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Computational analysis of functional monomers used in molecular imprinting for promising COVID-19 detection.
Cubuk, Hasan; Ozbil, Mehmet; Cakir Hatir, Pinar.
  • Cubuk H; Istanbul Arel University, Department of Biomedical Engineering, Bioinspired Functional Polymers and Nanomaterials Laboratory, 34537 Buyukcekmece, Istanbul, Turkey.
  • Ozbil M; Gebze Technical University, Institute of Biotechnology, 41400 Gebze, Kocaeli, Turkey.
  • Cakir Hatir P; Istanbul Arel University, Department of Biomedical Engineering, Bioinspired Functional Polymers and Nanomaterials Laboratory, 34537 Buyukcekmece, Istanbul, Turkey.
Comput Theor Chem ; 1199: 113215, 2021 May.
Article in English | MEDLINE | ID: covidwho-1135292
ABSTRACT
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.
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Full text: Available Collection: International databases Database: MEDLINE Language: English Journal: Comput Theor Chem Year: 2021 Document Type: Article Affiliation country: J.comptc.2021.113215

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Full text: Available Collection: International databases Database: MEDLINE Language: English Journal: Comput Theor Chem Year: 2021 Document Type: Article Affiliation country: J.comptc.2021.113215