Kaur Paramjit, Sharma Vikas, Kumar Vipin
Institute of Pharmaceutical Sciences, Kurukshetra University, Haryana, Kurukshetra 136119, India.
Int J Med Chem. 2012;2012:452325. doi: 10.1155/2012/452325. Epub 2012 May 31.
Pharmacophore modelling-based virtual screening of compound is a ligand-based approach and is useful when the 3D structure of target is not available but a few known active compounds are known. Pharmacophore mapping studies were undertaken for a set of 50 N(3)-phenylpyrazinones possessing Corticotropin-releasing Factor 1 (CRF 1) antagonistic activity. Six point pharmacophores with two hydrogen bond acceptors, one hydrogen bond donor, two hydrophobic regions, and one aromatic ring as pharmacophoric features were developed. Amongst them the pharmacophore hypothesis AADHHR.47 yielded a statistically significant 3D-QSAR model with 0.803 as R (2) value and was considered to be the best pharmacophore hypothesis. The developed pharmacophore model was externally validated by predicting the activity of test set molecules. The squared predictive correlation coefficient of 0.91 was observed between experimental and predicted activity values of test set molecules. The geometry and features of pharmacophore were expected to be useful for the design of selective CRF 1 receptor antagonists.
基于药效团模型的化合物虚拟筛选是一种基于配体的方法,当靶点的三维结构未知但有一些已知的活性化合物时很有用。对一组具有促肾上腺皮质激素释放因子1(CRF 1)拮抗活性的50种N(3)-苯基吡嗪酮进行了药效团映射研究。开发了具有两个氢键受体、一个氢键供体、两个疏水区域和一个芳香环作为药效团特征的六点药效团。其中,药效团假设AADHHR.47产生了一个具有统计学意义的3D-QSAR模型,R(2)值为0.803,被认为是最佳的药效团假设。通过预测测试集分子的活性对所开发的药效团模型进行了外部验证。在测试集分子的实验活性值和预测活性值之间观察到平方预测相关系数为0.91。预计药效团的几何形状和特征将有助于设计选择性CRF 1受体拮抗剂。