Computational Analysis of Functional Monomers Used in Molecular Imprinting for Promising Covid-19 Detection
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CitationCubuk, H., Ozbil, M., & Hatir, P. C. (2021). Computational analysis of functional monomers used in molecular imprinting for promising COVID-19 detection. Computational and Theoretical Chemistry, 1199, 113215.
Today, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has recently caused a severe outbreak worldwide. There are still several challenges in COVID-19 diagnoses, such as limited reagents, equipment, and long turnaround times. In this research, we propose to design molecularly imprinted polymers as a novel approach for the rapid and accurate detection of SARS-CoV-2. For this purpose, we investigated molecular interactions between the target spike protein, receptor-binding domain of the virus, and the common functional monomers used in molecular imprinting by a plethora of computational analyses; sequence analysis, molecular docking, and molecular dynamics (MD) simulations. Our results demonstrated that AMPS and IA monomers gave promising results on the SARS-CoV-2 specific TEIYQAGST sequence for further analysis. Therefore, we propose an epitope approach-based synthesis route for specific recognition of SARS-CoV-2 by using AMPS and IA as functional monomers and the peptide fragment of the TEIYQAGST sequence as a template molecule.