The group of Theoretical Structural Biology at the Technical University of Berlin is led by Dr. Ariane Nunes Alves. One of our main interests is the development and application of computational methods to predict kinetic rates for protein-ligand binding and enzyme-substrate binding. Knowledge of binding pathways and fine tuning of kinetic rates can lead to better drugs and improved enzyme catalysis. The main methods we use to study binding kinetics are molecular dynamics simulations and machine learning.
Another main interest is to understand how crowded environments affect protein-ligand binding and enzyme catalysis. While experiments and simulations to characterize proteins are usually performed using low concentration of proteins, the environment inside cells is crowded with different macromolecules. Such environment may affect binding and catalysis through excluded volume effects and quinary interactions.
Another main interest is to understand how crowded environments affect protein-ligand binding and enzyme catalysis. While experiments and simulations to characterize proteins are usually performed using low concentration of proteins, the environment inside cells is crowded with different macromolecules. Such environment may affect binding and catalysis through excluded volume effects and quinary interactions.
Publications
Ganna Gryn’ova, Tristan Bereau, Carolin Müller, Pascal Friederich, Rebecca C. Wade, Ariane Nunes-Alves, Thereza A. Soares, Kenneth Jr. Merz
Journal of Chemical Information and Modeling, vol. 64, 2024, pp. 5737-5738
Characterization of the Bottlenecks and Pathways for Inhibitor Dissociation from [NiFe] Hydrogenase
Farzin Sohraby, Ariane Nunes-Alves
Journal of Chemical Information and Modeling, vol. 64, 2024, pp. 4193-4203
Fiona Berger, Guillermo M. Gomez, Cecilia P. Sanchez, Britta Posch, Gabrielle Planelles, Farzin Sohraby, Ariane Nunes-Alves, Michael Lanzer
Nature Communications, 2023
Advances in computational methods for ligand binding kinetics
Farzin Sohraby, Ariane Nunes-Alves
Trends in Biochemical Sciences, 2023
AlphaFold2 in Molecular Discovery
Ariane Nunes-Alves, Kenneth Merz
Journal of Chemical Information and Modeling, vol. 63, 2023, pp. 5947-5949
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