Predicting reactivity to drug metabolism: beyond CYPs
Introduction Predicting sites of metabolism (SoM) enable chemists to be more efficient in optimising the structure of new chemical entities…
The Nova ideas generated depend on the parameters set by users’ input, which are based on over 200 commonly known transformations. The proposed compounds generated would make ‘sense’ to a chemist in terms of their properties.
Chapter 10 of the reference guide* describes the properties of the resulting predicted compounds and the most promising ideas are prioritised for further consideration to identify those that are most likely to have a good balance of the properties required in a high quality drug.
This example, which goes through the generation of new compound ideas using ‘Med. Chem. transformations’ and prioritised against a project’s requirements. This is based on an example we published in J. Chem. Inf. Model. 2011, 51 (11), pp. 2967-2976.
Just follow the step-by-step guidelines in this PDF and the associated example files can also be downloaded.
Introduction Predicting sites of metabolism (SoM) enable chemists to be more efficient in optimising the structure of new chemical entities…
In this webinar, we demonstrate how Augmented Chemistry®, a unique deep learning method, can learn from higher throughput data together with limited panel data to provide high-quality imputations for sensory properties.
Try Matched Series Analysis in this follow-along tutorial