O-(2,4-O-diacetyl-alpha-L-rhamnopyranoside) from leaves of Zingiber zerumbet Sm resulting from those models turned out to be agreement with experimental data and those from literature.

Keywords


QSARMLR model, neural network QSARANN, anticancer activities Hela.

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