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Computational models for predicting substrates or inhibitors of P-glycoprotein

机译:预测P-糖蛋白底物或抑制剂的计算模型

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The impact of P-glycoprotein (P-gp) on the multidrug resistance and pharmacokinetics of clinically important drugs has been widely recognized.Here,we review tn 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.
机译:P-糖蛋白(P-gp)对临床上重要药物的多药耐药性和药代动力学的影响已得到广泛认可。总结了用于模型构建的数据集和可用的计算模型,并概述了这些模型的优缺点。综述了开发可靠的P-gp抑制剂或底物预测模型的挑战,以及克服这些挑战的策略。

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