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Received: 3 November 2022
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Revised: 21 December 2022
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Accepted: 27 December 2022
DOI: 10.1002/jcb.30367
RESEARCH ARTICLE
The role of S477N mutation in the molecular behavior of
SARS‐CoV‐2 spike protein: An in‐silico perspective
Mozhgan Mondeali
1
|Ali Etemadi
2
|Khabat Barkhordari
3
|
Mina Mobini Kesheh
4
|Sara Shavandi
5
|Atefeh Bahavar
6
|
Fatemeh Hosseini Tabatabaie
7
|Mohammad Mahmoudi Gomari
8
|
Mohammad H. Modarressi
1
1
Department of Medical Genetics, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
2
Medical Biotechnology Department, School of Advanced Technologies in MedicineSchool of Advanced Technologies in Medicine, Tehran
University of Medical Sciences (TUMS), Tehran, Iran
3
Department of Virology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
4
Department of Virology, School of Medicine, Iran University of Medical Sciences, Tehran, Iran
5
Department of Energy and Environmental Biotechnology, National Institute of Genetic Engineering and Biotechnology, Tehran, Iran
6
Department of Microbiology, School of Medicine, Golestan University of Medical Sciences, Gorgan, Iran
7
Department of virology, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran
8
Department of Medical Biotechnology, Faculty of Allied Medicine, Iran University of Medical Sciences, Tehran, Iran
Correspondence
Mohammad H. Modarressi, Department of
Medical Genetics, School of Medicine,
Tehran University of Medical Sciences,
Tehran, Iran.
Email: modaresi@tums.ac.ir
Abstract
The attachment of SARA‐CoV‐2 happens between ACE2 and the receptor
binding domain (RBD) on the spike protein. Mutations in this domain can
affect the binding affinity of the spike protein for ACE2. S477N, one of the
most common mutations reported in the recent variants, is located in the RBD.
Today's computational approaches in biology, especially during the SARS‐
CoV‐2 pandemic, assist researchers in predicting a protein's behavior in
contact with other proteins in more detail. In this study, we investigated the
interactions of the S477N‐hACE2 in silico to find the impact of this mutation
on its binding affinity for ACE2 and immunity responses using dynamics
simulation, protein–protein docking, and immunoinformatics methods. Our
computational analysis revealed an increased binding affinity of N477 for
ACE2. Four new hydrogen and hydrophobic bonds in the mutant RBD‐ACE2
were formed (with S19 and Q24 of ACE2), which do not exist in the wild type.
Also, the protein spike structure in this mutation was associated with an
increase in stabilization and a decrease in its fluctuations at the atomic level.
N477 mutation can be considered as the cause of increased escape from the
immune system through MHC‐II.
KEYWORDS
molecular docking, molecular dynamics (MD) simulation, molecular interactionss,
SARS‐CoV‐2, S477N mutation
J Cell Biochem. 2023;1–12. wileyonlinelibrary.com/journal/jcb © 2023 Wiley Periodicals LLC.
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1
1|INTRODUCTION
The worldwide outbreak of coronaviruses has been one
of the most challenging medical problems of the 21st
century. Coronavirus disease 2019 (COVID‐19) has been
responsible for about 435 million confirmed cases and 5.9
million deaths in more than 240 countries around the
world since December 2019 caused by the severe acute
respiratory syndrome coronavirus 2 (SARS‐CoV‐2).
1
SARS‐CoV‐2, which is an enveloped virus with positive
single‐stranded RNA (+SSRNA), is a Betacoronavirus
and a member of the family coronaviridae, known as
“crown viruses”due to the structure of their surface
spike (S) proteins.
2
These homotrimeric proteins are
classified under fusion protein type 1, and are divided
into two subunits shortly after binding to the human
Angiotensin‐converting enzyme 2 receptors (hACE2); the
amino‐part is S1 and its carboxyl‐part is S2. The S1
subunit contains an N‐terminal domain (NTD) and a
receptor‐binding domain (RBD), while S2 has the fusion
peptide (FP), heptad repeat 1/2 (HR1/2), transmembrane
domain (TM) and cytoplasm tail (CT). The S1 plays a role
in identifying and binding to hACE2 through the
receptor‐binding motif (RBM) embedded in RBD,
3
and
the S2 is important for fusing the virus particle into the
cell membrane
4
(Figure 1). It is also stated that RBD is
important in the zoonotic transmission of the virus and
in determining cell tropism.
