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. 2023 Jan 16;181:107704. doi: 10.1016/j.ympev.2023.107704

Bioinformatic analysis of the S protein of human respiratory coronavirus

Zheng Niu a,b,1, ShaSha Xu a,1, JingYi Zhang a,1, ZhuoLan Zou a,c, LiXin Ren a, XiangYang Liu a,d, ShuJuan Zhang a, Hong Zou a, Xia Hu a, Jing Wang a, Li Zhang a, Yang Zhou a,d, ZhenHui Song a,c,⁎
PMCID: PMC9840983  PMID: 36657625

Graphical abstract

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Keywords: Bioinformatic, Human respiratory coronavirus, S protein

Abstract

The present study aimed to apply bioinformatic methods to analyze the structure of the S protein of human respiratory coronaviruses, including severe respiratory disease syndrome coronavirus (SARS-CoV), Middle East respiratory syndrome coronavirus (MERS-CoV), human coronavirus HKU1 (HCoV-HKU1), and severe respiratory disease syndrome coronavirus type 2 (SARS-CoV-2). We predicted and analyzed the physicochemical properties, hydrophilicity and hydrophobicity, transmembrane regions, signal peptides, phosphorylation and glycosylation sites, epitopes, functional domains, and motifs of the S proteins of human respiratory coronaviruses. All four S proteins contain a transmembrane region, which enables them to bind to host cell surface receptors. All four S proteins contain a signal peptide, phosphorylation sites, glycosylation sites, and epitopes. The predicted phosphorylation sites might mediate S protein activation, the glycosylation sites might affect the cellular orientation of the virus, and the predicted epitopes might have implications for the design of antiviral inhibitors. The S proteins of all four viruses have two structural domains, S1 (C-terminal and N-terminal domains) and S2 (homology region 1 and 2). Our bioinformatic analysis of the structural and functional domains of human respiratory coronavirus S proteins provides a basis for future research to develop broad-spectrum antiviral drugs, vaccines, and antibodies.

1. Introduction

Since 2019, severe respiratory disease syndrome coronavirus type 2 (SARS-CoV-2) has rapidly spread throughout the world, causing a pandemic of coronavirus disease 2019 (COVID-19) since its emergence in Wuhan, China (Ahmad et al., 2022, Wang et al., 2020). As of September 24, 2022, SARS-CoV-2 has caused more than 600 million infections and more than 6.5 million deaths worldwide, and this number continues to grow.

In addition to SARS-CoV-2, other coronaviruses that can cause human respiratory diseases include severe respiratory disease syndrome coronavirus (SARS-CoV), Middle East respiratory syndrome coronavirus (MERS-CoV), and human coronavirus HKU1 (HCoV-HKU1). Among them, SARS-CoV causes severe respiratory disease syndrome (SARS), which has resulted in more than 8,000 infections worldwide since its discovery in southern China at the end of 2002; however, worldwide efforts prevented it from triggering a larger outbreak (Hon et al., 2008). Ten years later, MERS-CoV, which causes Middle East Respiratory Syndrome (MERS), was detected in Saudi Arabia and global transmission occurred in 2015. By 2019, more than 2,000 people had been infected with MERS-CoV, which causes a severe respiratory illness (Kato et al., 2019). By contrast, HCoV-HKU1, which was discovered in Hong Kong in 2005, generally only causes patients to develop self-limiting syndromes such as common cold-like symptoms, bronchitis, and pneumonia, and has not caused serious damage to human health(Zhao et al., 2008, p. 1).

Coronaviruses belong to the order Nidovirales, Coronaviridae, and are classified into α, β, γ, and δ coronaviruses according to their genome sequences. SARS-CoV, MERS-CoV, HCoV HKU1, and SARS-CoV-2 all belong to the β genus (Agarwal et al., 2022, Hembram, 2021, Zaki et al., 2012, Zhong et al., 2003). Coronaviruses contain four structural proteins: The nucleocapsid protein (N), spike protein (S), envelope protein (E), and membrane protein (M) (Bosch et al., 2003). Among them, the S protein plays an important role in the process of viral invasion and infection of cells.

