In Silico Analysis of COVID-19 Variants: Structural Interaction with ACE2, TMPRSS2 and Pathogenic Implications
Keywords:
Homology modelling, structural prediction, COVID-19, multiple sequence alignment, pathogenesisAbstract
Background: Compared to SARS-CoVs, the S-protein of SARS-CoV-2 has a significantly higher specificity and stability for binding to the ACE2 receptor and due to the structural variation of COVID-19, the development of drugs for each variant is complicated.
Objective: This study investigates the three-dimensional structure of COVID-19 variants.
Methodology: To predict the protein structure of COVID-19 variants, homology modelling was used to determine the tertiary structure. For modelling, the Swiss Model and BLAST were used, and to ensure reliability and validated with PROCHECK, Verify3D, and ERRAT. A Ramachandran plot was used to verify the quality of 3D structure. Models were validated through SAVES. Multiple Sequence Alignment was performed to identify similarities and differences between variants.
Results: Homology Modelling indicates the sequence similarity of ALPHA, BETA, DELTA, and OMICRON variants with the template model observed as 94.48%, 94.64%, 95.11%, and 94.84%, respectively. Ramachandran plot signifies that residues are present in the most favorable region with a frequency of 90% for ALPHA, followed by BETA residues at 88%, DELTA residues at 99.9%, and OMICRON residues at 87%.
Conclusion: In conclusion, Delta variant exhibits 80-90% higher transmissibility and can propagate infection more than twice as compared to the Alpha variant.
Bangladesh Journal of Infectious Diseases, June 2026;13(1):25-42
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Copyright (c) 2026 Syed Ali Raza Shah, Imtiaz Mustafa, Iffat Nayila, Zarish Zahid, Kushaf Mohsin, Sumaira Sharif
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