Nair Pramod C, Sobhia M Elizabeth
Centre for Pharmacoinformatics, National Institute of Pharmaceutical Education and Research (NIPER), Sector 67, S.A.S Nagar, Mohali 160062, Punjab, India.
Eur J Med Chem. 2008 Feb;43(2):293-9. doi: 10.1016/j.ejmech.2007.03.020. Epub 2007 Apr 5.
Influenza virus is a major global threat that impacts the world in one form or another as flu infections. Neuraminidase, one of the targets for these viruses, has recently been exploited in the treatment of these infections. Quantitative structure activity relationship studies were performed on thiourea analogues using spatial, topological, electronic, thermodynamic and E-state indices. Genetic algorithm based genetic function approximation method of variable selection was used to generate the model. Highly statistically significant model was obtained when number of descriptors in the equation was set to 5. The atom type log P and shadow indices descriptors showed enormous contributions to neuraminidase inhibition. The validation of the model was done by cross validation, randomization and external test set prediction. The model gives insight on structural requirements for designing more potent analogues against influenza virus neuraminidase.
流感病毒是一种重大的全球威胁，以流感感染的某种形式影响着世界。神经氨酸酶是这些病毒的靶点之一，最近已被用于这些感染的治疗。利用空间、拓扑、电子、热力学和E态指数对硫脲类似物进行了定量构效关系研究。使用基于遗传算法的变量选择遗传函数逼近方法生成模型。当方程中的描述符数量设置为5时，获得了具有高度统计学意义的模型。原子类型log P和影子指数描述符对神经氨酸酶抑制显示出巨大贡献。通过交叉验证、随机化和外部测试集预测对模型进行了验证。该模型为设计更有效的抗流感病毒神经氨酸酶类似物的结构要求提供了见解。
