Chang Cheng, Ekins Sean, Bahadduri Praveen, Swaan Peter W
Department of Pharmaceutical Sciences, School of Pharmacy, 20 Penn Street, HSF2-621, University of Maryland, Baltimore, Baltimore, MD 21201, USA.
Adv Drug Deliv Rev. 2006 Nov 30;58(12-13):1431-50. doi: 10.1016/j.addr.2006.09.006. Epub 2006 Sep 26.
The ability to identify ligands for drug transporters is an important step in drug discovery and development. It can both improve accurate profiling of lead pharmacokinetic properties and assist in the discovery of new chemical entities targeting transporters. In silico approaches, especially pharmacophore-based database screening methods have great potential in improving the throughput of current transporter ligand identification assays, leading to a higher hit rate by focusing in vitro testing to the most promising hits. In this review, the potential of different in silico methods in transporter ligand identification studies are compared and summarized with an emphasis on pharmacophore modeling. Various implementations of pharmacophore model generation, database compilation and flexible screening algorithms are also introduced. Recent successful utilization of database searching with pharmacophores to identify novel ligands for the pharmaceutically significant transporters hPepT1, P-gp, BCRP, MRP1 and DAT are reviewed and the challenges encountered with current approaches are discussed.
识别药物转运蛋白配体的能力是药物发现与开发中的重要一步。它既能改善先导药物药代动力学性质的准确分析,又有助于发现靶向转运蛋白的新化学实体。计算机辅助方法,尤其是基于药效团的数据库筛选方法,在提高当前转运蛋白配体识别试验的通量方面具有巨大潜力,通过将体外测试集中于最有前景的命中物,从而获得更高的命中率。在本综述中,比较并总结了不同计算机辅助方法在转运蛋白配体识别研究中的潜力,重点是药效团建模。还介绍了药效团模型生成、数据库编纂和灵活筛选算法的各种实现方式。综述了近期利用药效团数据库搜索来识别具有药学意义的转运蛋白hPepT1、P-gp、BCRP、MRP1和DAT的新型配体的成功案例,并讨论了当前方法所面临的挑战。