Specific neutralizing antibodies against the S protein
are produced by the human immune system after the
virus enters the cell or after vaccination, and most of
them seem to bind to RBD.
5
Since the outbreak of this
virus, several mutations have negatively affected the
efficiency of both vaccination and treatment methods.
6,7
About 4150 mutations throughout the spike gene have
been reported by 2021, among them 187 substitutions
located in the RBD.
8
This natural selection and positive
fitness caused by the pressure of the host's immune
system probably increase transmissibility.
2,7,9
Various studies conducted to evaluate the effects of
mutations on immune evasion and enhance the binding
of the virus to the hACE2 receptor.
7,9–12
S477N was one
of the highest frequent substitutions submitted in the
Global Initiative on Sharing Avian Influenza Data
database (GISAID) from Iran.
13
In addition, globally,
the S477 position had a high frequency and variety of
mutations in the RBD domain and was detected by
neutralizing antibodies S2E12 and C102.
14,15
The highest
frequency of the substitutions is related to the asparagine
(S477N) that was first reported in the fall of 2020 in
European EU1 and EU2 clusters.
9,16
Also, this substitu-
tion is common in BA.1, B.A.2, B.A3, and B.A4
variants.
17,18
It is noted that S477N mutation can increase
the fatality rate of covid‐19 worldwide
2
and also results in
a very high viral load in combination with D614G.
9
The
S477N mutation is located in the flexible region of the
FIGURE 1 Crystal structure of the spike
protein with three protomers was colored by
domain (PDB ID: 6VSB). Each promoter is
comprised of two subunits, the head (S1),
and the stem (S2). The S1 subunit contains
N‐terminal domain (NTD), receptor‐binding
domain (RBD) embedding receptor‐binding
motif (RBM), and subdomain1/2 (SD1/2, and
the fusion peptide (FP), heptad repeat 1
(HR1), central helix (CH), connector domain
(CD), heptad repeat 2 (HR2), transmembrane
domain (TM), and cytoplasm domain (CT)
form the S2 subunit. Arrows denote protease
cleavage sites.
2
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MONDEALI ET AL.
spike's RBD and may lead to conformational alteration.
19
Also, it was suggested that S477 caused an enhancement
in the binding affinity toward ACE2,
9
which more
studies need to investigate it. Therefore, in this study,
we aimed to study the molecular behavior of S477N
mutation by using structural bioinformatics methods
such as docking, molecular dynamics (MD), territory
structure, and immunoinformatics for understanding of
the atomic‐level influence of this mutation on the spike
protein structure and behavioral changes of the virus in
complex to its human receptor (hACE2).
2|MATERIALS AND METHODS
2.1 |Preparation of structures
The three‐dimensional structure of the SARS‐CoV‐2 RBD
bound to hACE2 (PDB ID:6M0J) and S477N mutant
(PDB ID:7EJZ) were retrieved from the RCSB (https://
www.rcsb.org). These structures were prepared and
relaxed with the Rosetta software suite.
20,21
The protein
preparation steps included removing water, ligand, and
other complexed molecules, assigning proper bond
orders, correcting disoriented groups, adding hydrogen
atoms, and implementing relaxation and repack process
for backbone and sidechains clashes fixation.
2.2 |Docking and interaction analysis
The docking process was applied to consider the effect of
the S477N mutation on the ability of spike to bind to the
hACE2 receptor. Two Servers, Haddock 2.4
22
and cluspro
2.0,
23
and also the Rosetta program were used to attain
the docking complexes. Through the docking, the
solvated docking mode was activated, active residues
were considered as the fully‐flexible segment and passive
residues were chosen automatically. The cluster with the
best conformation and highest score obtained in this step
was employed in other analysis steps. The 3D interac-
tions were created using the PyMOL v2.4.1,
24
while the
2D interactions were created using LigPlot+ 4.5.3
25
and
PDBsum.
26
2.3 |Molecular dynamics (MD)
simulation
MD simulation was accomplished with GROMACS
v2021 (CUDA compiled) on Linux operating system
(Ubuntu v20.04 LTS)
27
to study the behavior of
hACE2‐S477N complex over time and the effect of this
displacement on the structural properties of the spike
using Newtonian equations. Pressure, temperature,
and neutralizing conditions for the equilibrium of
systems were checked before starting the MD analysis.
