González Maykel Pérez, Terán Carmen, Teijeira Marta
Department of Organic Chemistry, Vigo University, C.P. 36310, Vigo, Spain.
Med Res Rev. 2008 May;28(3):329-71. doi: 10.1002/med.20108.
In view of the large libraries of nucleoside analogues that are now being handled in organic synthesis, the identification of drug biological activity is advisable prior to synthesis and this can be achieved by employing predictive biological property methods. In this sense, Quantitative Structure-Activity Relationships (QSAR) or docking approaches have emerged as promising tools. Although a large number of in silico approaches have been described in the literature for the prediction of different biological activities, the use of QSAR applications to develop adenosine receptor (AR) antagonists is not common as for the case of the antibiotics and anticancer compounds for instance. The intention of this review is to summarize the present knowledge concerning computational predictions of new molecules as adenosine receptor antagonists.
鉴于目前有机合成中正在处理的大量核苷类似物库,在合成之前确定药物的生物活性是明智的,这可以通过采用预测生物学性质的方法来实现。从这个意义上说,定量构效关系(QSAR)或对接方法已成为很有前景的工具。尽管文献中已经描述了大量用于预测不同生物活性的计算机方法,但与抗生素和抗癌化合物的情况不同,使用QSAR应用来开发腺苷受体(AR)拮抗剂并不常见。本综述的目的是总结有关作为腺苷受体拮抗剂的新分子的计算预测的现有知识。