Natural Science Laboratory, Division of Medicinal and Pharmaceutical Chemistry, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India.
J Pharm Pharmacol. 2013 Oct;65(10):1541-54. doi: 10.1111/jphp.12133. Epub 2013 Aug 25.
Matrix metalloproteinase-2 (MMP-2) is a potential target in metastases. Regression (conventional 2D QSAR) and classification (recursive partitioning (RP), Bayesian modelling) QSAR, pharmacophore mapping and 3D QSAR (comparative molecular field analysis and comparative molecular similarity analysis) were performed on 202 MMP-2 inhibitors.
Quality of the regression models was justified by internal (Q(2) ) and external (R(2) Pred ) cross-validation parameters. Stepwise regression was used to develop linear model (Q(2) = 0.822, R(2) Pred = 0.667). Genetic algorithm developed linear (Q(2) = 0.845, R(2) Pred = 0.638) and spline model (Q(2) = 0.882, R(2) Pred = 0.644). The RP and Bayesian models showed cross-validated area under receiver operating characteristic curve (AUCROC _ CV ) of 0.805 and 0.979 respectively. QSAR models depicted importance of descriptors like five-membered rings, fractional positively charged surface area, lipophilocity and so on. Higher molecular volume was found to be detrimental. Pharmacophore mapping was performed with two tools - Hypogen and PHASE. Both models indicated that one hydrophobic and three hydrogen bond acceptor features are essential. The Pharmacophore-aligned structures were used for CoMFA (Q(2) of 0.586 and R(2) Pred of 0.689) and CoMSIA (Q(2) of 0.673 and R(2) Pred of 0.758), results of which complied with the other analyses.
All modelling techniques were compared to each other. The current study may help in designing novel MMP-2 inhibitors.
基质金属蛋白酶-2（MMP-2）是转移的潜在靶点。对 202 种 MMP-2 抑制剂进行了回归（传统二维 QSAR）和分类（递归分区（RP）、贝叶斯建模）QSAR、药效团映射和 3D QSAR（比较分子场分析和比较分子相似性分析）。
内部（Q 2 ）和外部（R 2 Pred ）交叉验证参数证明了回归模型的质量。逐步回归用于开发线性模型（Q 2 = 0.822，R 2 Pred = 0.667）。遗传算法开发了线性（Q 2 = 0.845，R 2 Pred = 0.638）和样条模型（Q 2 = 0.882，R 2 Pred = 0.644）。RP 和贝叶斯模型的交叉验证接收者操作特征曲线（AUCROC _ CV ）分别为 0.805 和 0.979。QSAR 模型描述了像五元环、部分正电荷表面积、亲脂性等描述符的重要性。发现较高的分子体积是有害的。使用 Hypogen 和 PHASE 两种工具进行药效团映射。两个模型都表明，一个疏水性和三个氢键接受体特征是必不可少的。基于药效团的结构用于 CoMFA（Q 2 为 0.586，R 2 Pred 为 0.689）和 CoMSIA（Q 2 为 0.673，R 2 Pred 为 0.758），结果与其他分析一致。
将所有建模技术相互比较。本研究可能有助于设计新型 MMP-2 抑制剂。
