Institute of Functional Nano & Soft Materials and Jiangsu Key Laboratory for Carbon-Based Functional Materials & Devices, Soochow University, Suzhou, Jiangsu 215123, China.
Drug Discov Today. 2012 Apr;17(7-8):343-51. doi: 10.1016/j.drudis.2011.11.003. Epub 2011 Nov 18.
The impact of P-glycoprotein (P-gp) on the multidrug resistance and pharmacokinetics of clinically important drugs has been widely recognized. Here, we review in silico approaches and computational models for identifying substrates or inhibitors of P-gp. The advances in the datasets for model building and available computational models are summarized and the advantages and drawbacks of these models are outlined. We also discuss the impact of the recently reported crystal structures of P-gp on potential breakthroughs in the computational modeling of P-gp substrates. Finally, the challenges of developing reliable prediction models for P-gp inhibitors or substrates, as well as the strategies to surmount these challenges, are reviewed.
P-糖蛋白（P-gp）对多种临床重要药物的耐药性和药代动力学的影响已得到广泛认可。在这里，我们回顾了用于鉴定 P-gp 底物或抑制剂的计算方法和计算模型。总结了用于模型构建和现有计算模型的数据集的进展，并概述了这些模型的优缺点。我们还讨论了最近报道的 P-gp 晶体结构对 P-gp 底物计算模型的潜在突破的影响。最后，综述了开发用于 P-gp 抑制剂或底物的可靠预测模型的挑战，以及克服这些挑战的策略。
