Literature DB >> 11911703

Predicting Caco-2 cell permeation coefficients of organic molecules using membrane-interaction QSAR analysis.

Amit Kulkarni1, Yi Han, A J Hopfinger.   

Abstract

A methodology termed membrane-interaction QSAR (MI-QSAR) analysis has been developed in order to predict the behavior of organic compounds interacting with the phospholipid-rich regions of biological membranes. One important application of MI-QSAR analysis is to estimate ADME properties including the transport of organic solutes through biological membranes as a computational approach to forecasting drug intestinal absorption. A training set of 30 structurally diverse drugs, whose permeability coefficients across the cellular membranes of Caco-2 cells were measured, was used to construct significant MI-QSAR models of Caco-2 cell permeation. Cellular permeation is found to depend primarily upon aqueous solvation free energy (solubility) of the drug, the extent of drug interaction with a model phospholipid (DMPC) monolayer, and the conformational flexibility of the solute within the model membrane. A test set of eight drugs was used to evaluate the predictivity of the MI-QSAR models. The permeation coefficients of the test set compounds were predicted with the same accuracy as the compounds of the training set.

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Year:  2002        PMID: 11911703     DOI: 10.1021/ci010108d

Source DB:  PubMed          Journal:  J Chem Inf Comput Sci        ISSN: 0095-2338


  19 in total

1.  A cell-based molecular transport simulator for pharmacokinetic prediction and cheminformatic exploration.

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Review 2.  Recent progress in the computational prediction of aqueous solubility and absorption.

Authors:  Stephen R Johnson; Weifan Zheng
Journal:  AAPS J       Date:  2006-02-03       Impact factor: 4.009

Review 3.  Computational methods in drug discovery.

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Journal:  Pharmacol Rev       Date:  2013-12-31       Impact factor: 25.468

4.  Insights into the permeability of drugs and drug-like molecules from MI-QSAR and HQSAR studies.

Authors:  Ranajit N Shinde; K Srikanth; M Elizabeth Sobhia
Journal:  J Mol Model       Date:  2011-06-03       Impact factor: 1.810

5.  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

6.  Testing physical models of passive membrane permeation.

Authors:  Siegfried S F Leung; Jona Mijalkovic; Kenneth Borrelli; Matthew P Jacobson
Journal:  J Chem Inf Model       Date:  2012-05-24       Impact factor: 4.956

7.  Chemical substituent effect on pyridine permeability and mechanistic insight from computational molecular descriptors.

Authors:  I-Jen Chen; Rajneesh Taneja; Daxu Yin; Paul R Seo; David Young; Alexander D MacKerell; James E Polli
Journal:  Mol Pharm       Date:  2006 Nov-Dec       Impact factor: 4.939

8.  Predicting blood-brain barrier partitioning of organic molecules using membrane-interaction QSAR analysis.

Authors:  Manisha Iyer; Rama Mishra; Yi Han; A J Hopfinger
Journal:  Pharm Res       Date:  2002-11       Impact factor: 4.200

9.  Molecular dynamics simulations of ethanol permeation through single and double-lipid bilayers.

Authors:  Mahdi Ghorbani; Eric Wang; Andreas Krämer; Jeffery B Klauda
Journal:  J Chem Phys       Date:  2020-09-28       Impact factor: 3.488

10.  Decomposition mechanism of 3-N-morpholinosydnonimine (SIN-1)--a density functional study on intrinsic structures and reactivities.

Authors:  Roy U Rojas Wahl
Journal:  J Mol Model       Date:  2004-03-02       Impact factor: 1.810

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