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Modular Label-Free Electrochemical Biosensor Loading Nature-Inspired Peptide toward the Widespread Use of COVID-19 Antibody Tests

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Castro, Ana C. H. ; Bezerra, Italo R. S. ; Pascon, Aline M. ; da Silva, Gabriela H. ; Philot, Eric A. ; de Oliveira, Vivian L. ; Mancini, Rodrigo S. N. ; Schleder, Gabriel R. ; Castro, Carlos E. ; de Carvalho, Luciani R. S. ; Fernandes, Bianca H. V. ; Cilli, Eduardo M. ; Sanches, Paulo R. S. ; Santhiago, Murilo ; Charlie-Silva, Ives ; Martinez, Diego S. T. ; Scott, Ana L. ; Alves, Wendel A. ; Lima, Renato S.
Total Authors: 19
Document type: Journal article
Source: ACS NANO; v. 16, n. 9, p. 15-pg., 2022-09-27.
Abstract

Limitations of the recognition elements in terms of synthesis, cost, availability, and stability have impaired the translation of biosensors into practical use. Inspired by nature to mimic the molecular recognition of the anti-SARS-CoV-2 S protein antibody (AbS) by the S protein binding site, we synthesized the peptide sequence of Asn-Asn-Ala-Thr-Asn-COOH (abbreviated as PEP2003) to create COVID-19 screen-ing label-free (LF) biosensors based on a carbon electrode, gold nanoparticles (AuNPs), and electrochemical impedance spec-troscopy. The PEP2003 is easily obtained by chemical synthesis, and it can be adsorbed on electrodes while maintaining its ability for AbS recognition, further leading to a sensitivity 3.4-fold higher than the full-length S protein, which is in agreement with the increase in the target-to-receptor size ratio. Peptide-loaded LF devices based on noncovalent immobilization were developed by affording fast and simple analyses, along with a modular functionalization. From studies by molecular docking, the peptide-AbS binding was found to be driven by hydrogen bonds and hydrophobic interactions. Moreover, the peptide is not amenable to denaturation, thus addressing the trade-off between scalability, cost, and robustness. The biosensor preserves 95.1% of the initial signal for 20 days when stored dry at 4 degrees C. With the aid of two simple equations fitted by machine learning (ML), the method was able to make the COVID-19 screening of 39 biological samples into healthy and infected groups with 100.0% accuracy. By taking advantage of peptide-related merits combined with advances in surface chemistry and ML-aided accuracy, this platform is promising to bring COVID-19 biosensors into mainstream use toward straightforward, fast, and accurate analyses at the point of care, with social and economic impacts being achieved. (AU)

FAPESP's process: 17/02317-2 - Interfaces in materials: electronic, magnetic, structural and transport properties
Grantee:Adalberto Fazzio
Support Opportunities: Research Projects - Thematic Grants
FAPESP's process: 19/19939-1 - Effects of marine pharmaceuticals in ZFL cell line
Grantee:Ives Charlie da Silva
Support Opportunities: Scholarships in Brazil - Post-Doctoral
FAPESP's process: 14/50867-3 - INCT 2014: National Institute of Science and Technology in Bioanalysis
Grantee:Marco Aurelio Zezzi Arruda
Support Opportunities: Research Projects - Thematic Grants
FAPESP's process: 20/05761-3 - Study of the action of synthetic peptides as antivirals against SARS-CoV-2 (COVID-19) and combined evaluation with commercial anti-inflammatories
Grantee:Eduardo Maffud Cilli
Support Opportunities: Regular Research Grants