Chen Jin-Juan, Liu Ting-Lin, Yang Li-Jun, Li Lin-Li, Wei Yu-Quan, Yang Sheng-Yong
State Key Laboratory of Biotherapy, West China Hospital, West China School of Pharmacy, Sichuan University.
Chem Pharm Bull (Tokyo). 2009 Jul;57(7):704-9. doi: 10.1248/cpb.57.704.
In this study, chemical feature-based 3-dimensional (3D) pharmacophore models of Checkpoint kinase 1 (Chk1) inhibitors were developed based on the known inhibitors of Chk1. The best pharmacophore model Hypo1 was characterized by the best correlation coefficient (0.9577), and the lowest root mean square deviation (0.8871). Hypo1 consists of one hydrogen-bond acceptor, one hydrogen-bond donor, and two hydrophobic features, as well as one excluded volume. This pharmacophore model was further validated by both test set and cross validation methods. A comparison analysis of Hypo1 with chemical features in the active site of Chk1 indicates that the pharmacophore model Hypo1 can correctly reflect the interactions between Chk1 and its ligands. Then Hypo1 was used to screen chemical databases, including Specs and Chinese Nature Product Database (CNPD) for potential lead compounds. The hit compounds were subsequently subjected to filtering by Lipinski's rule of five and docking study to refine the retrieved hits. Finally some of the most potent (estimated) compounds were selected from the final refined hits and suggested for further experimental investigation.
在本研究中,基于已知的Chk1抑制剂,开发了基于化学特征的Chk1抑制剂三维(3D)药效团模型。最佳药效团模型Hypo1的特征是具有最佳相关系数(0.9577)和最低均方根偏差(0.8871)。Hypo1由一个氢键受体、一个氢键供体、两个疏水特征以及一个排除体积组成。该药效团模型通过测试集和交叉验证方法进一步验证。对Hypo1与Chk1活性位点化学特征的比较分析表明,药效团模型Hypo1能够正确反映Chk1与其配体之间的相互作用。然后使用Hypo1筛选化学数据库,包括Specs和中国天然产物数据库(CNPD)以寻找潜在的先导化合物。随后对命中的化合物进行Lipinski五规则过滤和对接研究,以优化检索到的命中结果。最后,从最终优化的命中结果中选择了一些最有效的(估计)化合物,并建议进行进一步的实验研究。