Modeling of Ligand Binding to the HIF-2α Protein with Enhanced Sampling Methods

Ligand-protein interactions play a key role in protein functions. Ligand binding to biological targets can be effectively studied using molecular dynamics (MD) simulations with enhanced sampling technique to explore the long time-scales of such processes [1]⁠. The study-case here investigated is the Hypoxia Inducible Factor-2α (HIF-2α), a transcription factor that responds to decreases in available oxygen in the cellular environment (hypoxia). A domain of this protein (the HIF-2α PAS-B) contains a preformed cavity inaccessible to the solvent and able to bind artificial ligands which role as potential anticancer drugs is attracting great interest. Several crystallographic structures of HIF-2α in complex with different ligands have become available, and both thermodynamic and kinetic data associated to the binding/unbinding process of some ligands have been experimentally determined [2]. The aim of this study is to get an accurate mechanistic description of ligand binding to HIF-2α using computational methods able to simulate the dynamics of the process. Among the MD-based enhanced sampling techniques, we tested and compared: Steered MD [3] to identify the exit paths of the ligands from the pocket of HIF-2α PAS-B; Umbrella Sampling [4]⁠ to predict the free-energy profiles on the previously identified pathways; Path Collective Variables [5] to optimize the paths and obtain a more accurate description of the process. After an initial test of the different methods on a single ligand, the study will be extended to all the HIF-2α ligands for which experimental information is available to set up a reliable computational protocol for predictive studies. [1] Rydzewski, J. & Nowak, W., Phys. Life Rev. 22–23, 58–74 (2017) [2] Key, J., Scheuermann, T. H., Anderson, P. C., Daggett, V. & Gardner, K. H., J. Am. Chem. Soc. 131, 17647– 54 (2009) [3] Patel, J. S., Berteotti, A., Ronsisvalle, S., Rocchia, W. & Cavalli, A., J. Chem. Inf. Model. 54, 470–480 (2014) [4] Kästner, J., Wiley Interdiscip. Rev. Comput. Mol. Sci. 1, 932–942 (2011) [5] Tiwary, P., Limongelli, V., Salvalaglio, M. & Parrinello, M., Proc. Natl. Acad. Sci. 112, E386–E391 (2015)