Literature DB >> 19937826

In silico prediction of human oral absorption based on QSAR analyses of PAMPA permeability.

Miki Akamatsu1, Masaaki Fujikawa, Kazuya Nakao, Ryo Shimizu.   

Abstract

The parallel artificial membrane permeation assay (PAMPA) was developed as a model for the prediction of transcellular permeation in the process of drug absorption. Our research group has measured the PAMPA permeability of peptide-related compounds, diverse drugs, and agrochemicals. This work led to a classical quantitative structure-activity relationship (QSAR) equation for PAMPA permeability coefficients of structurally diverse compounds based on simple physicochemical parameters such as lipophilicity at a particular pH (log P(oct) and |pKa-pH|), H-bond acceptor ability (SA(HA)), and H-bond donor ability (SA(HD)). Since the PAMPA permeability of lipophilic compounds decreased with their apparent lipophilicity due to the unstirred water layer (UWL) barrier on membrane surfaces and to membrane retention, a bilinear QSAR model was introduced to explain the permeability of a broader set of compounds using the same physicochemical parameters as those used for the linear model. We also compared PAMPA and Caco-2 cell permeability coefficients of compounds transported by various absorption mechanisms. The compounds were classified according to their absorption pathway (passively transported compounds, actively transported compounds, and compounds excreted by efflux systems) in the plot of Caco-2 vs. PAMPA permeability. Finally, based on the QSAR analyses of PAMPA permeability, an in silico prediction model of human oral absorption for possibly transported compounds was proposed, and the usefulness of the model was examined.

Entities:  

Mesh:

Substances:

Year:  2009        PMID: 19937826     DOI: 10.1002/cbdv.200900112

Source DB:  PubMed          Journal:  Chem Biodivers        ISSN: 1612-1872            Impact factor:   2.408


  7 in total

1.  Highly predictive and interpretable models for PAMPA permeability.

Authors:  Hongmao Sun; Kimloan Nguyen; Edward Kerns; Zhengyin Yan; Kyeong Ri Yu; Pranav Shah; Ajit Jadhav; Xin Xu
Journal:  Bioorg Med Chem       Date:  2016-12-31       Impact factor: 3.641

2.  Drug discovery and regulatory considerations for improving in silico and in vitro predictions that use Caco-2 as a surrogate for human intestinal permeability measurements.

Authors:  Caroline A Larregieu; Leslie Z Benet
Journal:  AAPS J       Date:  2013-01-24       Impact factor: 4.009

Review 3.  In vitro blood-brain barrier models: current and perspective technologies.

Authors:  Pooja Naik; Luca Cucullo
Journal:  J Pharm Sci       Date:  2011-12-27       Impact factor: 3.534

4.  Modeling the pharmacodynamics of passive membrane permeability.

Authors:  Robert V Swift; Rommie E Amaro
Journal:  J Comput Aided Mol Des       Date:  2011-11-01       Impact factor: 3.686

5.  Translating Human Effective Jejunal Intestinal Permeability to Surface-Dependent Intrinsic Permeability: a Pragmatic Method for a More Mechanistic Prediction of Regional Oral Drug Absorption.

Authors:  Andrés Olivares-Morales; Hans Lennernäs; Leon Aarons; Amin Rostami-Hodjegan
Journal:  AAPS J       Date:  2015-05-19       Impact factor: 4.009

Review 6.  Intestinal Permeability and Drug Absorption: Predictive Experimental, Computational and In Vivo Approaches.

Authors:  David Dahlgren; Hans Lennernäs
Journal:  Pharmaceutics       Date:  2019-08-13       Impact factor: 6.321

7.  Development of a Hierarchical Support Vector Regression-Based In Silico Model for Caco-2 Permeability.

Authors:  Giang Huong Ta; Cin-Syong Jhang; Ching-Feng Weng; Max K Leong
Journal:  Pharmaceutics       Date:  2021-01-28       Impact factor: 6.321

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.