Yang Xiang-Lin, Zhou Yuan, Liu Xin-Ling
College of Chemistry and Chemical Engineering, Hunan University of Science and Technology, Xiangtan, Hunan 411201, China.; College of Chemistry and Chemical Engineering, Hunan Institute of Engineering, Xiangtan, Hunan 411104, China.
College of Chemistry and Chemical Engineering, Hunan Institute of Engineering, Xiangtan, Hunan 411104, China.
Iran J Pharm Res. 2016 Winter;15(Suppl):139-148.
A series of structurally related 2,4-dioxopyrimidine-1-carboxamide derivatives as highly potent inhibitors against acid ceramidase were subjected to hologram quantitative structure-activity relationship (HQSAR) analysis. A training set containing 24 compounds served to establish the HQSAR model. The best HQSAR model was generated using atoms, bond, connectivity, donor and acceptor as fragment distinction and 3-6 as fragment size with six components showing cross-validated q value of 0.834 and conventional r value of 0.965. The model was then employed to predict the potency of test set compounds that were excluded in the training set, and a good agreement between the experimental and predicted values was observed exhibiting the powerful predictable capability of this model [Formula: see text]. Atom contribution maps indicate that the electron-withdrawing effects at position 5 of the uracil ring, the preferential acyl substitution at N3 position and the substitution of eight-carbon alkyl chain length at N1 position predominantly contribute to the inhibitory activity. Based upon these key structural features derived from atom contribution maps, we have designed novel inhibitors of acid ceramidase possessing better inhibitory activity.
一系列结构相关的2,4-二氧代嘧啶-1-甲酰胺衍生物作为酸性神经酰胺酶的高效抑制剂，进行了全息定量构效关系（HQSAR）分析。一个包含24种化合物的训练集用于建立HQSAR模型。使用原子、键、连接性、供体和受体作为片段区分，3-6作为片段大小生成了最佳HQSAR模型，六个成分的交叉验证q值为0.834，传统r值为0.965。然后使用该模型预测训练集中排除的测试集化合物的效力，观察到实验值和预测值之间有良好的一致性，表明该模型具有强大的预测能力[公式：见正文]。原子贡献图表明，尿嘧啶环5位的吸电子效应、N3位的优先酰基取代以及N1位的八碳烷基链长度取代主要有助于抑制活性。基于从原子贡献图得出的这些关键结构特征，我们设计了具有更好抑制活性的新型酸性神经酰胺酶抑制剂。
