Combining MOE Bioinformatics Analysis and In Vitro Pseudovirus Neutralization Assays to Predict the Neutralizing Ability of CV30 Monoclonal Antibody on SARS-CoV-2 Variants
Combining bioinformatics and in vitro cytology assays, a predictive method was established to quickly evaluate the protective effect of immunity acquired through SARS-CoV-2 infection against variants. Bioinformatics software was first used to predict the changes in the affinity of variant antigens t...
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MDPI AG
2023-07-01
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| Series: | Viruses |
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| Online Access: | https://www.mdpi.com/1999-4915/15/7/1565 |
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| author | Yajuan Zhu Husheng Xiong Shuang Liu Dawei Wu Xiaomin Zhang Xiaolu Shi Jing Qu Long Chen Zheng Liu Bo Peng Dingmei Zhang |
| author_facet | Yajuan Zhu Husheng Xiong Shuang Liu Dawei Wu Xiaomin Zhang Xiaolu Shi Jing Qu Long Chen Zheng Liu Bo Peng Dingmei Zhang |
| author_sort | Yajuan Zhu |
| collection | DOAJ |
| description | Combining bioinformatics and in vitro cytology assays, a predictive method was established to quickly evaluate the protective effect of immunity acquired through SARS-CoV-2 infection against variants. Bioinformatics software was first used to predict the changes in the affinity of variant antigens to the CV30 monoclonal antibody by integrating bioinformatics and cytology assays. Then, the ability of the antibody to neutralize the variant antigen was further verified, and the ability of the CV30 to neutralize the new variant strain was predicted through pseudovirus neutralization experiments. The current study has demonstrated that when the Molecular Operating Environment (MOE) predicts |ΔBFE| ≤ 3.0003, it suggests that the CV30 monoclonal antibody exhibits some affinity toward the variant strain and can potentially neutralize it. However, if |ΔBFE| ≥ 4.1539, the CV30 monoclonal antibody does not display any affinity for the variant strain and cannot neutralize it. In contrast, if 3.0003 < |ΔBFE| < 4.1539, it is necessary to conduct a series of neutralization tests promptly with the CV30 monoclonal antibody and the variant pseudovirus to obtain results and supplement the existing method, which is faster than the typical procedures. This approach allows for a rapid assessment of the protective efficacy of natural immunity gained through SARS-CoV-2 infection against variants. |
| first_indexed | 2024-03-11T00:33:51Z |
| format | Article |
| id | doaj.art-03c793ca4cf4468d83b3b4554777520b |
| institution | Directory Open Access Journal |
| issn | 1999-4915 |
| language | English |
| last_indexed | 2024-03-11T00:33:51Z |
| publishDate | 2023-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Viruses |
| spelling | doaj.art-03c793ca4cf4468d83b3b4554777520b2023-11-18T21:45:29ZengMDPI AGViruses1999-49152023-07-01157156510.3390/v15071565Combining MOE Bioinformatics Analysis and In Vitro Pseudovirus Neutralization Assays to Predict the Neutralizing Ability of CV30 Monoclonal Antibody on SARS-CoV-2 VariantsYajuan Zhu0Husheng Xiong1Shuang Liu2Dawei Wu3Xiaomin Zhang4Xiaolu Shi5Jing Qu6Long Chen7Zheng Liu8Bo Peng9Dingmei Zhang10School of Public Health, Sun Yat-Sen University, Guangzhou 510080, ChinaSchool of Public Health, Sun Yat-Sen University, Guangzhou 510080, ChinaSchool of Public Health, Sun Yat-Sen University, Guangzhou 510080, ChinaSchool of Public Health, Sun Yat-Sen University, Guangzhou 510080, ChinaDepartment of Microbiology Laboratory, Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, ChinaDepartment of Microbiology Laboratory, Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, ChinaDepartment of Microbiology Laboratory, Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, ChinaDepartment of Microbiology Laboratory, Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, ChinaKobilka Institute of Innovative Drug Discovery, School of Medicine, Chinese University of Hong Kong, Shenzhen 518172, ChinaDepartment of Microbiology Laboratory, Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, ChinaSchool of Public Health, Sun Yat-Sen University, Guangzhou 510080, ChinaCombining bioinformatics and in vitro cytology assays, a predictive method was established to quickly evaluate the protective effect of immunity acquired through SARS-CoV-2 infection against variants. Bioinformatics software was first used to predict the changes in the affinity of variant antigens to the CV30 monoclonal antibody by integrating bioinformatics and cytology assays. Then, the ability of the antibody to neutralize the variant antigen was further verified, and the ability of the CV30 to neutralize the new variant strain was predicted through pseudovirus neutralization experiments. The current study has demonstrated that when the Molecular Operating Environment (MOE) predicts |ΔBFE| ≤ 3.0003, it suggests that the CV30 monoclonal antibody exhibits some affinity toward the variant strain and can potentially neutralize it. However, if |ΔBFE| ≥ 4.1539, the CV30 monoclonal antibody does not display any affinity for the variant strain and cannot neutralize it. In contrast, if 3.0003 < |ΔBFE| < 4.1539, it is necessary to conduct a series of neutralization tests promptly with the CV30 monoclonal antibody and the variant pseudovirus to obtain results and supplement the existing method, which is faster than the typical procedures. This approach allows for a rapid assessment of the protective efficacy of natural immunity gained through SARS-CoV-2 infection against variants.https://www.mdpi.com/1999-4915/15/7/1565SARS-CoV-2mutationprediction |
| spellingShingle | Yajuan Zhu Husheng Xiong Shuang Liu Dawei Wu Xiaomin Zhang Xiaolu Shi Jing Qu Long Chen Zheng Liu Bo Peng Dingmei Zhang Combining MOE Bioinformatics Analysis and In Vitro Pseudovirus Neutralization Assays to Predict the Neutralizing Ability of CV30 Monoclonal Antibody on SARS-CoV-2 Variants Viruses SARS-CoV-2 mutation prediction |
| title | Combining MOE Bioinformatics Analysis and In Vitro Pseudovirus Neutralization Assays to Predict the Neutralizing Ability of CV30 Monoclonal Antibody on SARS-CoV-2 Variants |
| title_full | Combining MOE Bioinformatics Analysis and In Vitro Pseudovirus Neutralization Assays to Predict the Neutralizing Ability of CV30 Monoclonal Antibody on SARS-CoV-2 Variants |
| title_fullStr | Combining MOE Bioinformatics Analysis and In Vitro Pseudovirus Neutralization Assays to Predict the Neutralizing Ability of CV30 Monoclonal Antibody on SARS-CoV-2 Variants |
| title_full_unstemmed | Combining MOE Bioinformatics Analysis and In Vitro Pseudovirus Neutralization Assays to Predict the Neutralizing Ability of CV30 Monoclonal Antibody on SARS-CoV-2 Variants |
| title_short | Combining MOE Bioinformatics Analysis and In Vitro Pseudovirus Neutralization Assays to Predict the Neutralizing Ability of CV30 Monoclonal Antibody on SARS-CoV-2 Variants |
| title_sort | combining moe bioinformatics analysis and in vitro pseudovirus neutralization assays to predict the neutralizing ability of cv30 monoclonal antibody on sars cov 2 variants |
| topic | SARS-CoV-2 mutation prediction |
| url | https://www.mdpi.com/1999-4915/15/7/1565 |
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