Rf. Liu et Ss. So, Development of quantitative structure-property relationship models for early ADME evaluation in drug discovery. 1. Aqueous solubility, J CHEM INF, 41(6), 2001, pp. 1633-1639
Citations number
27
Categorie Soggetti
Chemistry
Journal title
JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES
A simple QSPR model, based on seven 1D and 2D descriptors and artificial ne
ural network, was developed for fast evaluation of aqueous solubility. The
model was able to predict the molar solubility of a diverse set of 1312 org
anic compounds with an overall correlation coefficient of 0.92 and a standa
rd deviation of 0.72 log unit between the calculated and experimental data.
Considering the fact that the estimated uncertainty of the experimental da
ta is no less than 0.5 log unit, the results demonstrate that carefully cho
sen physically meaningful ID and 2D descriptors encode sufficient molecular
information for fast and reasonably reliable prediction of aqueous solubil
ity with a simple neural network. As a comparison, we calculated the solubi
lity of a test set of 258 compounds, ranging from simple hydrocarbons to mo
re complex multifunctional organic molecules, with a commercial program (QM
PR+ version 2.0.1 of SimulationPlus Inc.) and compared the results with pre
dictions from our model. Statistical parameters indicate that for small and
simple organic compounds, QMPR+ outperforms our model. However for more co
mplex multifunctional molecules, our model is superior.