A trimer of S proteins located on the surface of the viral envelope is the basic unit of viral receptor binding (Wu et al., 2020). S proteins can be functionally divided into S1 and S2 regions (Lu et al., 2020, Zhou et al., 2020). S1 contains the Receptor Binding Domain (RBD), which is mainly responsible for viral-receptor binding, while S2 contains homology region (HR) structural domains (HR1 and HR2), which are closely related to viral fusion. The replication of coronaviruses begins with the cellular attachment of the virus through the interaction between the S protein and its receptor (Huang et al., 2020, Walls et al., 2020, Wrapp et al., 2020). After attachment to the receptor, the virus enters the cell by cleavage of the S protein (S1 is cleaved from S2) by host cell proteases, such as transmembrane serine protease 2 (TMPRSS2) (Glowacka et al., 2011, Matsuyama et al., 2010, Shulla et al., 2011). This process is followed by fusion of the virus and host cell membranes (Yuan et al., n.d.). The next step is the translation of the replicase from the virion genomic RNA, and the translation and assembly of the viral replicase complex (Gorbalenya et al., 2006, V’Kovski et al., 2020). Both SARS and SARS-CoV-2 enter the host cell by binding to angiotensin converting enzyme 2 (ACE2) on the host cell membrane (Han et al., 2022, Wu et al., 2009). The receptor for MERS-CoV entry into the host cell is dipeptidyl peptidase-4 (DPP4). However, the mechanism of host invasion by HCoV HKU1 is not yet clear (Raj et al., 2013, Yang et al., 2014). The mechanism of binding between the coronavirus S protein and its receptor has been studied in depth and has led to the development of several therapeutic or blocking drugs (Lan et al., 2022, Totura and Bavari, 2019).

In this study, the biological functions of the S proteins of the four human respiratory coronaviruses were analyzed and compared using bioinformatic software. The bioinformatic software was used to analyze their physicochemical properties, transmembrane regions, signal peptides, functional domains, protein modifications, and antigenic epitopes. These analyses will facilitate our understanding of the human respiratory coronavirus S protein. Moreover, analysis of the biological functions of S proteins will promote the study of the biological properties of human respiratory coronavirus and provide data for S protein modification, vaccine preparation, and the design of antiviral drug molecules. In addition, the results of these analyses could from the basis for more in-depth studies of S proteins in the future.

2. Materials and methods

2.1. Virus information

The S-gene nucleotide and amino acid sequences of SARS ShanghaiQXC2 (GenBank ID: AY463060), MERS nasal swab (GenBank ID: MK564474), HCoV-HKU1 SI17244 (GenBank ID: MH940245), and SARS-CoV-2 Wuhan-Hu-1 (GenBank ID: NC_045512) were downloaded from the National Center for Biotechnology Information (NCBI) (Table 1 ).

Table 1.

The information of S gene sequences of the four coronaviruses.

Strain name Genome source Genome accession Position in genome Protein accession PDB ID
SARS ShanghaiQXC2 AY463060 20834–24601 AAR86775 ——
MERS nasal swab MK564474 21443–25504 QBM11737 ——
HCoV-HKU1 SI17244 MH940245 22858–26913 AYN64561 ——
SARS-CoV-2 Wuhan-Hu-1 NC_045512 21563–25384 YP_009724390 7CWL
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2.2. Bioinformatics software

The physical and general biological characteristics of the human respiratory coronavirus S proteins were calculated using the ProtParam and ProtScale tools on the ExPASy Server. The transmembrane regions (Transmembrane Helix (TMH)), signal peptides, phosphorylation sites, and glycosylation sites of S protein, were predicted using TMHMM Server v.2.0, SignalP4.1, NetPhos 3.1 Server, NetNGlyc 1.0 and NetOGlyc 4.0 Server software, respectively. Meanwhile, the amino acid sequences of human respiratory coronavirus S proteins were subjected to Predicting Antigenic Peptides, SMART, and PROSITE analyses to predict antigenic epitopes, functional domains, and functional patterns of each S protein sequence. Their three-dimensional (3D) conformations were predicted using phyre2, and S protein surface potential and hydrophobicity were demonstrated by ChimeraX. The links to the bioinformatics analysis software used in this paper can be found in Table 2 .

Table 2.

Bioinformatics software-related information.

Name of software URL Function
ProtParam https://web.expasy.org/protparam/ Analysis of the physical and chemical properties of protein
ExPASy-ProtScale https://web.expasy.org/protscale/ Analysis of protein affinity and hydrophobicity
TMHMM Server v.2.0 https://www.cbs.dtu.dk/services/TMHMM/ Transmembrane analysis of proteins
SignalP4.1 https://services.healthtech.dtu.dk/service.php?SignalP-4.1 Predictive signal peptide
NetPhos 3.1 Server https://www.cbs.dtu.dk/services/NetPhos/ Prediction of phosphorylation site
NetNGlyc1.0 Serve https://www.cbs.dtu.dk/services/NetNGlyc/ Prediction of N-type glycosylation sites
NetOGlyc4.0 Server https://services.healthtech.dtu.dk/service.php?NetOGlyc-4.0 Prediction of O-type glycosylation sites
Predicting Antigenic Peptides https://imed.med.ucm.es/Tools/antigenic.pl Prediction of protein epitopes
PROSITE https://prosite.expasy.org/ Prediction of functional motif
SMART https://smart.embl-heidelberg.de/ Protein domain analysis tool
phyre2 https://www.sbg.bio.ic.ac.uk/phyre2/html/page.cgi?id=index Protein 3D structure modeling
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3. Results

