Computational analysis of functional monomers used in molecular imprinting for promising COVID-19 detection
| Autor: | Hasan Cubuk, Pinar Cakir Hatir, Mehmet Ozbil |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
010304 chemical physics
Coronavirus disease 2019 (COVID-19) Molecular Interactions Chemistry Sequence analysis SARS-CoV-2 Molecularly imprinted polymer COVID-19 Sequence (biology) Computational biology 010402 general chemistry Condensed Matter Physics 01 natural sciences Biochemistry Article Epitope 0104 chemical sciences Molecular Imprinting Molecular dynamics 0103 physical sciences Molecule Physical and Theoretical Chemistry Molecular imprinting Computational Analyses |
| Zdroj: | Computational & Theoretical Chemistry |
| ISSN: | 2210-271X |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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