Fossa Paola, Mosti Luisa, Bondavalli Francesco, Schenone Silvia, Ranise Angelo, Casolino Chiara, Forina Michele
Dipartimento di Scienze Farmaceutiche, Università degli Studi di Genova, Genoa, Italy.
Bioorg Med Chem. 2006 Mar 1;14(5):1348-63. doi: 10.1016/j.bmc.2005.09.058. Epub 2005 Nov 2.
In this paper, we are presenting a quantitative-structure-activity relationship (QSAR) study performed on 21 selective A(1) adenosine receptor agonists plus the endogenous substrate, adenosine, so as to identify those predictors which play a key role in describing the binding of the ligand with the A(1) receptor. A large number of molecular descriptors plus a calculated receptor-agonist binding energy and atomic charges were taken into account to derive different QSAR models, using different regression techniques. The results obtained both with linear and nonlinear approaches converge to the selection of the same informative parameters, highlighting the correlation of these descriptors with the biological Response. The evaluation 'a priori' of these predictors could therefore represent a useful tool in the screening of large libraries of compounds and in the rational design of new selective agonists.
在本文中，我们对21种选择性A(1)腺苷受体激动剂以及内源性底物腺苷进行了定量构效关系（QSAR）研究，以确定那些在描述配体与A(1)受体结合中起关键作用的预测因子。考虑了大量的分子描述符以及计算得到的受体-激动剂结合能和原子电荷，使用不同的回归技术来推导不同的QSAR模型。线性和非线性方法得到的结果都收敛于选择相同的信息参数，突出了这些描述符与生物学反应的相关性。因此，对这些预测因子的“先验”评估可能是筛选大量化合物库和合理设计新型选择性激动剂的有用工具。