Three trajectories were analyzed for 50 ns, 2 fs per step.
The boundary box to protein distance was considered
as a minimum of 1 nm as the simulation box. During
the analysis, desired structures were parameterized
with an AMBER99SB‐ILDN force field. The simulated
protein complexes were placed in a triclinic box and
the TIP3P water molecule model was used to solvate
the system. To neutralize the net charge of systems, Na
+andCl‐ions were added. All the MD simulations
were carried out considering periodic boundary condi-
tions. The systems were energy minimized for 10 000
steps using the steepest descent algorithm. The
temperature was set at 310 K and employed the
velocity‐rescaling thermostat during the simulation.
Afterward, the pressure was equilibrated at 1 bar using
the Berendsen barostat. In the MD production step, all
systems were simulated for 50 ns. Structural parame-
ters such as root‐mean‐square deviation (RMSD), root‐
mean‐square fluctuation (RMSF), solvent accessible
surface area (SASA), the radius of gyration (Rg),
secondary structure, hydrogen bonds, minimum dis-
tance, and the number of contacts were obtained from
the output trajectory files.
2.4 |Stability investigation
To determine the effect of mutation on the stability of
native and mutant spikes in unbounded mode, FoldX
(version 5) plugin
28
for YASARA and ExPASy‐
ProtParam
29
were used for the structures obtained from
the last frame of the simulation. FoldX estimates the
energy of the structure by using physics and statistics‐
based energy terms algorithms. The empirical force field
algorithm as the main function of FoldX is based on free
energy (ΔG) terms calculating the change of ΔGin
kcal mol−.
28
2.5 |Tertiary structure topology
analysis
The impact of the S477N displacement on the folding
of spike protein was studied by structural alignment
andtunnelanalysisaroundthemutatedposition.
Structural alignment and tunnel analysis were per-
formed using PyMOL v2.4.1
24
and CAVER Web v1.0,
30
respectively. The mutation position was selected as the
starting point.
MONDEALI ET AL.
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3
2.6 |Immunogenicity analysis
The sequences of native and S477N spike variants were
derived from the UniProt database.
31
Subsequently, the
Immune Epitope Database (IEDB) was used to evaluate
and compare the immunogenicity and physicochemical
properties of the wild‐type and mutant spike. Antigen
Sequence Properties (Bepipred Linear Epitope Prediction
2.0) and DiscoTope tools were used for predicting Linear
and discontinuous B‐cells epitopes, respectively. Further-
more, T‐cell epitope prediction established by IEDB
recommended 2.22 (MHC‐I) and NetMHCPan 4.1 EL
(MHC‐II) methods.
32
3|RESULTS
3.1 |Molecular docking and
interactions
Molecular docking is an important strategy that predicts
the preferable orientation, affinity, and interaction
between a ligand and binding site of a protein.
33
For
protein–protein docking and molecular interactions,
three software were applied including Rosetta, Haddock,
and Cluspro. In comparison to the wild type, the free
energy for the mutant was stronger (Table 1), resulting in
a higher binding affinity of N477‐ACE2. Our binding
pattern displayed two newly formed hydrogen and
hydrophobic bonds in the mutant RBD‐ACE2, which
did not exist in the wild type (Table 2). Indeed, Asn477
formed two hydrogen bonds with Ser19
ACE2
with bond
distances of 3.22Å and 2.73Å and two hydrophobic bonds
with Gln24
ACE2
and Ser19
ACE2
with bond distances of
3.81Å and 3.74, respectively, whereas S477 had none of
these interactions (Table 2). Furthermore, the connection
of Asn477 with serine and glutamine residues led
to a reduction of hydrogen bond distance of
Ala475
RBD
‐Ser19
ACE2
, as the length of this bond changed
from 2.84Å in the wild type to 2.61Å in the mutant. On
the other hand, binding affinity free energy of N477
RBD‐ACE2 in Omicron variants exhibited a higher increase
compared to both the wild type and Delta variants,
34
which
confirms our finding that the bond between N477 and
ACE2 is stronger than the wild type (Figure 2).
3.2 |MD simulation analysis
MD simulation is a potent approach for investigating the
biomolecular structure, interactions, the dynamics of
biological systems in‐silico.
