The infectivity of SARS-CoV-2 is mainly determined by the binding affinity of the ACE2 and RBD complex, although the furin cleavage site plays a crucial role as well. (18) Omicron has three mutations at the furin cleavage site and 15 mutations on the RBD, suggesting a significant change in its infectivity.
Since the virus has optimized its infectivity in human cells, one should not expect a dramatic increase in the viral infectivity by any single mutation. An effective infection pathway is for the virus to have multiple RBD mutations to accumulatively enhance its infectivity, which appears to be the case for Omicron.This work analyzes the infectivity of Omicron by examining the BFE changes of the ACE2 and S protein complex induced by 15 Omicron RBD mutations.
Figure 1a illustrates the binding complex of ACE2 and S protein RBD. Most of the RBD mutations are located near the binding interface of ACE2 and RBD, except for mutations G339D, S371L, S373P, and S375F. Omicron-induced BFE changes are depicted in Figure 1b.
Overall, mutations significantly increase the BFE changes, which strengthen the binding affinity of the ACE2–RBD complex and makes the variant more infectious. This result indicates that Omicron appears to have followed the infectivity-strengthening pathway of natural selection. (21)
The infectivity-strengthening mutations N440K, T478K, and N501Y enhance the BFEs by 0.62, 1.00, and 0.55 kcal/mol, respectively. Among them, T478K is one of two RBD mutations in the Delta variant, while N501Y is presented on many prevailing variants, including Alpha, Beta, Gamma, Theta, and Mu. Notably, mutation Y505H induces a small negative BFE change of −0.20 kcal/mol.
All other mutations, particular those four mutations that are far away from the ACE2 and RBD binding interface, cause little or no BFE changes. Figure 1c gives a comparison of Omicron with a few other named variants, i.e., Alpha, Beta, Gamma, Delta, Theta, Kappa, and Mu.
The BFE changes indicate that Omicron is more infectious than other named variants. Specifically, the accumulated BFE change is 2.60 kcal/mol, suggesting a 13-fold increase in the viral Infectivity. In comparison, Omicron is about 2.8 times as infectious as the Delta (i.e., BFE change: 1.57 kcal/mol for Delta).
Vaccination has been proven to be the most effective means for COVID-19 prevention and control. There are four types of vaccines, i.e., virus vaccines, viral-vector vaccines, DNA/RNA vaccines, and protein-based vaccines. (22) Essentially, the current COVID-19 vaccines in use mainly target the S protein. (23) The 32 amino acid changes, including three small deletions and one small insertion in the spike protein, suggest that Omicron may be induced by antibody resistance. (17) As a result, these mutations may dramatically enhance the variant’s ability to evade current vaccines.
In general, it is essentially impossible to accurately characterize the full impact of Omicron’s S protein mutations on the current vaccines in the world’s populations. First, different types of vaccines may lead to different immune responses from the same individual. Additionally, different individuals characterized by race, gender, age, and underlying medical conditions may produce different sets of antibodies from the same vaccine. Moreover, the reliability of statistical analysis over populations may be limited because of the inability to fully control various experimental conditions.
This work offers a molecule-based data-driven analysis of Omicron’s impact on vaccines through a library of 185 known antibody and S protein complexes. We evaluate the binding free energy changes induced by 15 RBD mutations on these complexes to understand the potential impact of Omicron’s RBD mutations to vaccines. To ensure reliability, our study does not include a few known antibody–S protein complexes that are far away from the RBD, such as those in the N-terminal domain (NTD), due to limited experimental data in our antibody library. (10,11)Figure 2a, b1, and b2 depict the Omicron RBD mutation-induced BFE changes of 185 known antibody and RBD complexes.
Overall, Omicron RBD mutations can significantly change the binding pattern of known antibodies. Positive changes strengthen the binding between antibody and RBD complexes, while negative changes weaken the binding. In the color bar, the largest negative change is more significant than the largest positive change, indicating more severe disruptive impacts. In general, there are more negative BFE changes than positive ones, as shown in Figure 2, indicating that the Omicron mutations favor the escape of current vaccines.
Among 15 RBD mutations, K417N, also part of the Beta variant that originated in South Africa, causes the most significant disruption of known antibodies. Notably, E484A is another mutation that leads to overwhelmingly disruptive effects to many known antibodies. It is worth mentioning that most of E484A’s disruptive effects are complementary to those of K417N, which makes Omicron more effective in vaccine breakthroughs. The third disruptive mutation is Y505H. It is also able to weaken many known antibody and RBD complexes.
Mutation G339D creates a mild impact on various antibody–RBD complexes. One of the reasons is that it locates pretty far away from the binding interfaces of most known antibodies. Its change from a noncharged amino acid to a negatively charged amino acid induces mostly favorable bindings among many antibody–RBD complexes. S371L, S373P, and S375F are other mutations that have mild impacts due to their locations.For a comparison, ACE2 is also included in Figure 2b1. The impact of Omicron on ACE2 is significantly weak, indicating the SARS-CoV-2 has already optimized its binding with ACE2, and there is a relatively limited potential for the virus to improve its infectivity. However, due to the increase in the vaccination rate, variants can become more destructive to vaccines in years to come. (17)Figure 2a gives a separate plot of the impacts of Omicron on a few mAbs. Similarly, there are dramatic reductions in their efficacy.
A more specific discussion is given in the next section.Figure 3 provides the analysis of variant mutation-induced BFE changes of 185 antibody–RBD complexes induced by Omicron, Alpha, Beta, Delta, Gamma, Lambda, and Mu mutations. From Figure 3a1, it is clear that most complexes have negative accumulated BFE changes, indicating Omicron may disrupt most antibody–RBD binding complexes. In contrast, Delta’s distribution focuses on a smaller domain as shown in Figure 3e1. The BEF changes are essentially distributed around zero, suggesting Delta RBD mutations may not disrupt most known antibody–RBD binding complexes. The distributions of Beta and Gamma, respectively, in Figure 3c1 and d1 also indicate potential antibody–RBD binding complex disruption.
It becomes very subtle to judge whether a mutation would disrupt an antibody and RBD complex as Omicron involves multiple vaccine-escape RBD mutations, which may generate multiple cancellations for each antibody–RBD complex over different mutations. It is useful to focus on disruptive mutations, i.e, mutations leading to negative BFE changes. Therefore, we previously have used −0.3 kcal/mol as a threshold to judge whether a mutation disrupts an antibody–RBD complex, which would give us a total of 163 disrupted antibody–RBD complexes as shown in Figure 3a2, suggesting a rate of 0.88 (i.e., 163/185) for potential vaccine breakthrough. As a comparison, Delta has 70 counts and a rate of 0.37 (70/185) in a similar estimation as shown in Figure 3e2. One would have 143 and 48 disrupted antibody and RBD complexes, respectively, for Omicron and Delta if the threshold is increased to −0.6 kcal/mol. In both cases, Omicron is over twice more likely to disrupt antibody–RBD complexes. Note that Beta and Gamma in Figure 3c2 and d2 show a similar pattern.
The assessment of Omicron’s mutational threats to FDA-approved mAbs and a few other mAbs in clinical development is of crucial importance. Our AI-based predictions of similar threats from other variants, namely, Alpha, Beta, Gamma, Delta, Epsilon, and Kappa, have shown excellent agreements with experimental data. (11) In this section, we select a few mAbs, specifically, mAbs from Eli Lilly (LY-CoV016 and LY-CoV555), Regeneron (REGN10933, REGN10987, and REGN10933/10987), AstraZeneca (AZD1061 and AZD8895), GlaxoSmithKline (S309), Celltrion (CT-P59), and the Rockefeller University (C135 and C144). Among them, mAbs from Eli Lilly, Regeneron, AstraZeneca, and GlaxoSmithKline have had FDA approval. In addition, Celltrion’s COVID-19 antibody treatment had the EU drug agency’s recommendation in November 2021. Rockefeller University’s mAbs are still in clinical trials. Our analysis focuses on disruptive RBD mutations.
Eli Lilly mAbs
Eli Lilly mAb LY-CoV555 (PDB ID: 7KMG(24)) is also known as Bamlanivimab and is used in combination with LY-CoV016 (aka Etesevimab, PDB ID: 7C01(25)). Antibody LY-CoV016 is isolated from patient peripheral blood mononuclear cells convalescing from COVID-19. It was optimized based on the SARS-CoV-2 virus. The interaction of Eli Lilly mAbs with the S protein RBD is depicted in Figure 4a. ACE2 is included as a reference, indicating both LY-CoV016 and LY-CoV555 can directly neutralize the virus. Clearly, LY-CoV555 has a competing relationship with LY-CoV016, which might complicate our predictions slightly. In this work, we carry out the analysis of Eli Lilly mAbs separately.
Omicron mutation-induced BFE changes for the antibody LY-CoV016 and RBD complex is given in Figure 4b. It appears that LY-CoV555 was optimized with respect to the original S protein but is sensitive to mutations. This complex may be weakened by K417N and N501Y as predicted in our earlier work. (11) New mutation Y505H may also reduce LY-CoV016’s efficacy. Overall, the complex may be significantly weakened by Omicron, leading to the efficacy reduction of Etesevimab.The predicted BFE changes of LY-CoV555 are shown in Figure 4c. Mutation E484A induces a negative BFE change of −2.79 kcal/mol for the LY-CoV555 and RBD complex.
The BFE change may translate into a dramatic efficacy reduction of 16 times for LY-CoV555, making it less competitive with ACE2 as most Omicron mutations strengthen the S protein and ACE2 binding. Similarly, Q493R may also reduce the efficacy by about 5 times. However, G496S may enhance the binding of the complex. The impacts of other mutations are mild. Therefore, Omicron is expected to reduce LY-CoV555 efficacy significantly. A previous study indicated that LY-CoV555 is prone to the E484K mutation presented in Beta and Gamma variants, for which the Eli Lilly mAb cocktail was taken off the market for many months in 2021.Although LY-CoV555 and LY-CoV016 might slightly complement, they are both prone to Omicron mutation-induced efficacy reduction. We predict that the Eli Lilly mAb cocktail will be retaken off the market if Omicron becomes a prevailing variant in the world.
Regeneron mAbs REGN10933 and REGN10987 (aka Casirivimab and Imdevimab, respectively) are FDA-approved antibody cocktails (PDB ID: 6XDG(26)) against COVID-19. Their 3D structures in complex with the S protein RBD are depicted in Figure 5a. ACE2 is inclused as a reference. Unlike the Eli Lilly mAb cocktail, the Regeneron mAbs do not overlap each other and bind to different parts of the RBD.
Our 3D alignment shows that the antibody REGN10987 does not directly compete with ACE2 on their binding interfaces with the RBD but still spatially conflicts with ACE2. As a result, REGN10987 can directly neutralize the virus but is less sensitive to infectivity-induced RBD mutations. In contrast, REGN10933 overlaps with ACE2 both spatially and on the RBD binding interface. Consequently, REGN10933 is prone to infectivity-induced RBD mutations.
Figure 5b plots our AI predicted BFE changes of the REGN10987-RBD complex. There are mixed responses to various Omicron mutations. Although G446K and K417N induce a negative BFE change, many other mutations may enhance the binding of the complex.Omicron-induced BFE changes of the REGN10933-RBD complex are given in Figure 5c. Apparently, K417N and E484A induce BFE changes of −1.08 and −0.86 kcal/mol, respectively. However, most other Omicron mutations may strengthen the binding of the complex.It is interesting to study how the two Regeneron mAbs are affected by Omicron when they are combined. Figure 5d shows the BFE changes of the complex induced by various Omicron mutations. We note that amplitudes of both positive and negative BEF changes have significantly reduced. However, Omicron RBD mutations K417N, G446S, and E484A may still weaken the cocktail binding to the RBD. We predict that Omicron will have a negative impact on the Regeneron cocktail efficacy.
2.3.3. AstraZeneca mAbs
AstraZeneca mAbs are designed as a cocktail of tixagevimab (AZD8895, PDB ID: 7L7D) and cilgavimab (AZD1061 PDB ID: 7L7E) as in Figure 6a. AZD8895 competes with ACE2 for the same binding interface and thus is able to directly neutralize the virus. However, it is also prone to the infection-induced RBD mutations. As shown in Figure 6b, AZD8895 can be slightly weakened by Q493R and K417N. In contrast, AZD1061 can be significantly disrupted by G477N as shown in 6c. Omicron mutation Q493R can also lead to the binding affinty reduction of the RBD and AZD1061 complex. Omicron impacts on the AstraZeneca cocktail are slightly alleviated as shown in 6d. Since mutation Q493R affects both AZD8895 and AZD1061, it may give rise to a significant BFE reduction and disrupt the efficacy of the cocktail.
Celltrion’s antibody CT-P59 (aka Regdanvimab, PDB ID: 7CM4) is used as cocktail with CT-P63, for which we do not have its 3D structure. Figure 7a shows that antibody CT-P59 binds the RBD in a completing region with ACE2 and thus might play a more important role than CT-P63 in combating the virus. Figure 7b shows that mutations E484A, Q493R, and Q498R, respectively, lead to BFE changes of −1.49, −2.82, and −1.0 kcal/mol for the CT-P59-RBD complex. These disruptive effects may be slightly offset by a positive BFE change of 1.71 kcal/mol due to mutation N501Y, which was reported in our earlier work. (11) The impacts of other mutations are relatively mild. Overall, CT-P59 may still be impaired by Omicron. Previously, we have shown that CT-P59 is prone to L452R in Delta and Q439R and S494P. (11) Due to the lack of the CT-P63 structure, we cannot provide an inclusive estimation for Celltrion’s cocktail but would recommend caution toward the use of Celltrion’s Regdanvimab in the wake of Omicron infections.
We also analyze the Rockefeller University antibodies C135 (PDB ID: 7K8Z) and C144 (PDB ID: 7K90), whose binding complexes with the RBD are given in Figure 7c and e, respectively. Antibody C135 has a relatively small region of interface with RBD and does not overlap with ACE2. Our earlier study indicates that C135 is prone to R346K and R346S mutations. (11) Mutation S317L induces a BFE change of −0.63 kcal/mol, indicating a relatively weak negative impact on C135’s efficacy. In contrast, antibody C144 shares part of its binding domain with ACE2 and has more dramatic responses to Omicron mutations (see Figure 7f).
Our earlier study indicates that the efficacy of C144 can be significantly reduced by E484K in the Delta variant. (11) Mutation E484A may cause a BFE change of −1.27 kcal/mol. Therefore, we predict that the efficacy of C144 may be also undermined by Omicron RBD mutations.Finally, we study antibody S309 (PDB ID: 6WPS) which is the parent antibody for Sotrovimab developed by GlaxoSmithKline and Vir Biotechnology, Inc. The alignment of S309 with ACE2 was given an earlier study (28) and is also presented in Figure 7g. Since S309 does not overlap with ACE2 both spatially and on the RBD binding interface, infectivity-induced mutations will not affect S309 very much. Figure 7h shows that Omicron-induced BFE changes are from −0.47 to 0.39 kcal/mol. Therefore, Omicron may have minor impacts on S309.
reference link : https://pubs.acs.org/doi/10.1021/acs.jcim.1c01451