Bahaa Jawad1,2, Puja Adhikari1, Rudolf Podgornik3,4,5,6, Wai-Yim Ching1. 1. Department of Physics and Astronomy, University of Missouri─Kansas City, Kansas City, Missouri 64110, United States. 2. Department of Applied Sciences, University of Technology, Baghdad 10066, Iraq. 3. Wenzhou Institute of the University of Chinese Academy of Sciences, Wenzhou, Zhejiang 325000, China. 4. School of Physical Sciences and Kavli Institute of Theoretical Science, University of Chinese Academy of Sciences, Beijing 100049, China. 5. CAS Key Laboratory of Soft Matter Physics, Institute of Physics, Chinese Academy of Sciences, Beijing 100090, China. 6. Department of Physics, Faculty of Mathematics and Physics, University of Ljubljana, SI-1000 Ljubljana, Slovenia.
Abstract
The emergence of new SARS-CoV-2 Omicron variant of concern (OV) has exacerbated the COVID-19 pandemic because of a large number of mutations in the spike protein, particularly in the receptor-binding domain (RBD), resulting in highly contagious and/or vaccine-resistant strains. Herein, we present a systematic analysis based on detailed molecular dynamics (MD) simulations in order to understand how the OV RBD mutations affect the ACE2 binding. We show that the OV RBD binds to ACE2 more efficiently and tightly predominantly because of strong electrostatic interactions, thereby promoting increased infectivity and transmissibility compared to other strains. Some of the OV RBD mutations are predicted to affect the antibody neutralization either through their role in the S-protein conformational changes, such as S371L, S373P, and S375F, or through changing its surface charge distribution, such as G339D, N440K, T478K, and E484A. Other mutations, such as K417N, G446S, and Y505H, decrease the ACE2 binding, whereas S447N, Q493R, G496S, Q498R, and N501Y tend to increase it.
The emergence of new SARS-CoV-2 Omicron variant of concern (OV) has exacerbated the COVID-19 pandemic because of a large number of mutations in the spike protein, particularly in the receptor-binding domain (RBD), resulting in highly contagious and/or vaccine-resistant strains. Herein, we present a systematic analysis based on detailed molecular dynamics (MD) simulations in order to understand how the OV RBD mutations affect the ACE2 binding. We show that the OV RBD binds to ACE2 more efficiently and tightly predominantly because of strong electrostatic interactions, thereby promoting increased infectivity and transmissibility compared to other strains. Some of the OV RBD mutations are predicted to affect the antibody neutralization either through their role in the S-protein conformational changes, such as S371L, S373P, and S375F, or through changing its surface charge distribution, such as G339D, N440K, T478K, and E484A. Other mutations, such as K417N, G446S, and Y505H, decrease the ACE2 binding, whereas S447N, Q493R, G496S, Q498R, and N501Y tend to increase it.
Since the outbreak of the COVID-19
pandemic, its pathogen SARS-CoV-2 has continuously mutated and evolved,
resulting in the emergence of major variants of concern (VOC). These
VOC have been observed to alter the virus characteristics, such as
infectivity, transmissibility, antigenicity, and pathogenicity.[1] The most recently identified SARS-CoV-2 VOC is
the Omicron variant (OV) (B.1.1.529), which has quickly become the
dominant strain.[2,3] It has the highest number of amino
acid (AA) mutations of any known SARS-CoV-2 VOC, with over 30 mutations
in the spike (S) protein, of which 15 are in the receptor-binding
domain (RBD),[4] the main target for vaccine
and treatment developments.[5−8] The presence of many mutations in OV S-protein has
raised concerns about elevated transmissibility, immunological escape,
and vaccine and treatment failures.[9−15] OV has been identified to contain several key mutations observed
also in other SARS-CoV-2 VOC, such as K417N, E484A, and N501Y, that
change the virus sensitivity to neutralization or increase the infectivity.[16] Moreover, it contains many novel mutations that
have not been observed previously, and their biological effects are
largely unknown. Because the binding between RBD and the angiotensin-converting
enzyme-2 (ACE2) facilitates viral entry, initiating the infection
process, the fundamental understanding of how the OV RBD interacts
with ACE2 is pivotal for understanding the viral infection mechanism
and its evolution, as well as for therapeutic development of effective
means to reduce its spread.The present study aims to investigate
how OV mutations affect the
binding strength between RBD and ACE2 by highlighting the role of
each mutation, its underlying mechanism, and the pertinent binding
driving forces. All-atom molecular dynamics (MD) simulations in explicit
solvent have been implemented in order to study the dynamics and binding
mechanism of the RBD-ACE2 system, followed by the molecular mechanics
(MM) generalized Born surface area (MM-GBSA) method to predict the
binding affinity and the binding profile. The results are compared
with the previously reported analysis of the unmutated, wild type
(WT) RBD-ACE2 system[17] in order to assess
the effect of each mutation and the nature of its interaction based
on the per-residue and pairwise decomposition schemes. MD simulations
have proven valuable to investigate the dynamic and binding processes
of the RBD-ACE2 complex in WT and many previous VOC.[18−25]We implement a procedure, previously developed for both Alpha
and
Beta VOC, to build a computational model of the Omicron RBD-ACE2 system.[17] We briefly summarize it as follows. First, the
interface structure of RBD-ACE2 complex (PBD ID:6M0J) is used as a
template to create the OV RBD-ACE2 system, including all 15 RBD mutations:[26] G339D, S371L, S373P, S375F, K417N, N440K, G446S,
S477N, T478K, E484A, Q493R, G496S, Q498R, N501Y, and Y505H.[4] The last 10 mutations are subsequently exposed
to the ACE2 receptor as shown in Figure .
Figure 1
Omicron RBD-ACE2 interface system. (a) Front
view of unbound Omicron
variant (OV) RBD with all 15 mutations shown in blue and (b) top view.
(c) Bound OV RBD-ACE2 model.
Omicron RBD-ACE2 interface system. (a) Front
view of unbound Omicron
variant (OV) RBD with all 15 mutations shown in blue and (b) top view.
(c) Bound OV RBD-ACE2 model.To substitute the AAs of WT with mutated AAs of OV, we used the
Dunbrack backbone-dependent rotamer library[27] implemented by UCSF Chimera,[28] which
also allows for a careful control of backbone dihedral angles. For
example, the torsion angles of K417N and N501Y mutations from the
available RBD Beta VOC have been used in our OV model,[29] as well as the angles of T478K mutation in the
Delta variant.[30] Second, the resulting
OV RBD-ACE2 complex is solvated with 27000 explicit water molecules
together with the appropriate number of ions (1 Zn2+, 1
Cl–, and 22 Na+) using the TIP3P explicit
water model, implemented in AMBER,[31,32] with the most
recent ff14SB force field used for parametrizations of intermolecular
and intramolecular interactions in the OV complex.[33] Third, the same MD steps of minimization, heating, equilibration,
and two MD production runs were reproduced, but this time the MD runs
were extended over 500 ns (1 μs in total).[17] For each run, 2500 frames are extracted from the entire
simulation and used for the binding free energy (BFE) postprocess
analysis. Finally, the MM-GBSA method[17,34−37] was applied to compute the BFE and to quantify the complete binding
profile,[17] allowing for per-residue and
pairwise BFE decompositions to identify the role and the nature of
interaction for each mutation in the OV model.Figure a shows
the root-mean-square deviation (RMSD) and their frequency distributions
for two replicate MD simulations of the OV. Overall, the complex achieves
stable interfacial interactions as shown by small RMSD fluctuations.
We find that the OV RBD-ACE2 complex has a relatively RMSD smaller
than that previously reported of the WT from 100 ns MD simulations
(average from both runs is 2.32 vs 2.53 Å of WT).[17] The 15 OV RBD mutations thus lead to a more
stable interfacial complex with ACE2. Surprisingly, the inset figure
depicts a higher overlap between two MD runs. Even though the simulation
time is only 500 ns, this is a good sign that our simulations are
reproducible and convergent. This is even more pronounced by the value
of the root mean squared inner product (RMSIP) of 0.82 for the first
two principal components (PC1 and PC2) (Figure S1 in the Supporting Information). This behavior is also evident
from time evolutions and distribution of BFE (Figure S2).
Figure 2
Stability of the OV RBD-ACE2 complex and slight conformation
changes
of mutated residues at RBD core. (a) Time course and distribution
of the root mean square deviation (RMSD) of the heavy atoms of OV
RBD-ACE2 complex in both MD runs. (b) RMSF for 15 residues that are
mutated in OV and compared with WT.
Stability of the OV RBD-ACE2 complex and slight conformation
changes
of mutated residues at RBD core. (a) Time course and distribution
of the root mean square deviation (RMSD) of the heavy atoms of OV
RBD-ACE2 complex in both MD runs. (b) RMSF for 15 residues that are
mutated in OV and compared with WT.In comparison with WT, the OV mutations are seen to only slightly
change the RBD structure. This is even more pronounced when their
root-mean-square fluctuations (RMSFs) are compared, as shown in Figure S3. The average RMSF of mutated RBD in
OV is 1.49 Å vs 1.29 Å of WT RBD, indicating that the OV
RBD is relatively less rigid than WT RBD, thus allowing for larger
fluctuations. Figure b compares the RMSF of only the mutated AAs in OV vs WT. In particular,
D339, L371, P373, and F375 are relatively more flexible than their
WT counterparts. This is consistent with a recent study based on the
cryo-EM S-protein structure, showing that the L371, P373, and F375
significantly alter the conformation and mobility of RBD,[12] thus demonstrating that the computational MD
simulations can confirm and reproduce what is observed experimentally.The MM-GBSA method has been applied to calculate the BFE of the
OV RBD-ACE2 system at 310 K (37 °C), with neutral pH (7.4) and
0.15 M uniunivalent NaCl salt concentration. Table presents the BFE and its decomposition for
OV and in comparison with WT.[17] It shows
that the OV RBD binds ACE2 more strongly than WT, with relative binding
energy of −1.67 kcal/mol, consistent with recent experimental
and computational studies.[11−13,38−40] Interestingly, our predicted BFE value of −14.53
kcal/mol for OV is close to the Alpha BFE value of −14.7 kcal/mol.[17] The complete thermodynamic decomposition listed
in Table shows the
Coulomb electrostatic interaction (ΔEele) of OV to be more than twice that of WT. The increase in ΔEele of OV is mainly the result of five AAs at
the RBM changing from polar to positively charged residues (N440K,
T478K, Q493R, Q498R, and Y505H). The electrostatic component is thus
seen as the main reason behind the more effective binding of ACE2
and OV RBD, which may also elucidate the reason behind the highly
contagious nature of OV (Figure S4). The
electrostatic interaction has been shown to be the primary source
of increasing the binding of SARS-CoV-2 to ACE2 compared to SARS-CoV
as well as enhancing the binding affinity of VOC to ACE2.[23−25] ΔEele of OV, however, creates
a higher desolvation energy (ΔGGB) that is indispensable in the formation process and cannot be avoided
(Table ). On the other
hand, the van der Waals interaction (ΔEvdW) plays a key role in stabilizing and governing the RBD–ACE2
interaction as well as enhancing their binding by gaining −2.71
kcal/mol as compared to WT.
Table 1
Decomposition of
BFE (kcal·mol–1) of RBD-ACE2 Complex in OV
and WT
energy
OV (SEM)
WT (SEM)a
ΔΔGb
ΔEvdW
–92.81 (0.1)
–90.10 (0.1)
–2.71
ΔEele
–1486.5 (0.65)
–700.92 (0.6)
–785.58
ΔEMM
–1579.31 (0.66)
–791.03 (0.7)
–788.28
ΔGGB
1534.19 (0.64)
748.49 (0.6)
785.7
ΔGSA
–13.27 (0.01)
–13.21 (0)
–0.06
ΔGsol
1520.92 (0.64)
735.28 (0.6)
785.64
–TΔS
43.86
42.89
0.97
ΔGbind
–14.53 (0.1)
–12.86 (0.1)
–1.67
All values are taken from ref (17), and SEM is the standard
error of the mean.
ΔΔG = ΔGOV – ΔGWT.
All values are taken from ref (17), and SEM is the standard
error of the mean.ΔΔG = ΔGOV – ΔGWT.To gain a better understanding of the nature and impact of each
mutation on the BFE in RBD-ACE2, in terms of per-residue fractions,
decomposition schemes have been implemented and are shown in Figure S5 for all OV and WT single AAs. Figure a shows the per-residue
BFE decomposition change for the 15 mutations between OV and WT (ΔΔG = ΔGOV – ΔGWT), while their AA–AA interaction pair
maps are displayed in Figures b. These mutations are divided into three groups based on
their influence on binding: neutral, decreased, and increased binding.
Figure 3
BFE decompositions
of RBD-ACE2 complex in OV and WT. (a) Change
in per-residue BFE decomposition (ΔΔG = ΔGOV – ΔGWT). The 15 OV mutations are classified based
on their ACE2 binding properties as neutral, increased, or decreased binding. (b) Pairwise
BFE decomposition for only the mutated OV residues (blue characters
on y-axis) that form pairs with ACE2, compared with
their WT (black). (c) Details of the interactions for the five important
mutations in OV (Q493R, G496S, Q493R, N501Y, and Y505H) and compared
with their WT. The black dashed lines represent possible hydrogen
bonds or salt-bridges, while the red dashed lines represent hydrophobic
interactions.
BFE decompositions
of RBD-ACE2 complex in OV and WT. (a) Change
in per-residue BFE decomposition (ΔΔG = ΔGOV – ΔGWT). The 15 OV mutations are classified based
on their ACE2 binding properties as neutral, increased, or decreased binding. (b) Pairwise
BFE decomposition for only the mutated OV residues (blue characters
on y-axis) that form pairs with ACE2, compared with
their WT (black). (c) Details of the interactions for the five important
mutations in OV (Q493R, G496S, Q493R, N501Y, and Y505H) and compared
with their WT. The black dashed lines represent possible hydrogen
bonds or salt-bridges, while the red dashed lines represent hydrophobic
interactions.Although mutations outside of
RBM and away from the interface,
such as G339D, S371L, S373P, and S375F, do not affect the RBD–ACE2
binding, they may still give rise to other biological consequences.
For instance, substituting neutral G339 with highly negatively charged
D339 changes the surface charge distribution of RBD (Figure ), which may impair the binding
between RBD and antibody. Indeed, a recent study found that this mutation
has a slightly higher escape fraction for Sotrovimab, a human neutralizing
monoclonal antibody (mAb).[41] Aside from
that, changing G339 to D339 results in a longer side chain, which
probably varies the local intramolecular interactions, particularly
with the N343 glycosylation site.[12] We
did not include glycans in our simulation because earlier work suggested
that the RBD of the S-protein had far less glycans than the S-protein
itself and did not interact directly with ACE2.[42] Mutating the polar residue (S) to the hydrophobic residues,
L at 371, P at 373, and F at 375, forms a unique cluster that changes
the biochemical properties of this RBD region in ways not previously
observed in any other strains. This again allows OV to escape from
the class 4 antibodies and some other antibodies from class 1, 2,
and 3.[11,12] Surprisingly, our MD simulations revealed
that S371L, S373P, and S375F mutations are more flexible and induce
a conformational change in RBD, suggesting that they have a higher
chance to evade antibody recognition.
Figure 4
Comparison of electrostatic potential
surface of RBD in mutated
Omicron (top) and WT (bottom). From left to right, the first four
shapes are of the RBD front view, rotated sequentially by 90°,
while the fifth one represents the RBD top view. Important residues
that changed their electrostatic potential surfaces are labeled. Negative-potential
residues are shown in red, near-neutral residues in white, and positive-potential
residues in blue.
Comparison of electrostatic potential
surface of RBD in mutated
Omicron (top) and WT (bottom). From left to right, the first four
shapes are of the RBD front view, rotated sequentially by 90°,
while the fifth one represents the RBD top view. Important residues
that changed their electrostatic potential surfaces are labeled. Negative-potential
residues are shown in red, near-neutral residues in white, and positive-potential
residues in blue.Our findings based on
BFE decompositions show that the E484A, T478K,
and N440K mutations would exhibit the same pattern of neutral binding
(Figure ). Interestingly,
E484K mutation has also been observed in Beta and Gamma VOC and another
variant of interest (VOI), and it has been identified as an immunodominant spike protein residue. Therefore, E484A in
OV is expected to greatly reduce the susceptibility of many mAbs,
which is fully consistent with the recent studies.[11,12] In our MD simulations, we observed that the E484A mutation eliminates
the weak E484:K31 in WT, but it reduces the destabilization that is
stemming from possible electrostatic repulsion between E484 of WT
and E35 of ACE2 when changing to A484. Therefore, this mutation has
no impact on BFE, unlike the E484K mutation in Beta, which increases
the interaction marginally.[17] T478K has
also been seen in the Delta variant and has no direct influence on
the OV RBD-ACE2 interface network.[43] Finally,
the N440K has been linked to an increase in antibody neutralization
resistance for some antibodies.[11,44] Importantly, the exchange
of amino acids at these sites (440, 478, and 484) contributes to the
emergence of a different electrostatic surface of RBD, which may play
some role in attractive electrostatic interactions with the negatively
charged surface of ACE2 (Figure ). In this context, ab initio quantum
methodologies offer a more accurate description of the partial charge
distributions for these charged residues.[17,45−50]Similar to the Beta variant, the K417N mutation reduces the
OV
RBD-ACE2 binding because of the loss of the strong ionic pair with
D30 on ACE2.[17] While this result is consistent
with previous observations,[29,51] we note that the K417N
mutation could affect also the way the RDB clamps the ACE2.[19] Certain mAbs, such as Etesevimab and Casirivimab,
have been shown to be affected by K417N.[52] Similarly, the G446S and Y505H reduce the binding, but we suspect
that this is because of the impact of other mutations like N501Y rather
than the mutations themselves. In our early study, we observed that
the N501Y in the Alpha and Beta VOC significantly enhances the interactions
with ACE2, but it eliminates the hydrogen bond (HB) between the G446
and Q42 of ACE2 and reduces the strength of the Y505:E37 pair (Figure c).[17] The same is true in OV, even though the residues at 446
and 505 site are now S and H, and as a result, their overall contributions
to BFE in OV are smaller than in WT.On the other hand, S477N,
Q493R, G496S, Q498R, and N501Y mutations
confer additional strength to the ACE2 binding, while N477 (OV) forms
new HBs with S19 on ACE2. Interestingly, our findings indicate that
the main source of increased binding is due to the formation of two
new strong salt bridges between R493 and R498 of OV and E35 and D38
on ACE2 with pair interaction strengths of −11 and −6.5
kcal/mol, respectively, which was not observed in the WT (Figure b,c). According to
our findings, the dominant mutations in the OV that enhance electrostatic
interactions to ACE2 are Q493R and Q498R. This finding is in full
agreement with experimental results.[53,54] R493 (OV)
can also form a salt bridge with D38 with pair interaction strength
of −4.5 kcal/mol, but it also makes a weak unfavorable pair
with K353 and loses the pair with K31 that exists in the WT. R498
(OV) retains the pairings with Y41 and Q42, but they are stronger
than Q498 (WT). However, it loses the pair with K353 because of the
N501Y mutation.[17] Unlike G496 of WT, the
aliphatic hydroxyl group of S496 (OV) also forms new HBs with D38
on ACE2 with pair interaction strength of −4.3 kcal/mol and
maintains the HB with K353 (Figure b,c). Just like in Alpha and Beta VOC, Y501 forms more
pairings than N501 of WT (Figure b,c).[17] The number of pairs
between Y501 of OV and ACE2 residues is the same as in Alpha and Beta,
but their interaction strengths change, particularly the Y501:D38
pair (−0.35 of OV vs −4 kcal/mol of Alpha or Beta[17]).In conclusion, comprehensive MD simulations
have been performed
to investigate the effects of OV RBD mutations on ACE2 human cell
receptor binding. Our results shed light on the critical roles of
the new OV mutations in the conformational changes of RBD (S371L,
S373P, and S375F) and changes in its electrostatic potential surface
(N440K, T478K, E484A, Q493R, Q498R, and Y505H). As a result, the overall
electrostatic attraction between the positively charged OV RBD and
the negatively charged ACE2 receptor is twice as strong as in the WT, leading to increased OV contagiousness as well as
to the escape from neutralizing antibodies. Our analysis also shows
that the loss of some interactions caused by K417N, G446S, and Y505H
is completely compensated by the formation of new pairs from S477N,
Q493R, G496S, Q498R, and N501Y, resulting in an overall stronger binding
of OV’s RBD-ACE2.
Authors: Matthew McCallum; Alexandra C Walls; Kaitlin R Sprouse; John E Bowen; Laura E Rosen; Ha V Dang; Anna De Marco; Nicholas Franko; Sasha W Tilles; Jennifer Logue; Marcos C Miranda; Margaret Ahlrichs; Lauren Carter; Gyorgy Snell; Matteo Samuele Pizzuto; Helen Y Chu; Wesley C Van Voorhis; Davide Corti; David Veesler Journal: Science Date: 2021-11-09 Impact factor: 47.728
Authors: Lakshmanane Premkumar; Bruno Segovia-Chumbez; Ramesh Jadi; David R Martinez; Rajendra Raut; Alena Markmann; Caleb Cornaby; Luther Bartelt; Susan Weiss; Yara Park; Caitlin E Edwards; Eric Weimer; Erin M Scherer; Nadine Rouphael; Srilatha Edupuganti; Daniela Weiskopf; Longping V Tse; Yixuan J Hou; David Margolis; Alessandro Sette; Matthew H Collins; John Schmitz; Ralph S Baric; Aravinda M de Silva Journal: Sci Immunol Date: 2020-06-11
Authors: Chang Liu; Helen M Ginn; Wanwisa Dejnirattisai; Piyada Supasa; Beibei Wang; Aekkachai Tuekprakhon; Rungtiwa Nutalai; Daming Zhou; Alexander J Mentzer; Yuguang Zhao; Helen M E Duyvesteyn; César López-Camacho; Jose Slon-Campos; Thomas S Walter; Donal Skelly; Sile Ann Johnson; Thomas G Ritter; Chris Mason; Sue Ann Costa Clemens; Felipe Gomes Naveca; Valdinete Nascimento; Fernanda Nascimento; Cristiano Fernandes da Costa; Paola Cristina Resende; Alex Pauvolid-Correa; Marilda M Siqueira; Christina Dold; Nigel Temperton; Tao Dong; Andrew J Pollard; Julian C Knight; Derrick Crook; Teresa Lambe; Elizabeth Clutterbuck; Sagida Bibi; Amy Flaxman; Mustapha Bittaye; Sandra Belij-Rammerstorfer; Sarah C Gilbert; Tariq Malik; Miles W Carroll; Paul Klenerman; Eleanor Barnes; Susanna J Dunachie; Vicky Baillie; Natali Serafin; Zanele Ditse; Kelly Da Silva; Neil G Paterson; Mark A Williams; David R Hall; Shabir Madhi; Marta C Nunes; Philip Goulder; Elizabeth E Fry; Juthathip Mongkolsapaya; Jingshan Ren; David I Stuart; Gavin R Screaton Journal: Cell Date: 2021-06-17 Impact factor: 41.582