作为抗流感药物的神经氨酸酶抑制剂的定量构效关系研究
QSAR Studies on Neuraminidase Inhibitors as Anti-influenza Agents.
作者信息
Veerasamy Ravichandran, Rajak Harish
机构信息
AIMST University Faculty of Pharmacy, Department of Pharmaceutical Chemistry, Kedah, Malaysia
Guru Ghasidas University SLT Institute of Pharmaceutical Sciences, Bilaspur, India
出版信息
Turk J Pharm Sci. 2021 Apr 20;18(2):151-156. doi: 10.4274/tjps.galenos.2020.45556.
OBJECTIVES
The 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.
MATERIALS AND METHODS
We 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.
RESULTS
2D QSAR models had q: 0.950 and pred_r: 0.877 and 3D QSAR models had q: 0.899 and pred_r: 0.957. These results showed that the models werere predictive.
CONCLUSION
Parameters 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.
目的
本研究旨在建立针对神经氨酸酶抑制剂的有效且经过验证的定量构效关系（QSAR）模型，并将其物理化学、空间和静电性质与其抗流感活性相关联。
材料与方法
我们使用多元线性回归、偏最小二乘回归和k近邻分子场分析方法开发并验证了二维和三维QSAR模型。
结果
二维QSAR模型的q值为0.950，预测r值为0.877；三维QSAR模型的q值为0.899，预测r值为0.957。这些结果表明模型具有预测性。
结论
二维QSAR模型涉及氢原子数和亲水性等参数。三维QSAR研究表明，空间和疏水描述符对神经氨酸酶抑制活性有负向贡献。本研究结果可作为设计更好的抗流感药物的平台。
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