QSAR Modeling of Thirty Active Compounds for the Inhibition of the Acetylcholinesterase Enzyme
Nour El Houda Hammoudi1, Yacine Benguerba1 & Widad Sobhi1 Show affiliations
- Université Ferhat ABBAS Sétif-1, Algeria
Current Research in Bioinformatics, Volume 8, Issue 1, pp. 62–65 · doi.org/10.3844/ajbsp.2019.62.65
Abstract
This work aims at developing a reliable and predictive QSAR model which allows, on one hand, an exploration of the main molecular descriptors responsible for the inhibitory activity towards the Acetylcholinesterase enzyme and, on the other hand, predict the inhibitory activity of new compounds before testing them experimentally. This study involves a series of DL0410 and its 29 DL0410 derivatives. The Multiple Linear Regression (MLR) analysis is carried out to derive the QSAR model. The results indicate that the QSAR model is robust and possesses a high predictive capacity.
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Hammoudi, N. E. H., Benguerba, Y. & Sobhi, W. (2019). QSAR Modeling of Thirty Active Compounds for the Inhibition of the Acetylcholinesterase Enzyme. Current Research in Bioinformatics, 8(1), 62–65. https://doi.org/10.3844/ajbsp.2019.62.65
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