Predictive Modeling of Breast Anticancer Activity of a Series of Coumarin Derivatives using Quantum Descriptors
Lamoussa Ouattara, Kafoumba Bamba, Mamadou Guy-Richard Koné, Jean Stéphane N’dri, Kouakou Nobel N’Guessan, Ouattara Pierrre Massapihanhoro, Diarrassouba Fatogoman
Chemical Science International Journal · pp. 1–10 · Published 9 Apr 2019
10.9734/CSJI/2019/v26i430098Abstract
We focused on a series of coumarin derivatives in this work. The method of Density Functional Theory (DFT) of quantum chemistry has been used at B3LYP / 6-31G (d, p) level in order to identify molecular descriptors which are useful for this study. The analysis of the statistical indicators allowed to obtain a QSAR model based on quantum descriptors and anti-cancer activity against breast cancer (MCF-7) that were accredited for good statistical performance. For the model, the statistical indicators were: correlation coefficient R2 = 0.904, standard deviation S = 0.102, Fischer test coefficient F = 18.779 and correlation coefficient of cross validation
Cited by 3
Ouattara Lamoussa, Mamadou Guy-Richard Koné, O. Patrice · Mediterranean Journal of Chemistry · 2024
L. Ouattara, K. Bamba, M. Koné · 2021
Aparna Das, B. Banik · 2020
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