Gupta Pawan, Sharma Anju, Garg Prabha, Roy Nilanjan
Department of Pharmacoinformatics, National Institute of Pharmaceutical Education and Research, S.A.S. Nagar, Punjab, India.
Curr Comput Aided Drug Des. 2013 Mar;9(1):141-50.
A QSAR study was performed on curcumine derivatives as HIV-1 integrase inhibitors using multiple linear regression. The statistically significant model was developed with squared correlation coefficients (r(2)) 0.891 and cross validated r(2) (r(2) cv) 0.825. The developed model revealed that electronic, shape, size, geometry, substitution's information and hydrophilicity were important atomic properties for determining the inhibitory activity of these molecules. The model was also tested successfully for external validation (r(2) pred = 0.849) as well as Tropsha's test for model predictability. Furthermore, the domain analysis was carried out to evaluate the prediction reliability of external set molecules. The model was statistically robust and had good predictive power which can be successfully utilized for screening of new molecules.
使用多元线性回归对姜黄素衍生物作为HIV-1整合酶抑制剂进行了定量构效关系（QSAR）研究。构建了具有统计学意义的模型，其平方相关系数（r(2)）为0.891，交叉验证r(2)（r(2) cv）为0.825。所构建的模型表明，电子性质、形状、大小、几何结构、取代基信息和亲水性是决定这些分子抑制活性的重要原子性质。该模型还成功通过外部验证（r(2) pred = 0.849）以及用于模型可预测性的Tropsha检验。此外，进行了域分析以评估外部数据集分子的预测可靠性。该模型具有统计学稳健性和良好的预测能力，可成功用于筛选新分子。
