Key Laboratory of Biorheological Science and Technology, Ministry of Education, College of Bioengineering, Chongqing University, Chongqing 400030, PR China.
Fitoterapia. 2011 Dec;82(8):1141-51. doi: 10.1016/j.fitote.2011.08.007. Epub 2011 Aug 12.
Hunting lead compounds from natural products plays a vital role in finding successful drug candidates. The efficiency of screening campaigns is mainly determined by the validity of selected screening models. To screen desired lead compounds, researchers have developed a plethora of experimental screening models. However, the considerable diversity of screening models from animal models, tissue models, to cell models and so on, may cause some trouble in choosing the suitable one. This review provides a toolbox of experimental screening models that have been used to discover new drug candidates from natural products. Two screening indexes are designed for different research directions in this screening toolbox. Index I is proposed from the direction of screening different objective substance populations, including plant extracts, active fractions and pure compounds; index Π is according to screening different drug properties, including pharmacological properties, pharmacokinetic properties and affinity binding properties. We hope that the abbreviated bibliographies will help readers to quickly retrieve useful information by two screening indexes and provide certain reference value for choosing more appropriate screening models. Finally, we discuss ways of improving model systems, as well as future directions.
从天然产物中寻找先导化合物在发现成功的药物候选物方面发挥着至关重要的作用。筛选活动的效率主要取决于所选筛选模型的有效性。为了筛选所需的先导化合物,研究人员已经开发了大量的实验筛选模型。然而,从动物模型、组织模型到细胞模型等各种不同的筛选模型,可能会在选择合适的模型时造成一些困扰。
本综述提供了一个实验筛选模型的工具盒,这些模型已被用于从天然产物中发现新的药物候选物。在这个筛选工具盒中,为不同的研究方向设计了两个筛选指标。指标 I 是从筛选不同的目标物质群体的方向提出的,包括植物提取物、活性部分和纯化合物;指标 Π 是根据筛选不同的药物性质提出的,包括药理学性质、药代动力学性质和亲和结合性质。
我们希望通过这两个筛选指标,简短的参考文献能帮助读者快速检索到有用信息,并为选择更合适的筛选模型提供一定的参考价值。最后,我们讨论了改进模型系统的方法以及未来的发展方向。