3.1. Physical and chemical properties

The amino acid sequences of human respiratory coronavirus S proteins were uploaded to ProtParam online software. The ProtParam analysis showed that the SARS ShanghaiQXC2 S protein comprises 1255 amino acids, with a molecular weight and isoelectric point of 139006.07 and 5.67, respectively. The protein contains 113 negatively charged residues and 99 positively charged residues. The instability index of SARS ShanghaiQXC2 S protein is 31.91, the lipid index is 82.88, and the hydration grand mean is 0.038.

The MERS nasal swab S protein consists of 1358 amino acids, with a molecular weight and isoelectric point of 149559.3 and 5.61, respectively. The protein contains 112 negatively charged residues and 94 positively charged residues. The instability index of the MERS nasal swab S protein is 36.92, the lipid index is 82.85, and the grand mean of hydration is 0.068.

The HCoV-HKU1 SI17244 S protein contains 1351 amino acids and has a molecular weight and isoelectric point of 150,800 and 6.06, respectively. The protein contains 103 negatively charged residues and 92 positively charged residues. The instability index of HCoV-HKU1 SI17244 S protein is 40.33, the lipid index is 84.77, and the grand mean of hydration is 0.022.

The SARS-CoV-2 Wuhan-Hu-1 S protein comprises 1273 amino acids with a molecular weight and isoelectric point of 141178.47 and 6.24, respectively. The protein contains 110 negatively charged residues and 103 charged residues. The instability index and lipid index of the SARS-CoV-2 Wuhan-Hu-1 S protein is 33.01 and 84.67, respectively, and the grand mean of the hydration is 0.079.

The ProtParam system automatically generated a list of physical and chemical properties of the four proteins, the results of which are shown in Table 3 .

Table 3.

Physical and chemical properties of human respiratory coronavirus spike proteins.

Characteristic SARS-S protein MERS-S protein HCoV-HKU1-S protein SARS-CoV-2-S protein
Number of amino acids 1255 1358 1351 1273
Formula C6248H9588N1610
O1866S5 		C6700H10258N1730
O2031S63 		C6788H10327N1737
O2020S69 		C6336H9770N1656
O1894S54
Molecular weight 139006.07 149559.3 150800.23 141178.47
Theoretical isoelectric point (PI) 5.67 5.61 6.06 6.24
Number of negatively charged residues 113 112 103 110
Number of positively charged residues 99 94 92 103
Instability index (II) 31.91 36.92 40.33 33.01
Aliphatic index 82.88 82.85 87.71 84.67
Grand average of hydropathicity −0.038 −0.068 0.022 −0.079
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3.2. Hydrophilicity and hydrophobicity

The amino acid sequences of human respiratory coronavirus S proteins were analyzed separately for their hydrophilicity and hydrophobicity using the ExPASy-ProtScale software.

The SARS ShanghaiQXC2 S protein had the strongest hydrophilicity (2.822) for arginine (Arg) at position 758 and the strongest hydrophobicity (3.189) for threonine (Thr) at position 1213 (Fig. 1 A).

Fig. 1.

Fig. 1

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Hydrophilic and hydrophobic residues of human respiratory coronavirus spike proteins: A. SARS ShanghaiQXC2 S protein, B. MERS nasal swab S protein, C. HCoV-HKU1 SI17244 S protein, D. SARS-CoV-2 Wuhan-Hu-1 S protein. Note: The abscissa represents the amino acid position, and the ordinate represents the amino acid value. greater than 0 is hydrophobic; < 0 is hydrophilic.

The tyrosine (Tyr) at position 540 of the MERS nasal swab S protein had the strongest hydrophilic value (2.822), and the valine (Val) at position 1314 had the strongest hydrophobic value (3.333) (Fig. 1B).

HCoV-HKU1 SI17244 S protein had the strongest hydrophilic value (2.833) for lysine (Lys) at position 753 and the strongest hydrophobic value (4.044) for isoleucine (Ile) at position 1304 (Fig. 1C).

The asparagine (Asn) at position 679 of the SARS-CoV-2 Wuhan-Hu-1 S protein had the strongest hydrophilic value (2.589), and the leucine (Leu) at position 7 had the strongest hydrophobic value (3.222) (Fig. 1D).

The hydrophobicity analysis of the above proteins provides a reference for the identification of the transmembrane region of the protein.

3.3. Transmembrane region

The amino acid sequences of the transmembrane regions of the human respiratory coronavirus S proteins were predicted using TMHMM Server v.2.0. The results shown in Fig. 2 A indicated the probability that amino acids 1 to 1195 of the SARS ShanghaiQXC2 S protein were outside the viral envelope, as indicated by the purple line; the red region indicated that amino acids 1196 to 1218 could form a typical transmembrane helix region, and the blue region indicated that amino acids 1219 to 1225 were inside the viral envelope. In Fig. 2B, the purple line indicates the probability that amino acids 1 to 1295 of the MERS nasal swab S protein are outside the viral envelope, the red region indicates that amino acids 1296 to 1318 can form a transmembrane helical region, and the blue region indicates that amino acids 1319 to 1353 are in the viral envelope. In Fig. 2C, the purple line indicates the probability that amino acids 1 to 1295 in the HCoV-HKU1 SI17244 S protein are outside the viral envelope, with the red region indicates that amino acids 1296 to 1318 can form a typical transmembrane helix region, and the blue region indicates that amino acids 1319 to 1351 are in the viral envelope. In Fig. 2D, the purple line indicates the probability that amino acids 1 to 1213 of SARS-CoV-2 Wuhan-Hu-1 S protein are outside the viral envelope, the red region indicates that amino acids 1214 to 1236 can form a transmembrane helical region, and the blue region indicates that amino acids 1237 to 1273 are inside the viral envelope. The predicted results suggest that the S proteins of human respiratory coronavirus are mainly distributed on the outer side of the viral envelope, and are likely act as a membrane receptor for the viral invasion of cells.

Fig. 2.

Fig. 2

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Prediction of transmembrane domains in human respiratory coronavirus spike protein sequences using TMHMM: SARS ShanghaiQXC2 S protein, B. MERS nasal swab S protein, C. HCoV-HKU1 SI17244 S protein, D. SARS-CoV-2 Wuhan-Hu-1 S protein.

3.4. Signal peptides

The signal peptides of the human respiratory coronavirus S proteins were predicted using the neural network (NN) model of the SignalP4.1 software. The results showed that a possible signal peptide exists in the N-terminal 1–14 residues of the SARS ShanghaiQXC2 S protein. We observed that both the original cleavage site score (C score) and the combined cleavage site score (Y score) peaked at position 14, while the signal peptide score (S score) started to decrease at position 13. The cleavage site is most likely located N terminal to the Y score maximum, which is between amino acids 13 and 14 (TSG-SD) (Fig. 3 A).

Fig. 3.

Fig. 3

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Analysis of signal peptides in the human respiratory coronavirus spike proteins: A. SARS ShanghaiQXC2 S protein, B. MERS nasal swab S protein, C. HCoV-HKU1 SI17244 S protein, D. SARS-CoV-2 Wuhan-Hu-1 S protein.

There is a possible signal peptide in the range of N-terminal residues 1–18 of the MERS nasal swab S protein. We observed that both the original cleavage site score (C score) and the combined cleavage site score (Y score) peaked at position 18, while the signal peptide score (S score) started to decrease at position 15. The cleavage site is most likely located N terminal to the Y score maximum, i.e. between amino acids 17 and 18 (TES-YV) (Fig. 3B).

There is a possible signal peptide in the range of N-terminal residues 1–15 of the HCoV-HKU1 SI17244 S protein. We observed that both the original cleavage site score (C score) and the combined cleavage site score (Y score) peaked at position 14, while the signal peptide score (S score) started to decrease at position 12. The cleavage site was most likely located N terminal to the Y score maximum, i.e. between amino acids 13 and 14 (TLA-VI) (Fig. 3C).

There is a possible signal peptide in the range of 1–15 residues of SARS-CoV-2 Wuhan-Hu-1 S protein. Both the original cleavage site score (C score) and the combined cleavage site score (Y score) peaked at position 14, while the signal peptide score (S score) started to decrease at position 15. The cleavage site is most likely located N terminal to the Y score maximum, i.e. between amino acids 13 and 14 (SQC-VN) (Fig. 3D).

3.5. Phosphorylation sites

Almost all proteins undergo some chemical modifications during and after synthesis, such as cleavage of the peptide chain backbone and modifications of the side chains of specific amino acids. The phosphorylation of proteins is mainly carried out on tyrosine, serine, and threonine residues. The phosphorylation modification sites of human respiratory coronavirus S proteins were predicted using NetPhos 3.1 Server online software. A threshold value of 0.5 is usually taken, and the higher the phosphorylation potential, the higher the confidence level.

The SARS ShanghaiQXC2 S protein has 67 serine (Ser), 43 threonine (Thr) and 21 tyrosine (Tyr) predicted phosphorylation modification sites (Fig. 4 A). The MERS nasal swab S protein contains 90 serine (Ser), 40 threonine (Thr), and 29 tyrosine (Tyr) predicted phosphorylation modification sites (Fig. 4B). The HCoV-HKU1 SI17244 S protein has 88 serine (Ser), 33 threonine (Thr), and 29 tyrosine (Tyr) predicted phosphorylation modification sites (Fig. 4C). The SARS-CoV-2 Wuhan-Hu-1 S protein contains 68 serine (Ser), 45 threonine (Thr), and 23 tyrosine (Tyr) predicted phosphorylation modification sites (Fig. 4D). The prediction results indicated that all four coronavirus S proteins are likely to be phosphorylated proteins. We speculated that these modification sites are related to the phosphorylation and dephosphorylation processes of key molecules in related signaling pathways in vivo.

Fig. 4.

Fig. 4

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Analysis of the phosphorylation sites of human respiratory coronavirus spike proteins: A. SARS ShanghaiQXC2 S protein, B. MERS nasal swab S protein, C. HCoV-HKU1 SI17244 S protein, D. SARS-CoV-2 Wuhan-Hu-1 S protein.

3.6. Glycosylation sites

Glycosylation modifications can regulate protein function, and include N-type and O-type glycan chains. We used NetNGlyc 1.0 and NetOGlyc 4.0 Server online software, respectively, to predict the N type and O-type glycosylation modification sites of the human respiratory coronavirus S proteins. The prediction results showed that the SARS ShanghaiQXC2 S protein contains 24 potential N-glycosylation sites and 193 potential O-glycosylation sites (Figs. 5 A and 6A). The MERS nasal swab S protein contains 25 potential N-glycosylation sites and 226 potential O-glycosylation sites (Figs. 5B and 6B). The HCoV-HKU1 SI17244 S protein contains 31 potential N-glycosylation sites and 231 potential O-glycosylation sites (Figs. 5C and 6C). The SARS-CoV-2 Wuhan-Hu-1 S protein contains 22 potential N-glycosylation sites and 196 potential O-glycosylation sites (Figs. 5D and 6 D). The human respiratory coronavirus S proteins have multiple potential O and N-glycosylation sites, with far more O-glycosylation sites than N-glycosylation sites, suggesting that the antigenic sites might be obscured.

Fig. 5.

Fig. 5

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Analysis of the N-glycosylation sites of human respiratory coronavirus spike proteins: A. SARS ShanghaiQXC2 S protein, B. MERS nasal swab S protein, C. HCoV-HKU1 SI17244 S protein, D. SARS-CoV-2 Wuhan-Hu-1 S protein.

Fig. 6.

Fig. 6

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Analysis of the O-glycosylation sites of human respiratory coronavirus spike proteins: A. SARS ShanghaiQXC2 S protein, B. MERS nasal swab S protein, C. HCoV-HKU1 SI17244 S protein, D. SARS-CoV-2 Wuhan-Hu-1 S protein.

3.7. Antigenic epitopes

The specificity of the S protein depends on the type, nature, number, and spatial configuration of antigenic determinants. We performed epitope prediction for the human respiratory coronavirus S proteins using Predicting Antigenic Peptides online software. The results showed that the SARS ShanghaiQXC2 S protein has 61 epitopes, the MERS nasal swab S protein has 60 epitopes, the HCoV-HKU1 SI17244 S protein has 55 epitopes, and the SARS-CoV-2 Wuhan-Hu-1 S protein has 63 epitopes (Fig. 7 A–D). Predicting the antigenic epitopes facilitates the preparation of S protein-specific antibodies.

Fig. 7.

Fig. 7

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Analysis of the of human respiratory coronavirus spike proteins: A. SARS ShanghaiQXC2 S protein, B. MERS nasal swab S protein, C. HCoV-HKU1 SI17244 S protein, D. SARS-CoV-2 Wuhan-Hu-1 S protein.

3.8. Structural domains

Based on the analysis at the PROSITE database, the structure of the SARS ShanghaiQXC2 S protein was predicted to comprise an S1-N-terminal domain (NTD) region at 12–290 aa, an S1 Carboxy terminal domain (CTD) region at 321–513 aa, an S2-homology region (HR)1 region at 878–983 aa, and an S2-HR2 region at 1125–1207 aa (Fig. 8 A). The structure of the MERS nasal swab S protein was predicted to comprise an S1-NTD region at 17–351 aa, an S1-CTD region at 381–587 aa, an S2-HR1 region at 970–1075 aa, and an S2-HR2 region at 1226–1307 aa (Fig. 8B). The structure of the HCoV-HKU1 SI17244 S protein was predicted to comprise an S1-NTD region at 14–294 aa, an S1-CTD region at 325–605 aa, an S2-HR1 region at 977–1082 aa, and an S2-HR2 region at 1225–1307 aa (Fig. 8C) The structure of SARS-CoV-2 Wuhan Hu 1 S protein was predicted to comprise an S1-NTD region at 9–303 aa, an S1-CTD region at 334–527 aa, an S2-HR1 region at 896–1001 aa, and an S2-HR2 region at 1143–1226 aa (Fig. 8D). We hypothesized that the predicted S protein structural domain could provide a potential receptor binding domain for coronaviruses.

