北京大学学报(医学版) ›› 2021, Vol. 53 ›› Issue (1): 150-158. doi: 10.19723/j.issn.1671-167X.2021.01.023

• 论著 • 上一篇    下一篇

严重急性呼吸综合征冠状病毒2的Spike蛋白点突变后与受体蛋白质及潜在抗病毒药物结合能力的同源建模分析

曹泽,王乐童,刘振明()   

  1. 北京大学药学院天然药物及仿生药物国家重点实验室,北京 100191
  • 收稿日期:2020-07-06 出版日期:2021-02-18 发布日期:2021-02-07
  • 通讯作者: 刘振明 E-mail:zmliu@bjmu.edu.cn

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

摘要:

目的: 分析严重急性呼吸综合征冠状病毒2(severe acute respiratory syndrome coronavirus 2,SARS-CoV-2)的全长测序信息中,其刺突蛋白(Spike protein,S蛋白)的自发突变情况,以及S蛋白突变前后与宿主相关受体蛋白质和潜在抗病毒药物结合能力的变化。方法: 对SARS-CoV-2的一级序列进行生物信息学分析,确定高频突变位点,利用PolyPhen-2软件逐一对S蛋白突变后的功能进行预测和分析。使用SWISS-MODEL系统对突变后的S蛋白序列进行基于相似性的同源建模,利用ZDOCK程序对所建模型与血管紧张素转化酶2(angiotensin-converting enzyme 2,ACE2)、二肽基肽酶-4(dipeptidyl peptidase-4,DPP4,又称CD26)以及氨基肽酶N(aminopeptidase N,APN,又称CD13)进行蛋白质对接,用FiPD软件对结合能力评价结果进行分析,最后采用AutoDock-Chimera 1.14对突变前后的S蛋白与潜在抗病毒药物的结合能力进行预测和比较分析。结果: S蛋白的某些特定区域发生突变能够更大程度地影响其功能,突变之后,S蛋白与ACE2的结合能力趋向于减弱,而与DPP4的结合能力趋向于增强,与APN的结合能力无显著变化。抗人类免疫缺陷病毒(human immunodeficiency virus,HIV)药物aplaviroc与S蛋白的亲和能力显著高于其他候选小分子药物。结论: SARS-CoV-2在自然状态下发生突变,其S蛋白第400~1 100个氨基酸的区域为点突变高频区,突变趋势为与DPP4结合力增强,DPP4可能成为SARS-CoV-2感染细胞的新受体,aplaviroc可能成为一种SARS-CoV-2治疗药物的潜在选择。

关键词: 严重急性呼吸综合征冠状病毒2, 刺突糖蛋白, 冠状病毒, 突变, 序列比对, 分子对接模拟

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

中图分类号: 

  • R373.19

表1

S蛋白突变位点的分析"

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%

图1

S蛋白点突变对整体结构产生影响的可能性分析"

图2

S蛋白点突变前后的突变位点结构"

图3

S蛋白突变后与ACE2、DPP4和APN受体亲和力的变化"

图4

蛋白质结构示意图"

表2

ACE2、DPP4、APN与S蛋白各突变RBD结合能力的聚簇分析"

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

图5

小分子药物与突变S蛋白RBD结合的数据分析"

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