35,36
To complete the results
derived from molecular docking, we performed an MD
simulation. Compared to molecular docking, the main
advantage of MD simulation is that it not only investi-
gates proteins' interactions at the atomic level but also
provides a physiological condition that is close to the
cellular mode.
37
Before initiating the MD investigation, it
is necessary to define some structural parameters,
including pressure, temperature, and neutralizing condi-
tions for the equilibrium of systems. To ensure that the
MD time was sufficient, RMSD curves were drawn for
the target systems. During the simulation, these struc-
tural parameters reached equilibrium. The RMSD profile
with an average of 0.210 nm for the native and 0.169 nm
for the mutated protein indicated that the mutated
structure was more stable than the native one
(Figure 3A). Also, RMSF was calculated to identify a
single residue fluctuation during a simulation. Figure 3B
depicts the RMSF in the native and mutant structures
with averages of 0.105 and 0.101 nm, respectively.
Compared to S477, the N477 residue illustrated a slight
reduction in structural fluctuations. In other words, in
the N477 mutation, the asparagine residue had a larger
structure than the serine in S477, which could provide
more space and also more capacity to interact with
peripheral residues on the spike. As a result, this
TABLE 1 Docking servers' energies (KJ/mol) for wild type and
mutant variants
RBD Rosetta Haddock Cluspro
S477 −53.16 −78.8 −748.2
N477 −53.94 −83.2 −759.1
Abbreviation: RBD, receptor‐binding domain.
TABLE 2 The hydrogen bonds at the interaction of N477 and ACE2
ACE2 RBD
M
Length (Å) RBD
WT
Length (Å)
Hydrogen bond S19 (N) N477 (OD1) 2.73 ‐‐
S19 (O) N477 (ND2) 3.22 ‐‐
Hydrophobic bond S19 (CA) N477 (OD1) 3.74 ‐‐
Q24 (CG) N477 (CG) 3.81 ‐‐
Abbreviations: M, mutant; N, asparagine; Q, glutamine; RBD, receptor‐binding domain; S, serine; WT, wild type.
4
|
MONDEALI ET AL.
mutation leads to a reduction in the residual movements
and therefore an increase in the rigidity and stability of
the mutant protein, which is consistent with the results
of other MD simulations.
We used the Rg factor to measure the protein
compactness. The Rg of a protein is the distribution of
atoms around the center of that protein.
38
As shown in
Figure 4A, the average Rg values for the native and mutant
were 2.307 and 2.308 nm, respectively. An increase of about
0.001nminN477confirmsaslightreductioninthe
compactness of the mutant, which can lead to more
interactions in the mutated proteins. To measure the level
of protein folding, we estimated SASA, which shows how
much the surface area of a protein accesses a solvent.
39
Our
result exhibited an increased value of SASA for the mutant
RBD with 105.88 nm compared to the native with
105.39 nm (Figure 4B). This means that the substitution
of serine to asparagine at position 477, leads to a stronger
interaction between RBD and ACE2 complex. RBD mutant
has a higher interaction power than the native form in
substituting serine to asparagine residue at position 477.
Hydrogen bonds have a significant effect on the
formation of secondary and tertiary structures of a
protein and even in protein folding. Also, the kinetics
of hydrogen bonds between proteins, in particular among
receptors and ligands, determines the interactions
between biomacromolecules.
40
Therefore, we calculated
the number of hydrogen bonds, number of contacts, and
mean distance between ACE2 and RBD complex at the
atomic level through MD simulation. The mean, mini-
mum, and maximum H‐bond were 10.3, 3, and 16 in
N477, and 8.4, 0, and 14 in S477, sequentially
FIGURE 2 Docked complexes of the Spike RBD (cyan) with hACE2 receptor (green) are shown in a cartoon view. (A) Binding interface
of the complexes (B) Representation of interface interactions using pdbsum server, (C) 2D diagram of interactions using Ligplot+ software
in which the H‐bond and hydrophobic interactions are shown with green and red dots, respectively. The two red arrows indicate newly
formed interactions between N477 mutation and ACE2 residues. (D) 3D visualizations of H bond interactions between N477 and A475 with
ACE2 amino acids. Asn477 forms two hydrogen bonds with Ser19
ACE2
with bond distances of 3.22Å and 2.73Å, whereas S477 has none of
these interactions. Also, the hydrogen bond length of Ala475
RBD
‐Ser19
ACE2
reduce from 2.84Å, in the wild type, to 2.61Å, in the mutant.
