Abstract:
:Caco-2 cell monolayers are widely used systems for predicting human intestinal absorption. This study was carried out to develop a quantitative structure-property relationship (QSPR) model of Caco-2 permeability using a novel genetic algorithm-based partial least squares (GA-PLS) method. The Caco-2 permeability data for 73 compounds were taken from the literature. Molconn-Z descriptors of these compounds were calculated as molecular descriptors, and the optimal subset of the descriptors was explored by GA-PLS analysis. A fitness function considering both goodness-of-fit to the training data and predictability of the testing data was adopted throughout the genetic algorithm-driven optimization procedure. The final PLS model consisting of 24 descriptors gave a correlation coefficient (r) of 0.886 for the entire dataset and a predictive correlation coefficient (r(pred)) of 0.825 that was evaluated by a leave-some-out cross-validation procedure. Thus, the GA-PLS analysis proved to be a reasonable QSPR modeling approach for predicting Caco-2 permeability.
journal_name
J Pharm Scijournal_title
Journal of pharmaceutical sciencesauthors
Yamashita F,Wanchana S,Hashida Mdoi
10.1002/jps.10214subject
Has Abstractpub_date
2002-10-01 00:00:00pages
2230-9issue
10eissn
0022-3549issn
1520-6017pii
S0022-3549(16)31090-5journal_volume
91pub_type
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