Centro de Investigação em Química da Universidade do Porto, Departamento de Química, Portugal.
J Comput Aided Mol Des. 2011 Aug;25(8):763-75. doi: 10.1007/s10822-011-9459-4. Epub 2011 Jul 24.
Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) based on three-dimensional quantitative structure-activity relationship (3D-QSAR) studies were conducted on a series (39 molecules) of peptidyl vinyl sulfone derivatives as potential Plasmodium Falciparum cysteine proteases inhibitors. Two different methods of alignment were employed: (i) a receptor-docked alignment derived from the structure-based docking algorithm GOLD and (ii) a ligand-based alignment using the structure of one of the ligands derived from a crystal structure from the PDB databank. The best predictions were obtained for the receptor-docked alignment with a CoMFA standard model (q (2) = 0.696 and r (2) = 0.980) and with CoMSIA combined electrostatic, and hydrophobic fields (q (2) = 0.711 and r (2) = 0.992). Both models were validated by a test set of nine compounds and gave satisfactory predictive r (2) (pred) values of 0.76 and 0.74, respectively. CoMFA and CoMSIA contour maps were used to identify critical regions where any change in the steric, electrostatic, and hydrophobic fields may affect the inhibitory activity, and to highlight the key structural features required for biological activity. Moreover, the results obtained from 3D-QSAR analyses were superimposed on the Plasmodium Falciparum cysteine proteases active site and the main interactions were studied. The present work provides extremely useful guidelines for future structural modifications of this class of compounds towards the development of superior antimalarials.
基于三维定量构效关系(3D-QSAR)研究,对一系列(39 个分子)作为潜在疟原虫半胱氨酸蛋白酶抑制剂的肽基乙烯砜衍生物进行了比较分子场分析(CoMFA)和比较分子相似性指数分析(CoMSIA)。采用了两种不同的对齐方法:(i)基于结构的对接算法 GOLD 衍生的受体对接对齐,(ii)基于来自 PDB 数据库中晶体结构的一个配体的结构的配体对齐。对于基于受体对接的对齐,获得了最佳的预测结果,CoMFA 标准模型(q ² = 0.696 和 r ² = 0.980)和 CoMSIA 结合静电和疏水场(q ² = 0.711 和 r ² = 0.992)。这两个模型都通过了包含九个化合物的测试集进行了验证,得到了令人满意的预测 r ² (pred)值分别为 0.76 和 0.74。CoMFA 和 CoMSIA 等高线图用于确定任何改变立体、静电和疏水场可能影响抑制活性的关键区域,并突出生物活性所需的关键结构特征。此外,还将 3D-QSAR 分析的结果叠加到疟原虫半胱氨酸蛋白酶的活性部位,并研究了主要的相互作用。本工作为这一类化合物的进一步结构修饰提供了非常有用的指导,以开发更优秀的抗疟药物。