MONDEALI ET AL.
|
5
(Figure 5A). These results revealed significant differences
in the average of hydrogen bonds between the N477‐
ACE2 complex and S477‐ACE2, which represented an
increase in the potency of interaction in the mutant
complex. Furthermore, the mean, minimum, and maxi-
mum number of contacts in the S477‐ACE2 were 240.3,
212.0, and 267.0, while the same values increased in the
mutant with 245.7, 205.0, and 276.0, respectively, which
displayed robust interaction in the N477‐ACE2 complex
compared to the native (Figure 5B). The mean distance
for N477 (0.222) was shorter than that of S477 (0.314)
(Figure 5C), which shows an enhancement in the power
of links in the mutated complex and a higher binding
affinity for its receptor. Every change that leads to the
loss or formation of hydrogen bonds influences the basic
elements of the secondary structure, including turns,
bends, coils, and so forth.
41
The evaluation of secondary
structure elements in N47 showed a decrease in the
number of coils and an increase in the number of bends
which can influence the elements of secondary structure
in the surrounding residues; for example, the number of
coils at position 474 reduced (Figure 6).
3.3 |Stability, structural alignment, and
caver analysis
The impact of the N477 mutation on the stability of the
protein was investigated using FoldX, and ProtParam tools,
available at Expasy. The examination of FoldX and instability
index suggests that S477N mutation increases the stability of
the spike (Table 3). The structural alignment analysis
showed a small structural shift (4.37A°) in the structure of
the mutant, compared with that of the native protein,
showing that the mutation of S477N can affect the binding
affinity of the spike for its receptor, ACE2 (Figure 7).
FIGURE 3 Root‐mean‐square deviation
(RMSD) (A) and root‐mean‐square
fluctuations (RMSF) curves (B) during
50 000 ps MD simulations for RBD‐ACE2
complexes. N477 mutation is shown in red
and S477 in black. As can be seen, after 15 ns,
the RMSD value reached a steady state,
showing that the simulation time is sufficient
for systems equilibration. The RMSF for
amino acids at positions 474 to 480 is shown
in details in a gray square. The obtained
amount of RMSF for the mutated residue
was less than wild, which demonstrates the
reduction of structural fluctuations and the
increase in stability of the mutant structure.
6
|
MONDEALI ET AL.
Tunnel analysis reveals that although the mutation of
serine to asparagine at position 477 does not change the
bottleneck radius and curvature of the tunnel (1.2 and
1.1A°), it shortens the length of the tunnel available around
Asp477 (2.5) compared to Ser477 (3.5). This could be due to
the amide group in Asp477 (CH2‐CO‐NH) that is bigger
than the hydroxyl group (CH2‐OH) in Ser477 (Figure 8)
and has a larger capacity to interact with molecules around
compared to Ser477, as Asp477 makes two hydrogen and
two hydrophobic bonds with S19 and Q24 (Table 2).
3.4 |Immunogenicity analysis
The SARS‐CoV‐2 spike, as a trimeric protein, comprises
two subunits: head (S1) and stalk (S2), and RBD in the S1
subunit interacts with hACE2 to trigger the host cell
penetration.
3
There is a receptor binding motif (RBM) at
positions 438 to 506 of the RBD region that directly
interacts with ACE2.
4
Changes in the RBD play a
significant role in immunity provocation and pathoge-
nicity, for example, N501Y mutation enhances the
affinity of the RBD for ACE2 and reduces the spike's
immunogenicity.
42
To obtain an overview of the neutral-
ization status of T and B cells for mutant compared to
wild type, MCH‐I/II and linear/discontinuous epitopes
were predicted (Table 4). In terms of B cells, no
difference was observed between mutant and wild types.
