Insights from a computational analysis of the SARS‐CoV‐2 Omicron variant: Host–pathogen interaction, pathogenicity, and possible drug therapeutics
Abstract Introduction Prominently accountable for the upsurge of COVID‐19 cases as the world attempts to recover from the previous two waves, Omicron has further threatened the conventional therapeutic approaches. The lack of extensive research regarding Omicron has raised the need to establish corr...
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| Format: | Article |
| Language: | English |
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Wiley
2022-07-01
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| Series: | Immunity, Inflammation and Disease |
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| Online Access: | https://doi.org/10.1002/iid3.639 |
| _version_ | 1811229977646989312 |
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| author | Md Sorwer Alam Parvez Manash Kumar Saha Md. Ibrahim Yusha Araf Md. Taufiqul Islam Gen Ohtsuki Mohammad Jakir Hosen |
| author_facet | Md Sorwer Alam Parvez Manash Kumar Saha Md. Ibrahim Yusha Araf Md. Taufiqul Islam Gen Ohtsuki Mohammad Jakir Hosen |
| author_sort | Md Sorwer Alam Parvez |
| collection | DOAJ |
| description | Abstract Introduction Prominently accountable for the upsurge of COVID‐19 cases as the world attempts to recover from the previous two waves, Omicron has further threatened the conventional therapeutic approaches. The lack of extensive research regarding Omicron has raised the need to establish correlations to understand this variant by structural comparisons. Here, we evaluate, correlate, and compare its genomic sequences through an immunoinformatic approach to understand its epidemiological characteristics and responses to existing drugs. Methods We reconstructed the phylogenetic tree and compared the mutational spectrum. We analyzed the mutations that occurred in the Omicron variant and correlated how these mutations affect infectivity and pathogenicity. Then, we studied how mutations in the receptor‐binding domain affect its interaction with host factors through molecular docking. Finally, we evaluated the drug efficacy against the main protease of the Omicron through molecular docking and validated the docking results with molecular dynamics simulation. Results Phylogenetic and mutational analysis revealed the Omicron variant is similar to the highly infectious B.1.620 variant, while mutations within the prominent proteins are hypothesized to alter its pathogenicity. Moreover, docking evaluations revealed significant differences in binding affinity with human receptors, angiotensin‐converting enzyme 2 and NRP1. Surprisingly, most of the tested drugs were proven to be effective. Nirmatrelvir, 13b, and Lopinavir displayed increased effectiveness against Omicron. Conclusion Omicron variant may be originated from the highly infectious B.1.620 variant, while it was less pathogenic due to the mutations in the prominent proteins. Nirmatrelvir, 13b, and Lopinavir would be the most effective, compared to other promising drugs that were proven effective. |
| first_indexed | 2024-04-12T10:22:22Z |
| format | Article |
| id | doaj.art-320392b89f924f5bab9aef39ad019dca |
| institution | Directory Open Access Journal |
| issn | 2050-4527 |
| language | English |
| last_indexed | 2024-04-12T10:22:22Z |
| publishDate | 2022-07-01 |
| publisher | Wiley |
| record_format | Article |
| series | Immunity, Inflammation and Disease |
