Faculty of Pharmacy, Zarqa University, Zarqa, 13132, Jordan.
J Mol Graph Model. 2013 May;42:104-14. doi: 10.1016/j.jmgm.2013.03.003. Epub 2013 Mar 28.
Recent research suggested the involvement of migration inhibitor factor (MIF) in cancer and inflammatory diseases, which prompted several attempts to develop new MIF inhibitors. Accordingly, we investigated the pharmacophoric space of 79 MIF inhibitors using seven diverse subsets of inhibitors to identify plausible binding hypotheses (pharmacophores). Subsequently, we implemented genetic algorithm and multiple linear regression analysis to select optimal combination of pharmacophores and physicochemical descriptors capable of explaining bioactivity variation within the training compounds (QSAR model, r63=0.62, F=42.8, rLOO(2)=0.721,rPRESS(2) against 16 external test inhibitors=0.58). Two orthogonal pharmacophores appeared in the optimal QSAR model suggestive of at least two binding modes available to ligands inside MIF binding pocket. Subsequent validation using receiver operating characteristic (ROC) curves analysis established the validity of these two pharmacophores. We employed these pharmacophoric models and associated QSAR equation to screen the National Cancer Institute (NCI) list of compounds. Eight compounds gave >50% inhibition at 100μM. Two molecules illustrated >75% inhibition at 10μM.
最近的研究表明迁移抑制因子（MIF）参与癌症和炎症性疾病，这促使人们尝试开发新的 MIF 抑制剂。因此，我们使用七种不同的抑制剂亚组来研究 79 种 MIF 抑制剂的药效团空间，以确定合理的结合假设（药效团）。随后，我们实施遗传算法和多元线性回归分析，以选择能够解释训练化合物中生物活性变化的最佳药效团和物理化学描述符组合（QSAR 模型，r63=0.62，F=42.8，rLOO(2)=0.721，rPRESS(2)针对 16 个外部测试抑制剂=0.58）。最佳 QSAR 模型中出现了两个正交药效团，表明配体在 MIF 结合口袋内至少有两种结合模式。随后使用接受者操作特征（ROC）曲线分析进行验证，确立了这两种药效团的有效性。我们使用这些药效团模型和相关的 QSAR 方程筛选了国立癌症研究所（NCI）的化合物列表。有 8 种化合物在 100μM 时的抑制率超过 50%。有两种分子在 10μM 时的抑制率超过 75%。