In other words, the binding affinity of B cells for the
mutant is like the wild type. In terms of T cells, the
binding ability for MCH‐I in the N477 mutation was as
same as the S477, while a stronger affinity for MHC‐II
was observed in the N477 mutation. Despite the fact that
only three mutations occurred in Delta variants RBM, ten
FIGURE 4 The radius gyration (Rg) (A)
and the solvent accessible surface area
(SASA) (B) plots over 50 000 ps MD
simulations of the mutant (red) and naive
(black). The average RG and SASA for the
native Spike were 2.307 nm and 105.39 nm
2
,
respectively. While those of the mutant Spike
were 2.308 nm and 105.88 nm
2
. The greater
amount of RG and SASA for the mutant
protein compared to the native Spike
indicates a decrease in the compaction of
protein following mutation.
MONDEALI ET AL.
|
7
mutations embedded in Omicron RBM that monoclonal
antibodies directly interact with.
34
Although our analysis
illustrated no significant binding affinity for B cells, N477
mutation along with other changes in Omicron RBM can
increase the risk of immune evasion.
34,43
4|DISCUSSION
In line with our findings of molecular dynamics, the MD
simulation analysis in the S477N mutation confirmed the
increased power of binding affinity of the spike to the
hACE2 receptor in SARS‐CoV‐2. Based on the RMSD and
RMSF, the results showed more stability in the mutant
form than the native one as the reduction in fluctuations
and the residual movements in the N477 compared to the
S477, respectively. The other parameters, like the average
Rg values with a little increase, were associated with a low
decrease in the compactness of the N477 that can cause
more interactions in the mutated form. Moreover, we
estimated SASA as the level of protein folding, which had
an augment in the mutant RBD, and it can lead to
stronger interaction among RBD and ACE2 in mutant
form. The increase in the number of hydrogen bonds and
FIGURE 5 Hydrogen bonds state (A),
number of contacts (B), and the minimum
distance (C) for interface residues of RBD‐
ACE2 complex in both native (black) and
mutant (red) forms. MD analysis revealed a
significant increase in the average number of
hydrogen bonds and contacts in the mutant
complex (10, 245) compared to the wild type
(8, 240). The mean distance between Asn at
position 477 with interface residues of ACE2
(0.222 nm) was less than the native
(0.314 nm). These results could be evidence
for greater ability of mutant RBD to bind the
ACE2 cell surface receptor.
8
|
MONDEALI ET AL.
the enhancement in the number of contacts, along with
the reduction in the mean distance in the mutant
complex, help to make a stronger interaction and also
reinforce the potency of links and, finally, a higher
binding affinity in the mutant RBD with ACE2 complex.
N477 substitution induced conformational changes greater
than S477. Both asparagine and serine are polar and
neutral amino acids. The amide group in the side chain of
Asn is capable to accept two and also donate two
hydrogen bonds, resulting in a high propensity and
tendency for hydrogen bonds
44
; while serine possesses a
hydroxyl group in its side chain which often forms
hydrogen bonds with the atoms in the main chain.
Generally, serine is defined as a little polar amino acid,
though it is relatively neutral in connection with
mutations. It commonly substitutes with other polar or
small residues, especially threonine. Serine can be located
both in the inner or on the surface of the proteins.
45
Previous studies have shown that S447N alters the
hydrogen‐binding network and functional changes of the
ACE2 receptor.
46,47
Jawad et al.
46
illustrated the 477N
mutant forms new hydrogen bonds with S19 on ACE2 in
the Omicron variant. In another study, a 2.5‐fold increase
in the binding affinity between Omicron RBD and ACE2
was also reported, which was due to S477N, G496S,
Q498R, N501Y, K417N, Y505H, and Q493K mutations.
47
Also, our findings were consistent with the study of Singh
et al., which showed two common mutations like S477G
and S477N at the RBD are associated with the power of
binding with the hACE2 receptor.
9
Also, Ser‐to‐Asn
substitution reported in other viral proteins, for example,
S139N in Zika virus prM protein led to the increase of
microcephaly in the mouse fetus and viral replication in
human and mouse neural cells. It was suggested this
mutation contributed to the maturity of virions following
the viral fitness for neurovirulence.
48
Siboonnan et al.
49
demonstrated the mutation at S314N in nucleoprotein
FIGURE 6 The secondary structure of
the mutant spike (A) and native.
(B) Following S477N displacement, the
number of coils were decreased, while the
bends elements had increased.
TABLE 3 Stability assessment of spike in native and mutant
forms in terms of FoldX and ii
Lineage Tools foldX (KJ/mol) Expacy (ii)
a
Native 78.19 22.69
Mutant 76.81 21.93
a
Instability index.