Fig. 8.

Fig. 8

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Structural domains of human respiratory coronavirus spike proteins: A. SARS ShanghaiQXC2 S protein, B. MERS nasal swab S protein, C. HCoV-HKU1 SI17244 S protein, D. SARS-CoV-2 Wuhan-Hu-1 S protein.

3.9. Functional model

Different regions of the S proteins are likely to have different rates of evolution, and some amino acids must be sufficiently conserved during the evolutionary process to maintain their corresponding biological functions. The subunit structures of functional regions that can exist independently are termed structural domains. Therefore, the human respiratory coronavirus S proteins were analyzed using the Simple Modular Structure Research Tool (SMART).

The SARS ShanghaiQXC2 S protein was found to contain two typical functional domains, the Spike-rec-bind domain between aa 317and 569 and the highly conserved functional domain corona_S2 between aa 648 and 1252 (Fig. 9 A).

Fig. 9.

Fig. 9

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Functional motifs of human respiratory coronavirus spike proteins: A. SARS ShanghaiQXC2 S protein, B. MERS nasal swab S protein, C. HCoV-HKU1 SI17244 S protein, D. SARS-CoV-2 Wuhan-Hu-1 S protein.

The two functional domains of the MERS nasal swab S protein are the Spike-rec-bind domain between aa 330 and 583 and the highly conserved functional domain corona_S2 between aa 671and 1270 (Fig. 9B).

The HCoV-HKU1 SI17244 S protein contains two typical functional domains, the Spike rec bind domain between aa 381 and 534 and the highly conserved functional domain corona_S2 between aa 753 and 1352 (Fig. 9C).

The SARS-CoV-2 Wuhan-Hu-1 S protein likewise has two functional domains, namely the Spike-rec-bind domain between aa 330 and 583 and the highly conserved functional domain corona_S2 between aa 671 and 1270 (Fig. 9D).

3.10. Modeling of protein charge and hydrophobicity

Fig. 10 shows graphs providing a visual representation of the S-protein profile, as well as the positive and negative charges and hydrophobicity of the residues. The surface charge and hydrophobicity were demonstrated using the default charge and atomic type of standard residues recommended by Amber 20. The results showed that the SARS ShanghaiQXC2 S protein has a minimum coulomb value of 17.46 C, an average of 1.07 C, and a maximum of 23.47 C; and a minimum hydrophobicity value of 30.15, an average value of 4.03, and a maximum value of 24.76 (Fig. 10A). The MERS nasal swab S protein had a minimum coulomb value of 19.22 C, a mean of 1.64 C, and a maximum of 11.74 C; with a minimum hydrophobicity value of 31.21, a mean value of 4.234, and a maximum value of 25.53 (Fig. 10B). The HCoV-HKU1 SI17244 S protein had a minimum coulomb value of 17.41 C, a mean of 1.15 C, and a maximum of 15.35 C; with a minimum hydrophobicity value of 32, a mean of 4.519, and a maximum 27.4 (Fig. 10C). The SARS-CoV-2 Wuhan-Hu-1 S protein had a minimum coulomb value of 21.20 C, a mean of 1.19 C, and a maximum of 13.68 C, with a minimum hydrophobicity value of 7.79, a mean of 4.556, and a maximum of 25.61 (Fig. 10D).

Fig. 10.

Fig. 10

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Modeling of protein charge and hydrophobicity of human respiratory coronavirus spike proteins: A. SARS ShanghaiQXC2 S protein, B. MERS nasal swab S protein, C. HCoV-HKU1 SI17244 S protein, D. SARS-CoV-2 Wuhan-Hu-1 S protein.

4. Discussion

All coronaviruses share similarities in genome composition and protein structure, including structural proteins N, S, E, M and nonstructural proteins 1–16 (nsp1–nsp16) encoded by the 3′ segment of the genome(Brian and Baric, 2005). The RBD in the S protein can bind to the receptor on the host cell membrane and then undergo membrane fusion with the host cell via S2 (Rabaan et al., 2020). The S protein can also induce the host immune system to mount an immune response and is thus the key protein for vaccine development Gaebler et al., 2021). In addition to these roles, changes in the spatial structure of S proteins can directly affect the virulence of the virus (Aleem et al., 2022). There are also differences in tissue preference and host range of coronaviruses of the same genus (Li et al., 2020). Although SARS ShanghaiQXC2, MERS nasal swab, HCoV-HKU1, SI17244, and SARS-CoV-2 Wuhan-Hu-1 are in the same genus (β), they do not all use the same receptor. SARS-CoV-2 Wuhan-Hu-1 uses the same host receptor (ACE2) as SARS ShanghaiQXC2, whereas the receptor for MERS nasal swab is DPP4 (Han et al., 2022, Raj et al., 2013, Wu et al., 2009).

All proteins have a specific structure and function. The spatial structure of a protein determines its biological function. Changes to the spatial structure or chemical modifications will affect a protein's properties and functions (Jeffery, 2016). Prediction of the function and structure of human respiratory coronavirus S proteins using bioinformatic software will help us to understand the mechanism of action of these proteins. The physicochemical properties of human respiratory coronavirus S proteins were analyzed using ProtParam, and the results are informative for gene cloning and protein expression studies (Garg et al., 2016).

We analyzed the hydrophilicity and hydrophobicity of human respiratory coronavirus S proteins using ExPASy-ProtScale and performed surface hydrophobicity analysis using the PDB database and predicted structures. The results showed that these S proteins were negatively charged overall and rich in hydrophilic amino acids on their surface. In general, the hydrophobicity of amino acids is one of the main drivers of protein folding, thus the protein hydrophobicity distribution can reflect the protein folding ability (Halder and Jana, 2021).

The presence of a transmembrane region in a protein indicates that the protein might function as a membrane receptor or is a membrane-localized protein (Díaz, 2010, Takeshi, 2011). Using TMHMM Server v.2.0, we predicted the transmembrane regions of the human respiratory coronavirus S proteins, which indicated that all four S proteins have a transmembrane region. This is useful to analyze the S protein function, to develop purification protocols, and analyze its expression patterns. In addition, the transmembrane region could be used as a primary target for drugs, thus providing a basis for the development of drugs targeted to the S protein as a membrane protein (Chen et al., n.d.).

A signal peptide is a short amino acid sequence of 13–26 residues, usually located at the N terminus of a protein (von Heijne, 1983). They have important roles in the control of protein secretion, translocation, and expression of exogenous proteins in organisms (Ohmuro-Matsuyama and Yamaji, 2017, von Heijne, 1983). In addition, signal peptides can be used as a basis for determining the cellular localization of proteins (Liu et al., 2006). In this study, we predicted the location of the human respiratory coronavirus S protein signal peptide using SignalP4.1, which showed that the S proteins of all four coronaviruses contain an N-terminal signal peptide. Based on the physiological role of signal peptides, we speculated that the S protein signal peptide might determine the subcellular localization of S protein. This result might provide a reference for the in-depth study of the structure and function of the S protein.

Phosphorylation, as an important post-translational modification mechanism of proteins, can mediate cellular signaling and control and regulate protein viability and function. Through the analysis at the NetPhos 3.1 Server, we predicted the number and location of phosphorylation sites of S protein of SARS ShanghaiQXC2, MERS nasal swab, HCoV-HKU1 SI17244, and SARS CoV-2 Wuhan-Hu-1. These phosphorylation sites might mediate the intracellular phosphorylation and dephosphorylation process of S proteins, which is often the switch for activation of regulatory S proteins. This also provides a theoretical basis for the development of drugs targeting the phosphorylation-mediated activation/inhibition of the S protein.

Glycosylation is the most common form of biomolecular modification, including N- and O glycosylation modifications and glycolipid modifications, and is one of the most important post translational modifications in living organisms (Watanabe et al., 2019). Viral protein glycosylation has a wide range of roles in viral pathobiology, including mediating protein folding and stability, shaping viral directionality, and protecting potential antigenic epitopes from immune surveillance (Watanabe et al., 2020, Watanabe et al., 2019, Zhang et al., 2020). The glycosylation sites of the S proteins of SARS ShanghaiQXC2, MERS nasal swab, HCoV-HKU1 SI17244, and SARS-CoV-2 Wuhan-Hu-1 were predicted by NetNGlyc 1.0 Serve and NetOGlyc 4.0 Serve, respectively. The results showed that the S proteins of all four viruses contained many N-glycosylation sites and O glycosylation sites, and the number of O-glycosylation sites was much higher than that of N glycosylation sites. Previous research identified a total of 22 N-glycosylation modification sites in the extracellular domain of the S protein of SARS-CoV-2 purified and expressed in vitro and in the S protein extracted from viral particles, which is also consistent with our prediction results (Gong et al., 2021, p. 2). Studies have reported that the coronavirus S protein is a highly glycosylated protein and that glycosylation modifications might endow the coronavirus S protein with greater structural flexibility, which could play an important role in virus recognition, binding, and invasion of host cell receptors, and might protect some epitopes from antibody neutralization (Watanabe et al., 2020, Zhang et al., 2020). Therefore, a better understanding of S protein glycosylation could provide an opportunity to develop anti-SARS-CoV-2 glycoconjugates.

