Turkish journal of pharmaceutical sciences | 2021
QSAR Studies on Neuraminidase Inhibitors as Anti-influenza Agents
Abstract
Objectives\nThe present study aimed to establish significant and validated quantitative structure-activity relationship (QSAR) models for neuraminidase inhibitors and correlate their physicochemical, steric, and electrostatic properties with their anti-influenza activity.\n\n\nMaterials and Methods\nWe have developed and validated 2D and 3D QSAR models by using multiple linear regression, partial least square regression, and k-nearest neighbor-molecular field analysis methods.\n\n\nResults\n2D QSAR models had q2: 0.950 and pred_r2: 0.877 and 3D QSAR models had q2: 0.899 and pred_r2: 0.957. These results showed that the models werere predictive.\n\n\nConclusion\nParameters such as hydrogen count and hydrophilicity were involved in 2D QSAR models. The 3D QSAR study revealed that steric and hydrophobic descriptors were negatively contributed to neuraminidase inhibitory activity. The results of this study could be used as platform for design of better anti-influenza drugs.