| spelling | doaj.art-320392b89f924f5bab9aef39ad019dca2022-12-22T03:37:04ZengWileyImmunity, Inflammation and Disease2050-45272022-07-01107n/an/a10.1002/iid3.639Insights from a computational analysis of the SARS‐CoV‐2 Omicron variant: Host–pathogen interaction, pathogenicity, and possible drug therapeuticsMd Sorwer Alam Parvez0Manash Kumar Saha1Md. Ibrahim2Yusha Araf3Md. Taufiqul Islam4Gen Ohtsuki5Mohammad Jakir Hosen6Department of Drug Discovery Medicine Kyoto University Graduate School of Medicine Kyoto JapanDepartment of Genetic Engineering & Biotechnology Shahjalal University of Science & Technology Sylhet BangladeshDepartment of Genetic Engineering & Biotechnology Shahjalal University of Science & Technology Sylhet BangladeshDepartment of Genetic Engineering & Biotechnology Shahjalal University of Science & Technology Sylhet BangladeshDepartment of Genetic Engineering & Biotechnology Shahjalal University of Science & Technology Sylhet BangladeshDepartment of Drug Discovery Medicine Kyoto University Graduate School of Medicine Kyoto JapanDepartment of Genetic Engineering & Biotechnology Shahjalal University of Science & Technology Sylhet BangladeshAbstract Introduction Prominently accountable for the upsurge of COVID‐19 cases as the world attempts to recover from the previous two waves, Omicron has further threatened the conventional therapeutic approaches. The lack of extensive research regarding Omicron has raised the need to establish correlations to understand this variant by structural comparisons. Here, we evaluate, correlate, and compare its genomic sequences through an immunoinformatic approach to understand its epidemiological characteristics and responses to existing drugs. Methods We reconstructed the phylogenetic tree and compared the mutational spectrum. We analyzed the mutations that occurred in the Omicron variant and correlated how these mutations affect infectivity and pathogenicity. Then, we studied how mutations in the receptor‐binding domain affect its interaction with host factors through molecular docking. Finally, we evaluated the drug efficacy against the main protease of the Omicron through molecular docking and validated the docking results with molecular dynamics simulation. Results Phylogenetic and mutational analysis revealed the Omicron variant is similar to the highly infectious B.1.620 variant, while mutations within the prominent proteins are hypothesized to alter its pathogenicity. Moreover, docking evaluations revealed significant differences in binding affinity with human receptors, angiotensin‐converting enzyme 2 and NRP1. Surprisingly, most of the tested drugs were proven to be effective. Nirmatrelvir, 13b, and Lopinavir displayed increased effectiveness against Omicron. Conclusion Omicron variant may be originated from the highly infectious B.1.620 variant, while it was less pathogenic due to the mutations in the prominent proteins. Nirmatrelvir, 13b, and Lopinavir would be the most effective, compared to other promising drugs that were proven effective.https://doi.org/10.1002/iid3.639ACE2COVID‐19drugs efficacyhost–pathogen interactionNRP1Omicron variant |
| spellingShingle | Md Sorwer Alam Parvez Manash Kumar Saha Md. Ibrahim Yusha Araf Md. Taufiqul Islam Gen Ohtsuki Mohammad Jakir Hosen Insights from a computational analysis of the SARS‐CoV‐2 Omicron variant: Host–pathogen interaction, pathogenicity, and possible drug therapeutics Immunity, Inflammation and Disease ACE2 COVID‐19 drugs efficacy host–pathogen interaction NRP1 Omicron variant |
| title | Insights from a computational analysis of the SARS‐CoV‐2 Omicron variant: Host–pathogen interaction, pathogenicity, and possible drug therapeutics |
| title_full | Insights from a computational analysis of the SARS‐CoV‐2 Omicron variant: Host–pathogen interaction, pathogenicity, and possible drug therapeutics |
| title_fullStr | Insights from a computational analysis of the SARS‐CoV‐2 Omicron variant: Host–pathogen interaction, pathogenicity, and possible drug therapeutics |
| title_full_unstemmed | Insights from a computational analysis of the SARS‐CoV‐2 Omicron variant: Host–pathogen interaction, pathogenicity, and possible drug therapeutics |
| title_short | Insights from a computational analysis of the SARS‐CoV‐2 Omicron variant: Host–pathogen interaction, pathogenicity, and possible drug therapeutics |
| title_sort | insights from a computational analysis of the sars cov 2 omicron variant host pathogen interaction pathogenicity and possible drug therapeutics |
| topic | ACE2 COVID‐19 drugs efficacy host–pathogen interaction NRP1 Omicron variant |
| url | https://doi.org/10.1002/iid3.639 |
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