Monoclonal antibodies are usually classified according to their epitopes (the part of the target protein bound by the monoclonal antibody) and paratopes (the part of the monoclonal antibody bound to the target) (Deng et al., 2018). Developers are increasingly using the same or similar epitope (paratope) information to enhance the generality of monoclonal antibodies, which has generated higher value in recognizing antigenic epitope information (Klein et al., 2013, Zhao et al., 2021). In addition to monoclonal antibodies, small molecule inhibitors that inhibit viral infection by blocking RNA binding activity or normal oligomerization of N proteins have been developed, including HCoV-OC43 and MERS-CoV (Cheng et al., 2021). This class of drugs currently targets mainly N proteins, based on their structural conservation. In contrast, antibodies are still more often developed against S proteins (Bai et al., 2021, Lan et al., 2022, Mohammed, 2022, Su et al., xxxx). We predicted the epitopes of human respiratory coronavirus S proteins using Predict Antigenic Peptides, and we found 61 epitopes for SARS ShanghaiQXC2 S protein, 60 epitopes for MERS nasal swab S protein, 55 epitopes for HCoV-HKU1 SI17244 S protein, and 63 epitopes for SARS -CoV-2 Wuhan-Hu-1 S protein. Based on our predictions, subsequent research can use these epitopes for vaccine design. Then, the corresponding antigenic epitopes can be transferred into an expression system by genetic engineering, such that the corresponding antigenic proteins can be produced. In addition, it could also help in the discovery and development of antiviral inhibitors targeting S protein antigenic epitopes.

Based on SMART and PROSITE database analysis, we found that the S proteins of SARS ShanghaiQXC2, MERS nasal swab, HCoV-HKU1 SI17244, and SARS-CoV-2 Wuhan-Hu-1 S all contain two common functional domains, i.e., the Spike-rec- bind and corona-S2 domains. The Spike-rec-bind functional domain contains two major functional motifs, namely the NTD and CTD, while the corona-S2 functional domain contains functional motifs HR1 and HR2. S proteins can be functionally classified into S1 and S2 (Lu et al., 2020, Zhou et al., 2020). Structurally, they can be further divided into NTD sand CTDs, and both S1-NTD and S1-CTD can bind to cell surface binding receptors (Li, 2013). Based on the feature that homotrimers of S proteins play an important role in receptor binding and viral invasion, it is suggested that S-NTDs and S-CTDs can be used as key targets within their structural domains in the preparation of antibodies against coronaviruses (Jackson et al., n.d.; Wang et al., n.d.). It has been shown that HR1 and HR2 can facilitate virus entry into cells and also promote cell–cell fusion, thus enhancing intercellular infection by the virus (Bosch et al., 2003, Root, 2001, Yuan et al., 2004). The structural core regions of the S proteins of different coronaviruses are highly conserved; however, the spatial conformation of their receptor-binding regions varies, leading to differences in the host species infected by the virus (Jackson et al., n.d.; Shang et al., 2020, Wrapp et al., 2020).

Finally, we modeled the protein surface banding and hydrophobicity, which can not only reveal the protein charge and solubility, but also can provide a reference to further investigate the functions of S proteins related to their surface properties.

5. Conclusion

The present study comprised a bioinformatic analysis of the structure and function of S proteins of SARS-CoV, MERS-CoV, HCoV-HKU1, and SARS-CoV-2, which is significant to increase our understanding of S proteins, and will support the detection of antibodies to coronaviruses, the screening and development of antiviral drugs targeting the proteins, and the design of antiviral vaccines. Our analysis has an important reference value for designing broad-spectrum antiviral drugs and coronavirus vaccines using the S protein.

6. Foundation

This work was supported by the Fundamental Research Funds for the Central Universities (XDJK2020RC001), and Venture & Innovation Support Program for Chongqing Overseas Returnees (cx2019097).

CRediT authorship contribution statement

Zheng Niu: Data curation, Formal analysis, Software, Investigation, Writing – original draft. ShaSha Xu: Conceptualization, Methodology, Investigation, Writing – original draft. JingYi Zhang: Visualization, Investigation. ZhuoLan Zou: Visualization, Investigation. Lixin Ren: Resources, Supervision. XiangYang Liu: Software, Validation. ShuJuan Zhang: Visualization. Hong Zou: Software. Xia Hu: Resources. Jing Wang: Visualization. Li Zhang: Supervision. Yang Zhou: Supervision. ZhenHui Song: Conceptualization, Funding acquisition, Resources, Supervision, Writing – review & editing.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Data availability

No data was used for the research described in the article.

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