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
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.
| Medienart: |
Artikel |
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| Erscheinungsjahr: |
2020 |
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| Erschienen: |
2020 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:53 |
|---|---|
| Enthalten in: |
Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences - 53(2020), 1 vom: 21. Dez., Seite 150-158 |
| Sprache: |
Chinesisch |
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| Beteiligte Personen: |
Cao, Z [VerfasserIn] |
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| Themen: |
Antiviral Agents |
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| Anmerkungen: |
Date Completed 09.02.2021 Date Revised 18.02.2021 published: Print Citation Status MEDLINE |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM321108825 |
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| 100 | 1 | |a Cao, Z |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a 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 |
| 264 | 1 | |c 2020 | |
| 336 | |a Text |b txt |2 rdacontent | ||
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| 500 | |a Date Completed 09.02.2021 | ||
| 500 | |a Date Revised 18.02.2021 | ||
| 500 | |a published: Print | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a 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 | ||
| 520 | |a 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 | ||
| 520 | |a 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 | ||
| 520 | |a 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 | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Molecular docking simulation | |
| 650 | 4 | |a Mutation | |
| 650 | 4 | |a SARS-CoV-2 | |
| 650 | 4 | |a Sequence alignment | |
| 650 | 4 | |a Spike glycoprotein, coronavirus | |
| 650 | 7 | |a Antiviral Agents |2 NLM | |
| 650 | 7 | |a Spike Glycoprotein, Coronavirus |2 NLM | |
| 650 | 7 | |a Peptidyl-Dipeptidase A |2 NLM | |
| 650 | 7 | |a EC 3.4.15.1 |2 NLM | |
| 700 | 1 | |a Wang, L T |e verfasserin |4 aut | |
| 700 | 1 | |a Liu, Z M |e verfasserin |4 aut | |
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