Automatic QSAR modeling of ADME properties: blood-brain barrier penetration and aqueous solubility
Summary
In this study, our researchers combined an automatic model generation process for building QSAR models with the Gaussian Processes machine learning method. The article outlines the process for model construction and validation, and applies the automatic process to blood-brain barrier penetration and aqueous solubility data sets. Results are compared with ‘manually’ built models using external test sets, and show the automatic process to be highly effective for both in vivo and physico-chemical data.
Citation details
O. Obrezanova, J. M. R. Gola, E. Champness, M. D. Segall, J. Comp. Aided Mol. Design, 2008, 22(6-7) pp. 431-440.
DOI: 10.1007/s10822-008-9193-8
Find out more
Visit the journal webpage to read the final peer-reviewed version of this article.
INTERESTED IN DRUG DISCOVERY?
Discover StarDrop™
With its comprehensive suite of integrated software, StarDrop™ delivers best-in-class in silico technologies within a highly visual and user-friendly interface. StarDrop™ enables a seamless flow from the latest data through predictive modelling to decision-making regarding the next round of synthesis and research, improving the speed, efficiency, and productivity of the drug optimisation and discovery process.