Druggability Assessment in TRAPP using Machine Learning Approaches
Jui-Hung Yuan, Sungho Bosco Han, Stefan Richter, Rebecca C. Wade, Daria B. Kokh
The paper develops two models, TRAPP-LR and TRAPP-CNN, to predict protein druggability and its variation with conformational changes, integrated into the TRAPP tool for analyzing binding pocket dynamics.
Journal of Chemical Information and Modeling · Feb 27, 2020Peer-reviewedBioinformatics