Insight QSDAR models for prediction of anticancer activity on Hela cell line of new flavonoid isolating from rhizome Zingiber zerumbet SM in Viet Nam

This research predicts the anticancer activity on the Hela cell line of new flavonoid kaempferol-3-O-methyl ether isolating from rhizome Zingiber zerumbet SM by using the spectrum data activity relationship (QSDAR) models. This model has been developed for a set of 3-aminoflavonoids based on the simulated-spectral data 13 C NMR and 15 O NMR resulting from the semi-empirical quantum chemical calculations TNDO/2 SCF. The atomic sites O 1 , O 11 , C 2 , C 3 , C 6 , C 7, and C 2’ in the QSDAR models significantly contribute to anticancer activity resulting from the Genetic algorithm (GA). The best regression model QSDAR MLR with the values R 2 train of 0.9057 and R 2 test of 0.7137, and the neural network model QSDAR ANN I(7)-HL(9)-O(1) with the values R 2 train of 0.993 and R 2 pred of 0.971 have been explored to predict the anticancer activities on Hela cell line for new flavonoid kaempferol-3-O-methyl ether from rhizome Zingiber zerumbet SM in Viet Nam.