Díaz-Rovira, Anna M.

Are Deep Learning Structural Models Sufficiently Accurate for Virtual Screening? Application of Docking Algorithms to AlphaFold2 Predicted Structures

Díaz-Rovira, A. M., Martín, H., Beuming, T., Díaz, L., Guallar, V., & Ray, S. S. (2022) · Journal of Chemical Information and Modeling

Computational Drug Discovery MethodsProtein Structure and Dynamics

Cited by 95

Are Deep Learning Structural Models Sufficiently Accurate for Free Energy Calculations? Application of FEP+ to AlphaFold2 Predicted Structures

Beuming, T., Martín, H., Díaz-Rovira, A. M., Díaz, L., Guallar, V., & Ray, S. S. (2022) · Journal of Chemical Information and Modeling

Computational Drug Discovery MethodsProtein Structure and Dynamics

Cited by 61

Are Deep Learning Structural Models Sufficiently Accurate for Free-Energy Calculations? Application of FEP+ to AlphaFold2-Predicted Structures

Beuming, T., Martín, H., Díaz-Rovira, A. M., Díaz, L., Guallar, V., & Ray, S. S. (2022) · Journal of Chemical Information and Modeling

Computational Drug Discovery MethodsProtein Structure and Dynamics

Cited by 61

Tandem metalloenzymes gate plant cell entry by pathogenic fungi

Bissaro, B., Kodama, S., Nishiuchi, T., Díaz-Rovira, A. M., Hage, H., Ribeaucourt, D., Haon, M., Grisel, S., Simaan, A. J., Beisson, F., et al. (2022) · Science Advances

Plant Pathogens and Fungal DiseasesPlant-Microbe Interactions and Immunity

Cited by 37