Recent advances in computational prediction of drug absorption and permeability in drug discovery

被引:128
作者
Hou, Tingjun
Wang, Junmei
Zhang, Wei
Wang, Wei [1 ]
Xu, Xiaojie
机构
[1] Univ Calif San Diego, Dept Chem & Biochem, Ctr Theoret Biol Sci, La Jolla, CA 92093 USA
[2] Peking Univ, Coll Chem & Mol Engn, Beijing 100871, Peoples R China
[3] Scripps Res Inst, Dept Mol Biol, La Jolla, CA 92037 USA
关键词
ADME; drug adsorption; permeability; Caco-2; monolayer; blood-brain partitioning (BBB); logBB; QSAR;
D O I
10.2174/092986706778201558
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Approximately 40%-60% of developing drugs failed during the clinical trials because of ADME/Tox deficiencies. Virtual screening should not be restricted to optimize binding affinity and improve selectivity; and the pharmacokinetic properties should also be included as important filters in virtual screening. Here, the current development in theoretical models to predict drug absorption-related properties, such as intestinal absorption, Caco-2 permeability, and blood-brain partitioning are reviewed. The important physicochemical properties used in the prediction of drug absorption, and the relevance of predictive models in the evaluation of passive drug absorption are discussed. Recent developments in the prediction of drug absorption, especially with the application of new machine learning methods and newly developed software are also discussed. Future directions for research are outlined.
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页码:2653 / 2667
页数:15
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