Literature DB >> 20233033

Assessment of in silico models for fraction of unbound drug in human liver microsomes.

Hua Gao1, Stefanus J Steyn, George Chang, Jing Lin.   

Abstract

IMPORTANCE OF THE FIELD: Fraction of unbound drug in human liver microsome (fu(mic)) incubation media is an important parameter for accurate assessment of hepatic intrinsic clearance and drug-drug interactions. In recent years, there have been considerable advances in understanding structure-microsomal binding relationships. AREAS COVERED IN THE REVIEW: This review highlights the in silico modeling techniques for fu(mic) including physicochemical properties-based modeling, pharmacophore feature-based classification modeling and more complex statistical method-based modeling. The application of these modeling techniques to the understanding of the structure-binding relationships is also discussed. WHAT THE READER WILL GAIN: The reader will gain an understanding of the modeling techniques used for prediction of binding to human liver microsomes (fu(mic)). The reader will also understand the molecular structure-microsomal protein binding relationships. In all of these models, lipophilicity is the most important molecular property underlying the structure-binding relationship. Other molecular properties such as charge type (positive vs negative) and hydrogen bonding are also important factors for microsomal binding. TAKE HOME MESSAGE: The predictive accuracy of fu(mic) models in the high lipophilicity and tight microsomal binding ranges still needs to be further improved. However, in silico models are still valuable tools to aid chemical library design and prioritize multiple chemical series, which could provide efficiency and decrease knowledge cycle times in drug discovery.

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Year:  2010        PMID: 20233033     DOI: 10.1517/17425251003671022

Source DB:  PubMed          Journal:  Expert Opin Drug Metab Toxicol        ISSN: 1742-5255            Impact factor:   4.481


  7 in total

1.  Impact of low-dose ritonavir on danoprevir pharmacokinetics: results of computer-based simulations and a clinical drug-drug interaction study.

Authors:  Micaela B Reddy; Yuan Chen; Joshua O Haznedar; Jennifer Fretland; Steven Blotner; Patrick Smith; Jonathan Q Tran
Journal:  Clin Pharmacokinet       Date:  2012-07-01       Impact factor: 6.447

2.  Consideration of the Unbound Drug Concentration in Enzyme Kinetics.

Authors:  Nigel J Waters; R Scott Obach; Li Di
Journal:  Methods Mol Biol       Date:  2021

3.  Metabolic profiling of corylin in vivo and in vitro.

Authors:  Zifei Qin; Shishi Li; Zhihong Yao; Xiaodan Hong; Jinjin Xu; Pei Lin; Guoping Zhao; Frank J Gonzalez; Xinsheng Yao
Journal:  J Pharm Biomed Anal       Date:  2018-03-26       Impact factor: 3.935

4.  In vitrometabolic mapping of neobavaisoflavone in human cytochromes P450 and UDP-glucuronosyltransferase enzymes by ultra high-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry.

Authors:  Jinjin Xu; Mengsen Li; Zhihong Yao; Yezi Zhang; Shishi Li; Liufang Hu; Zifei Qin; Frank J Gonzalez; Xinsheng Yao
Journal:  J Pharm Biomed Anal       Date:  2018-06-18       Impact factor: 3.935

Review 5.  Successful and Unsuccessful Prediction of Human Hepatic Clearance for Lead Optimization.

Authors:  Jasleen K Sodhi; Leslie Z Benet
Journal:  J Med Chem       Date:  2021-03-25       Impact factor: 7.446

6.  Agent-based simulation of reactions in the crowded and structured intracellular environment: Influence of mobility and location of the reactants.

Authors:  Michael T Klann; Alexei Lapin; Matthias Reuss
Journal:  BMC Syst Biol       Date:  2011-05-14

7.  Developing a Physiologically-Based Pharmacokinetic Model Knowledgebase in Support of Provisional Model Construction.

Authors:  Jingtao Lu; Michael-Rock Goldsmith; Christopher M Grulke; Daniel T Chang; Raina D Brooks; Jeremy A Leonard; Martin B Phillips; Ethan D Hypes; Matthew J Fair; Rogelio Tornero-Velez; Jeffre Johnson; Curtis C Dary; Yu-Mei Tan
Journal:  PLoS Comput Biol       Date:  2016-02-12       Impact factor: 4.475

  7 in total

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