ADMET property prediction: The state of the art and current challenges
Summary This article discusses Quantitative Structure – Activity relationships (QSAR) methods to predict absorption, distribution, metabolism, excretion and toxicity (ADMET)…
This is due to a difference in data quality. The CYP2D6 model is categorical due to an uneven distribution in Ki values in the data set and uncertainty regarding the purity of some compounds going into the assay. The CYP2C9 data was more robust, lending itself to a continuous model.
You can find information on the models in Section 17 of the StarDrop Reference Guide, which can be accessed via the Help menu in StarDrop.
Experimental data is used to create the models and this process is described in detail in this section.
More QSAR resources
pKa prediction using quantum mechanics and machine learning
The dissociation of a proton from a heteroatom has a significant influence on the charge distribution and interactions of a…
Compound prioritisation and selection
In this demo we’re going to take a look at how StarDrop can guide the prioritisation and selections of compounds using a combination of in vitro and in silico data.
