Gao H, Bajorath J
Computational Chemistry and Informatics, MDS Panlabs, Bothell, WA 98011, USA.
Mol Divers. 1998;4(2):115-30. doi: 10.1023/a:1026449704559.
Binary and conventional 2D QSAR have been derived for a set of carbonic anhydrase II (CA II) inhibitors. An overall predictive accuracy of 94% was obtained by binary QSAR and of 84% by 2D QSAR model. For both models, preferred molecular descriptor sets were identified, which were overlapping but not identical. Both binary and 2D QSAR captured important molecular features of CA II inhibitors, notably the presence of a sulfonamido group, which is critical for binding, but also hydrophobicity. Promising results were obtained when the derived QSAR models were used to test a set of CA II inhibitors not included in the training set. In binary QSAR, previously unobserved boundary effects were detected both in the analysis of known inhibitors and when screening a large combinatorial library for putative inhibitors. The complementary use of binary and conventional 2D QSAR is thought to increase the accuracy of the lead discovery process by QSAR techniques.
已针对一组碳酸酐酶II（CA II）抑制剂推导了二元和传统的二维定量构效关系（QSAR）。二元QSAR获得的总体预测准确率为94%，二维QSAR模型为84%。对于这两种模型，都确定了优选的分子描述符集，它们有重叠但并不相同。二元和二维QSAR都捕捉到了CA II抑制剂的重要分子特征，特别是存在对结合至关重要的磺酰胺基团以及疏水性。当使用推导的QSAR模型测试一组未包含在训练集中的CA II抑制剂时，获得了有前景的结果。在二元QSAR中，在分析已知抑制剂以及筛选大型组合文库寻找推定抑制剂时，都检测到了以前未观察到的边界效应。二元和传统二维QSAR的互补使用被认为可通过QSAR技术提高先导化合物发现过程的准确性。
