Insight QSDAR models for prediction of anticancer activity on Hela cell line of new flavonoid isolating from rhizome Zingiber zerumbet SM in Viet Nam
INDIAN JOURNAL OF CHEMISTRY SECTION B-ORGANIC CHEMISTRY INCLUDING MEDICINAL CHEMISTRY(2021)
Abstract
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 C-13 NMR and O-15 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-2, and C2. in the QSDAR models significantly contribute to anticancer activity resulting from the Genetic algorithm (GA). The best regression model QSDARMLR with the values R-train(2) of 0.9057 and R-train(2) of 0.7137, and the neural network model QSDAR, NN I(7)-HL(9)-O(1) with the values R-train(2) of 0.993 and R-train(2) 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.
MoreTranslated text
Key words
QSDAR(MLR) model, QSDAR(ANN) model, quantitative spectrum data - activity relationship, chemical-shift data, anticancer activities, Hela cell line
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined