Combined 4D‐Fingerprint and Clustering Based Membrane‐Interaction QSAR Analyses for Constructing Consensus Caco‐2 Cell Permeation Virtual Screens
Time: 2016-03-17 02:29  Click:707

                    Journal of Pharmaceutical Sciences

                                              Volume 97, Issue 1, January 2008, Pages 566–583

Osvaldo A. Santos‐Filho1, , ,Anton J. Hopfinger2, 3
1 Division of Infectious Diseases, Faculty of Medicine, University of British Columbia, 2733 Heather Street, Vancouver, British Columbia, Canada V5Z 3J5
2 College of Pharmacy, MSC09 5360, 1 University of New Mexico, Albuquerque, New Mexico 87191‐0001
3 The Chem21 Group, Inc., 1780 Wilson Drive, Lake Forest, Illinois 60045

 

Abstract
A set of 30 structurally diverse molecules, for which Caco‐2 cell permeation coefficients were determined, formed the training set for construction of Caco‐2 cell permeation models based upon membrane‐interaction (MI) QSAR analysis and a new QSAR method called 4D‐fingerprint QSAR analysis. The descriptor terms of the 4D‐fingerprints equation are molecular similarity eigenvalues, and this set of descriptors is being evaluated as a potential “universal” QSAR descriptor set. The 4D‐fingerprint model suggests that Caco‐2 cell permeation is governed by the spatial distribution of hydrogen bonding and nonpolar groups over the molecular shape of a molecule. Moreover, a complementary resampling of the original Caco‐2 cell permeation training set, followed by the construction of several “clustered” MI‐QSAR models, led to a consensus model consistent in interpretation with the 4D‐fingerprint model. © 2007 Wiley‐Liss, Inc. and the American Pharmacists Association J Pharm Sci 97:566–583, 2008
 
Keywords
Caco‐2 cell permeation;membrane;QSAR;universal 4D‐fingerprint descriptors;drug absorption;molecular similarity;cluster analysis
 
Full text is available at http://www.sciencedirect.com/science/article/pii/S0022354916324509
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