Predictive Modeling of Breast Anticancer Activity of a Series of Coumarin Derivatives using Quantum Descriptors

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Lamoussa Ouattara
Kafoumba Bamba
Mamadou Guy-Richard Koné
Jean Stéphane N’dri
Kouakou Nobel N’Guessan
Ouattara Pierrre Massapihanhoro
Diarrassouba Fatogoman

Abstract

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

Keywords:
Anticancer activity, coumarin derivative, quantum descriptors, MCF-7, QSAR

Article Details

How to Cite
Ouattara, L., Bamba, K., Koné, M., N’dri, J., N’Guessan, K. N., Massapihanhoro, O., & Fatogoman, D. (2019). Predictive Modeling of Breast Anticancer Activity of a Series of Coumarin Derivatives using Quantum Descriptors. Chemical Science International Journal, 26(4), 1-10. https://doi.org/10.9734/CSJI/2019/v26i430098
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Short Research Article