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For direct application of predictive models please contact
Sabina Podlewska (smusz@if-pan.krakow.pl)

During the drug design process, most attention is firstly put to obtain desired affinity with the appropriate receptors. However, failures of compounds at further stages of drug development is connected with other unfavorable properties - physicochemical, pharmacokinetic or due to compounds toxicity. The proper evaluation of such properties in silico is therefore not less important than the development of computational tools for correct activity predictions.

In this study we focus on one of the compounds parameter - metabolic stability and offer a freely available online tool for metabolic stability predictions. It uses ligand-based methodology and machine learning methods for evaluation of compounds stability with separate models constructed for various species.

The study was supported by the National Science Centre, Poland within the HARMONIA 7 grant 2015/18/M/NZ7/00377