Back

Trimeric SARS-CoV-2 Spike interacts with dimeric ACE2 with limited intra-Spike avidity

Lui, I.; Zhou, X. X.; Lim, S. A.; Elledge, S.; Solomon, P.; Rettko, N. J.; Zha, B. S.; Kirkemo, L. L.; Gramespacher, J. A.; Liu, J.; Muecksch, F.; Lorenzi, J. C. C.; Schmidt, F.; Weisblum, Y.; Robbiani, D. F.; Nussenzweig, M. C.; Hatziioannou, T.; Bieniasz, P. D.; Rosenberg, O.; Leung, K. K.; Wells, J. A.

2020-05-21 biochemistry
10.1101/2020.05.21.109157 bioRxiv
Show abstract

A serious public health crisis is currently unfolding due to the SARS-CoV-2 pandemic. SARS-CoV-2 viral entry depends on an interaction between the receptor binding domain of the trimeric viral Spike protein (Spike-RBD) and the dimeric human angiotensin converting enzyme 2 (ACE2) receptor. While it is clear that strategies to block the Spike/ACE2 interaction are promising as anti-SARS-CoV-2 therapeutics, our current understanding is insufficient for the rational design of maximally effective therapeutic molecules. Here, we investigated the mechanism of Spike/ACE2 interaction by characterizing the binding affinity and kinetics of different multimeric forms of recombinant ACE2 and Spike-RBD domain. We also engineered ACE2 into a split Nanoluciferase-based reporter system to probe the conformational landscape of Spike-RBDs in the context of the Spike trimer. Interestingly, a dimeric form of ACE2, but not monomeric ACE2, binds with high affinity to Spike and blocks viral entry in pseudotyped virus and live SARS-CoV-2 virus neutralization assays. We show that dimeric ACE2 interacts with an RBD on Spike with limited intra-Spike avidity, which nonetheless contributes to the affinity of this interaction. Additionally, we demonstrate that a proportion of Spike can simultaneously interact with multiple ACE2 dimers, indicating that more than one RBD domain in a Spike trimer can adopt an ACE2-accessible "up" conformation. Our findings have significant implications on the design strategies of therapeutic molecules that block the Spike/ACE2 interaction. The constructs we describe are freely available to the research community as molecular tools to further our understanding of SARS-CoV-2 biology.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.