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Journal of Peking University (Health Sciences) ›› 2021, Vol. 53 ›› Issue (1): 150-158. doi: 10.19723/j.issn.1671-167X.2021.01.023

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Homologous modeling and binding ability analysis of Spike protein after point mutation of severe acute respiratory syndrome coronavirus 2 to receptor proteins and potential antiviral drugs

CAO Ze,WANG Le-tong,LIU Zhen-ming()   

  1. State Key Laboratory of Natural and Biomimetic Drugs, Peking University School of Pharmaceutical Sciences, Beijing 100191, China
  • Received:2020-07-06 Online:2021-02-18 Published:2021-02-07
  • Contact: Zhen-ming LIU E-mail:zmliu@bjmu.edu.cn

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Abstract:

Objective: To explore the natural mutations in Spike protein (S protein) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the changes of affinity between virus and associated receptors or drug molecules before and after the mutation based on whole length sequencing results.Methods: In the study, the bioinformatics analysis of all the published sequences of SARS-CoV-2 was conducted and thus the high frequency mutation sites were affirmed. Taking advantages of PolyPhen-2, the functional influence of each mutation in S protein was prospected. The 3D homologous modelling was performed by SWISS-MODEL to establish mutated S protein structural model, in which the protein-docking was then implemented with angiotensin-converting enzyme 2 (ACE2), dipeptidyl peptidase-4 (DPP4) and aminopeptidase N (APN) by ZDOCK, and the combining capacity of each mutated S protein evaluated by FiPD. Finally, the binding ability between mutated S proteins and anti-virus drugs were prospected and evaluated through AutoDock-Chimera 1.14.Results: The mutations in specific region of S protein had greater tendency to destroy the S protein function by analysis of mutated S protein structure. Protein-receptor docking analysis between naturally mutated S protein and host receptors showed that, in the case of spontaneous mutation, the binding ability of S protein to ACE2 tended to be weakened, while the binding ability of DPP4 tended to be enhanced, and there was no significant change in the binding ability of APN. According to the computational simulation results of affinity binding between small molecular drugs and S protein, the affinity of aplaviroc with S protein was significantly higher than that of other small molecule drug candidates.Conclusion: The region from 400-1 100 amino acid in S protein of SARS-CoV-2 is the mutation sensitive part during natural state, which was more potential to mutate than other part in S protein during natural state. The mutated SARS-CoV-2 might tend to target human cells with DPP4 as a new receptor rather than keep ACE2 as its unique receptor for human infection. At the same time, aplaviroc, which was used for the treatment of human immunodeficiency virus (HIV) infection, may become a new promising treatment for SARS-CoV-2 and could be a potential choice for the development of SARS-CoV-2 drugs.

Key words: SARS-CoV-2, Spike glycoprotein, coronavirus, Mutation, Sequence alignment, Molecular docking simulation

CLC Number: 

  • R373.19

Table 1

Analysis of S protein mutation sites"

Nucleotide locus Amino acid mutation type Base mutation type Numbers Mutation possibility
21 750 S63V C-A 5 1.1%
21 644 Y28N T-A 3 0.7%
21 646 Y28stop C-A 6 1.4%
21 575 L5I C-A 6 1.4%
21 724 L54F G-T 3 0.7%
21 783 N74I/T/S A-I 7 1.6%
21 846 T95N C-A 6 1.4%
21 850 E96D G-T 5 1.1%
21 893 D111Y G-T 4 0.9%
21 950 V130F G-T 7 1.6%
22 033 F157L C-A 6 1.4%
22 104 G181V G-T 3 0.7%
22 207 D215E T-A/G 7 1.6%
22 432 D290E C-A 4 0.9%
22 604 A348S G-T 4 0.9%
22 606 A340A A-I 3 0.7%
22 984 Q474H G-T 6 1.4%
22 988 G476C G-T 4 0.9%
23 010 V483D/G T-A/G 5 1.1%
23 403 D614V/A/G A-I 3 0.7%
23 730 T723N C-A 4 0.9%
23 952 F797Y/C T-A/G 7 1.6%
24 022 D820E T-A/G 9 2.1%
24 034 N824K C-A 7 1.6%
24 325 K921N A-I 2 0.5%
24 368 D936Y G-T 5 1.1%
24 694 G1044G A-I 3 0.7%
24 795 A1078D C-A 6 1.4%
25 064 D1168Y G-T 7 1.6%
25 094 N1178D/H/Y A-I 4 0.9%
25 337 D1259Y G-T 6 1.4%
25 335 E1258D A-I 7 1.6%
25 336 E1258V/A/G A-I 3 0.7%

