Literature DB >> 22580868

Physicochemical property space of hepatobiliary transport and computational models for predicting rat biliary excretion.

Manthena V S Varma1, George Chang, Yurong Lai, Bo Feng, Ayman F El-Kattan, John Litchfield, Theunis C Goosen.   

Abstract

Biliary excretion (BE) is a major elimination pathway, and its prediction is particularly important for optimization of systemic and/or target-site exposure of new molecular entities. The objective is to characterize the physicochemical space associated with hepatobiliary transport and rat BE and to develop in silico models. BE of 123 in-house compounds was obtained using the bile-duct cannulated rat model. Human and rat hepatic uptake transporters (hOATP1B1, hOATP1B3, hOATP2B1, and rOatp1b2) substrates (n = 183) were identified using transfected cells. Furthermore, the datasets were extended by adding BE of 163 compounds and 97 organic anion transporting polypeptide (OATP) substrates from the literature. Approximately 60% of compounds showing percentage of BE (%BE) ≥ 10 are anions, with mean BE of anions (36%) more than 3-fold higher than that of nonacids (11%). Compounds with %BE ≥ 10 are found to have high molecular mass, large polar surface area, more rotatable bonds, and high H-bond count, whereas the lipophilicity and passive membrane permeability are lower compared with compounds with %BE < 10. According to statistical analysis and principal component analysis, hOATPs and rOatp1b2 substrates showed physicochemical characteristics that were similar to those of the %BE ≥ 10 dataset. We further build categorical in silico models to predict rat BE, and the models (gradient boosting machine and scoring function) developed showed 80% predictability in identifying the rat BE bins (%BE ≥ 10 or < 10). In conclusion, the significant overlap of the property space of OATP substrates and rat BE suggests a predominant role of sinusoidal uptake transporters in biliary elimination. Categorical in silico models to predict rat BE were developed, and successful predictions were achieved.

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Year:  2012        PMID: 22580868     DOI: 10.1124/dmd.112.044628

Source DB:  PubMed          Journal:  Drug Metab Dispos        ISSN: 0090-9556            Impact factor:   3.922


  9 in total

1.  Predicting Clearance Mechanism in Drug Discovery: Extended Clearance Classification System (ECCS).

Authors:  Manthena V Varma; Stefanus J Steyn; Charlotte Allerton; Ayman F El-Kattan
Journal:  Pharm Res       Date:  2015-07-09       Impact factor: 4.200

2.  Estimation of biliary excretion of foreign compounds using properties of molecular structure.

Authors:  Mohsen Sharifi; Taravat Ghafourian
Journal:  AAPS J       Date:  2013-11-08       Impact factor: 4.009

3.  Predicting the extent of metabolism using in vitro permeability rate measurements and in silico permeability rate predictions.

Authors:  Chelsea M Hosey; Leslie Z Benet
Journal:  Mol Pharm       Date:  2015-04-23       Impact factor: 4.939

4.  Absorption, Distribution, Metabolism, and Excretion of the Androgen Receptor Inhibitor Enzalutamide in Rats and Dogs.

Authors:  Yoshiaki Ohtsu; Jacqueline A Gibbons; Katsuhiro Suzuki; Michael E Fitzsimmons; Kohei Nozawa; Hiroshi Arai
Journal:  Eur J Drug Metab Pharmacokinet       Date:  2017-08       Impact factor: 2.441

Review 5.  Prediction of pharmacokinetics and drug-drug interactions when hepatic transporters are involved.

Authors:  Rui Li; Hugh A Barton; Manthena V Varma
Journal:  Clin Pharmacokinet       Date:  2014-08       Impact factor: 6.447

6.  Predicting when biliary excretion of parent drug is a major route of elimination in humans.

Authors:  Chelsea M Hosey; Fabio Broccatelli; Leslie Z Benet
Journal:  AAPS J       Date:  2014-07-09       Impact factor: 4.009

7.  Unmasking the Role of Uptake Transporters for Digoxin Uptake Across the Barriers of the Central Nervous System in Rat.

Authors:  Kunal S Taskar; T Thanga Mariappan; Vishwanath Kurawattimath; Shashyendra Singh Gautam; T V Radhakrishna Mullapudi; Srikanth K Sridhar; Raja Reddy Kallem; Punit Marathe; Sandhya Mandlekar
Journal:  J Cent Nerv Syst Dis       Date:  2017-03-15

Review 8.  Examination of Urinary Excretion of Unchanged Drug in Humans and Preclinical Animal Models: Increasing the Predictability of Poor Metabolism in Humans.

Authors:  Nadia O Bamfo; Chelsea Hosey-Cojocari; Leslie Z Benet; Connie M Remsberg
Journal:  Pharm Res       Date:  2021-07-12       Impact factor: 4.580

9.  Novel testing strategy for prediction of rat biliary excretion of intravenously administered estradiol-17β glucuronide.

Authors:  Annelies Noorlander; Eric Fabian; Bennard van Ravenzwaay; Ivonne M C M Rietjens
Journal:  Arch Toxicol       Date:  2020-11-07       Impact factor: 5.153

  9 in total

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