FIGURE 7 Structural alignment of native (cyan) and mutant
(red) spike. A structural shift (4.37A°) was observed in the
structure of the mutant spike compared to the native structure
which can affect the binding affinity of the spike for ACE2.
MONDEALI ET AL.
|
9
(NP) of the H5N1 avian influenza virus caused interfer-
ence in the nuclear aggregation of NP at a nonpermissive
temperature in a temperature‐sensitive (ts) mutant
phenotype. Moreover, Yamaguchi et al.
50
illustrated
S123N substitution in the E protein of the Japanese
encephalitis virus (JEV), along with a low difference in
neuroinvasiveness between the parent and recombinant
JEV strains. And also, their finding depicted S123N
mutation has a low impact on viral growth features in
vitro or on pathogenicity in vivo. These reports suggest
that serine‐to‐asparagine mutation had often been associ-
ated with major effects on protein function.
Given the role of this mutation in increasing spike
stability and interaction with ACE2, which in turn
facilitates virus entry into the cell, more attention should
be paid to the identification of SARS‐CoV‐2 lineage bearing
S477N. These findings could be necessary for the design of
efficient diagnostic protocols, protein–protein interaction
inhibitor molecules, therapeutic antibodies, and vaccines.
5|CONCLUSION
Among several mutations that have been identified to occur
in RBD, the S477N substitution is known as one of the
signature mutations in the Omicron variant. Therefore,
searching the impact of mutations on the structure and
function of the spike can lead to better immunization
programs as well as more specific treatments. In this study,
numerous computational approaches were adopted to
investigate the influence of S477N mutation at the atomic
level and monitor the behavioral changes of the virus about
hACE2 and the immune system. We discovered that the
mutation of S477 to N477 can strengthen the bond between
RBD and hACE2. Although no difference was observed
between the mutant and wild type in terms of B cell and
TCD8
+
immunity, there was a higher affinity for MHC‐II in
N477. MD simulation along with structural analyses
revealed that S477N mutation can stabilize the structure
of spike protein and lessen its fluctuation.
AUTHOR CONTRIBUTIONS
Khabat Barkhordari conceptualized and Mohammad
Hossein Modarressi supervised the study. The server
was provided by Ali Etemadi. The formal analysis was
done by Mina Mobini Kesheh, Sara Shavandi, Atefeh
Bahavar, and Mozhgan Mondeali. The original drat was
written by Mina Mobini Kesheh, Sara Shavandi, Atefeh
Bahavar, Fatemeh Hosseini Tabatabaie, Mohammad
Mahmoudi Gomari, and Mozhgan Mondeali. The final
manuscript was edited by Ali Etemadi, Mozhgan
Mondeali, and Sara Shavandi. All all authors approved
the final version.
ACKNOWLEDGEMENT
The authors express great appreciation to the Tehran
University of Medical Sciences for their assistance.
CONFLICT OF INTEREST
The authors declare no conflict of interest.
DATA AVAILABILITY STATEMENT
Data sharing is not applicable to this article as no new
data were created or analyzed in this study.
ORCID
Mina Mobini Kesheh https://orcid.org/0000-0003-
0529-9163
Mohammad Mahmoudi Gomari https://orcid.org/
0000-0003-4143-2208
Mohammad H. Modarressi https://orcid.org/0000-
0003-2763-1964
FIGURE 8 Representation of tunnel
analysis outputs for desired structures, native
(A) and mutant (B). The tunnel results
showed the mutation of serine to asparagine
at position 477 shortens the length of the
tunnel from around 3.5Å to 2.5Å.
TABLE 4 MCH‐I/II and linear/discontinuous epitopes
prediction for the mutant and wild type
Sequence MHC‐I MHC‐II ASP Discotope score
S477 0.00 71.90 0.51 −6.067
N477 0.00 76.60 0.51 −6.008
Note: Higher score exhibits higher binding affinity.
Abbreviations: ASP, antigen sequence properties; MHC, histocompatibility
complex Class.
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How to cite this article: Mondeali M, Etemadi A,
Barkhordari K, et al. The role of S477N mutation in
the molecular behavior of SARS‐CoV‐2 spike
protein: an in‐silico perspective. J Cell Biochem.
2023;1‐12. doi:10.1002/jcb.30367
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