Prediction of Human Intestinal Absorption of Drug Compounds from Molecular Structure

• Published in: Journal of Chemical Information and Computer Sciences Vol. 38; no. 4; pp. 726 - 735
• Main Authors: Wessel, Matthew D, Jurs, Peter C, Tolan, John W, Muskal, Steven M
• Format: Journal Article
• Language: English
• Published: United States American Chemical Society 01.07.1998
• Subjects: Humans; Intestinal Absorption; Linear Models; Models, Biological; Molecular Structure; Neural Networks (Computer); Pharmacokinetics; Structure-Activity Relationship
• ISSN: 0095-2338; 1549-960X; 1520-5142
• DOI: 10.1021/ci980029a

The absorption of a drug compound through the human intestinal cell lining is an important property for potential drug candidates. Measuring this property, however, can be costly and time-consuming. The use of quantitative structure−property relationships (QSPRs) to estimate percent human intestinal absorption (%HIA) is an attractive alternative to experimental measurements. A data set of 86 drug and drug-like compounds with measured values of %HIA taken from the literature was used to develop and test a QSPR model. The compounds were encoded with calculated molecular structure descriptors. A nonlinear computational neural network model was developed by using the genetic algorithm with a neural network fitness evaluator. The calculated %HIA (cHIA) model performs well, with root-mean-square (rms) errors of 9.4%HIA units for the training set, 19.7%HIA units for the cross-validation (CV) set, and 16.0%HIA units for the external prediction set.