Identifying the Zoonotic Origin of SARS-CoV-2 by Modeling the Binding Affinity between the Spike Receptor-Binding Domain and Host ACE2

Abstract

Despite considerable research progress on SARS-CoV-2, the direct zoonotic origin (intermediate host) of the virus remains ambiguous. The most definitive approach to identify the intermediate host would be the detection of SARS-CoV-2-like coronaviruses in wild animals. However, due to the high number of animal species, it is not feasible to screen all the species in the laboratory. Given that binding to ACE2 proteins is the first step for the coronaviruses to invade host cells, we propose a computational pipeline to identify potential intermediate hosts of SARS-CoV-2 by modeling the binding affinity between the Spike receptor-binding domain (RBD) and host ACE2. Using this pipeline, we systematically examined 285 ACE2 variants from mammals, birds, fish, reptiles, and amphibians, and found that the binding energies calculated for the modeled Spike-RBD/ACE2 complex structures correlated closely with the effectiveness of animal infection as determined by multiple experimental data sets. Built on the optimized binding affinity cutoff, we suggest a set of 96 mammals, including 48 experimentally investigated ones, which are permissive to SARS-CoV-2, with candidates from primates, rodents, and carnivores at the highest risk of infection. Overall, this work not only suggests a limited range of potential intermediate SARS-CoV-2 hosts for further experimental investigation, but also, more importantly, it proposes a new structure-based approach to general zoonotic origin and susceptibility analyses that are critical for human infectious disease control and wildlife protection.

Keywords: EvoEF2 energy unit; SARS-CoV-2; binding affinity; intermediate host; zoonotic origin.

Figure 1.. A computational pipeline for ACE2 usage analysis.

321 ACE2 orthologs were downloaded from NCBI. The crystal structure of the hACE2/S-RBD complex (PDB ID: 6M0J) was used as a template for homology modeling. For each ACE2/S-RBD pair, 100 initial Modeller complex models were constructed and repacked by FASPR, and then five models were generated by EvoEF2/SAMC remodeling for each FASPR model. The binding energy cutoff (E_cutoff) was set to −47 EvoEF2 energy units.

Figure 2.. Mapping the calculated binding energy to 285 vertebrates.

The ACE2 proteins are categorized by their animal Class (Actinopterygii, Amphibia, Aves, Chondrichthyes, Mammalia, Reptilia, and Sarcopterygii) and ranked by the binding energy from low to high in each Class. The ACE2 proteins that are experimentally shown to be effective or less effective to SARS-CoV-2 are shown in blue and orange circles, respectively, while the others are shown in gray circles. Susceptible and insusceptible animals are highlighted in blue and red, respectively. The error bars were estimated via bootstrapping by subsampling with replacement for 500 data points from the original dataset of 500 binding scores for each species; the bootstrap steps were repeated for 1000 times.

Figure 3.. Putative N-glycosylation sites at the interface of two example ACE2/S-RBD complex structures.

(a) Eurasian common shrew (Sorex araneus); and (b) Aardvark (Orycteropus afer). ACE2 and S-RBD are shown in green and cyan cartoons, respectively. The potential interface N-glycosylation motifs are shown with the asparagine residues highlighted in spheres.

Figure 4.. Comparison of the mutated interface between hACE2/S-RBD and animal-ACE2/S-RBD.

(a) hACE2/S-RBD versus marmoset-ACE2/S-RBD; (b) hACE2/S-RBD versus pangolin-ACE2/S-RBD; and (c) hACE2/S-RBD versus turtle-ACE2/S-RBD. Residues in ACE2 and S-RBD are shown in magenta and yellow, respectively. Hydrogen bonds are shown in green dashed-lines.