Exploring conformational dynamics of the HER2 DFG-flip using machine-learning-guided metadynamics for type II inhibitor design.
Together, these results provide a structurally grounded inactive-state HER2 model and a mechanistic framework for structure-based design of HER2 inhibitors targeting inactive kinase conformations, highlighting the applicability of deep learning CVs to systems of complex free energy landscape.