期刊
MOLECULAR PHARMACEUTICS
卷 10, 期 10, 页码 3758-3768出版社
AMER CHEMICAL SOC
DOI: 10.1021/mp400251k
关键词
clearance; computational ADME; in silico modeling; QSPR; unbound clearance prediction; acidic drugs; elimination
Drug clearance is the most important of all pharmacokinetic parameters. It is affected significantly by the binding of drugs to serum proteins. Only the free (unbound) fraction of the drug is able to be cleared. The unbound clearance CLu is the clearance with reference to unbound drug in plasma C-u. CLu is independent of the plasma protein binding and depends only on drug chemical structure and properties. In the present study, the relationship between the unbound clearance CLu and the chemical structures of acidic drugs was modeled by a quantitative structure-clearance relationship (QSCLR) approach. The derived models were used to reveal the main structural features important for CLu. It was found that the lipophilicity of acidic drugs and the presence of substituents in the aromatic rings, cyano group, and/or nonpolar hydrogen atoms increase the rate of unbound clearance. The presence of sulfonyl groups, quaternary carbon atoms and/or eight-member ring system decreases the unbound clearance of drugs. Additionally, QSCLR models for renal, hepatic, and biliary clearances were derived.
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