Perturbation of ACE2 Structural Ensembles by SARS-CoV‑2 Spike Protein Binding

The human ACE2 enzyme
serves as a critical first recognition point
of coronaviruses, including SARS-CoV-2. In particular, the extracellular
domain of ACE2 interacts directly with the S1 tailspike protein of
the SARS-CoV-2 virion through a broad protein–protein interface.
Although this interaction has been characterized by X-ray crystallography,
these structures do not reveal significant differences in the ACE2
structure upon S1 protein binding. In this work, using several all-atom
molecular dynamics simulations, we show persistent differences in
the ACE2 structure upon binding. These differences are determined
with the linear discriminant analysis (LDA) machine learning method
and validated using independent training and testing datasets, including
long trajectories generated by D. E. Shaw Research on the Anton 2
supercomputer. In addition, long trajectories for 78 potent ACE2-binding
compounds, also generated by D. E. Shaw Research, were projected onto
the LDA classification vector in order to determine whether the ligand-bound
ACE2 structures were compatible with S1 protein binding. This allows
us to predict which compounds are “apo-like” versus
“complex-like” and to pinpoint long-range ligand-induced
allosteric changes in the ACE2 structure.