Check out the recently published article co-authored by Yurii Moroz and Olena Savych on generative and reinforcement learning approaches in designing biologically active compounds!
In this proof-of-concept study, the authors demonstrate the application of the deep generative recurrent neural network architecture to design inhibitors of the epidermal growth factor (EGFR) and further experimentally validate their potency. The proposed technical solutions are expected to substantially improve the success rate of finding novel bioactive compounds for specific biological targets.
You can find the link to the full publication here!
We also want to thank everyone for the great collaboration: Maria Korshunova, Niles Huang, Stephen Capuzzi, Dmytro S. Radchenko, Carrow I. Wells, Timothy M. Willson, Alexander Tropsha & Olexandr Isayev.