Figure 1

Possibility analysis of S protein point mutation affecting the overall structure"

Figure 2

Structure of mutation site of Spike protein before and after the point mutation A, Y28H; B, D111N; C, A348N; D, D614G; E, T723I; F, F797S; G, D936N; H, A1078V. Because of the existence of synonymous mutations and the cleavage of mutation sites in mature proteins, 33 high-frequency mutation sites eventually produced only 8 kinds of sequence changes in mature spike proteins."

Figure 3

Changes in the affinity of S protein with ACE2, DPP4, and APN receptors after mutation A, the absolute strength of binding ability of each receptor to the mutant protein, indicating that ACE2 receptor has the strongest binding ability to all mutant S protein. B, C, and D represents the percentage of changes in S protein’s binding ability to ACE2, APN, and DPP4 receptors respectively after mutation. The green part represents the changes in binding ability after mutation. The green part on the left indicates that the mutation leads to reduced binding ability; the green part on the right indicates that the mutation leads to increased binding ability. ACE2, angiotensin-converting enzyme 2; DPP4, dipeptidyl peptidase-4; APN, aminopeptidase N. AS, QH, VD, VG, and GC represent the mutation of A384S, Q474H, V483D, V483G, and G476C, respectively."

Figure 4

Schematic diagram of protein structure. A, the 3D modeling structure diagram of S protein; B, C, D, the protein structure diagrams of ACE2, DPP4, and APN, respectively; E, the structural diagram of RBD region of S protein; F, G, H, the 3D modeling structure diagrams of ACE2, DPP4, and APN, respectively binding complex with RBD region. ACE2, angiotensin-converting enzyme 2; DPP4, dipeptidyl peptidase-4; APN, aminopeptidase N; RBD, receptor binding domain."

Table 2

Cluster analysis of the binding ability of ACE2, DPP4, and APN receptors to each mutant RBD of S protein"

Mutation type ACE2 cluster DPP4 cluster APN cluster Mutation type ACE2 cluster DPP4 cluster APN cluster
AS 1 1 1 QH 2 2 2
AS-GC 2 2 2 QH-GC 1 3 2
AS-QH 1 3 3 QH-VD 1 3 3
AS-QH-GC 2 3 3 QH-VD-GC 1 2 2
AS-QH-VD 3 3 2 QH-VG 1 1 1
AS-QH-VD-GC 1 3 3 QH-VG-GC 2 3 3
AS-QH-VG 2 1 1 VD 1 1 1
AS-VD 1 2 1 VG 1 3 1
AS-VD-GC 1 2 1 Cluster 1 number 14 5 8
AS-VG 1 1 1 Cluster 2 number 7 8 8
AS-VG-GC 2 3 3 Cluster 3 number 2 10 7
AS-VG-QH-GC 2 3 3 Cluster 1 center -77.04 -121.57 -101.25
GC 1 2 2 Cluster 2 center 97.01 14.84 18.77
GC-VD 1 2 2 Cluster 3 center 385.64 190.30 226.15
GC-VG 3 2 2

Figure 5

Data analysis of the combination of small molecule drugs with RBD of S protein A, the binding free energy of various small molecule drugs with various mutant RBD. The smaller the binding free energy is, the easier the binding is. Aplaviroc has the strongest binding ability with various mutant subtypes. B-F, represents the schematic diagram of 3D modeling and analysis in cinanserin, aplaviroc, vicriviroc, obatoclax, and curcumin combined with RBD, respectively. 1 kcal=4.186 8 kJ. Abbreviations as in Figure 3."

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