Modular Label-Free Electrochemical Biosensor Loading Nature-Inspired Peptide toward the Widespread Use of COVID-19 Antibody Tests
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , , , , , , , , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1021/acsnano.2c04364 http://hdl.handle.net/11449/241701 |
Resumo: | 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 screening label-free (LF) biosensors based on a carbon electrode, gold nanoparticles (AuNPs), and electrochemical impedance spectroscopy. 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 °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. |
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Modular Label-Free Electrochemical Biosensor Loading Nature-Inspired Peptide toward the Widespread Use of COVID-19 Antibody Testselectrochemical impedance spectroscopygold nanoparticlemachine learningnoncovalent immobilizationSARS-CoV-2Limitations 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 screening label-free (LF) biosensors based on a carbon electrode, gold nanoparticles (AuNPs), and electrochemical impedance spectroscopy. 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 °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.Brazilian Nanotechnology National Laboratory Brazilian Center for Research in Energy and Materials, CampinasCenter for Natural and Human Sciences Federal University of ABC, Santo AndréInstitute of Biomedical Sciences University of São Paulo São PauloInstitute of Chemistry University of Campinas, CampinasSão Carlos Institute of Chemistry University of São Paulo, São CarlosLaboratory of Immunology Heart Institute University of São Paulo São PauloCenter for Mathematics Computing and Cognition Federal University of ABC, Santo AndréMedical School University of Sao Paulo São PauloInstitute of Chemistry São Paulo State University, AraraquaraJohn A. Paulson School of Engineering and Applied Sciences Harvard UniversityInstitute of Chemistry São Paulo State University, AraraquaraBrazilian Center for Research in Energy and MaterialsFederal University of ABCUniversidade de São Paulo (USP)Universidade Estadual de Campinas (UNICAMP)Universidade Estadual Paulista (UNESP)Harvard UniversityCastro, Ana C. H.Bezerra, Ítalo 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. [UNESP]Sanches, Paulo R. S. [UNESP]Santhiago, MuriloCharlie-Silva, IvesMartinez, Diego S. T.Scott, Ana L.Alves, Wendel A.Lima, Renato S.2023-03-01T21:17:30Z2023-03-01T21:17:30Z2022-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1021/acsnano.2c04364ACS Nano.1936-086X1936-0851http://hdl.handle.net/11449/24170110.1021/acsnano.2c043642-s2.0-85136624110Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengACS Nanoinfo:eu-repo/semantics/openAccess2023-03-01T21:17:31Zoai:repositorio.unesp.br:11449/241701Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T19:31:11.683090Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Modular Label-Free Electrochemical Biosensor Loading Nature-Inspired Peptide toward the Widespread Use of COVID-19 Antibody Tests |
title |
Modular Label-Free Electrochemical Biosensor Loading Nature-Inspired Peptide toward the Widespread Use of COVID-19 Antibody Tests |
spellingShingle |
Modular Label-Free Electrochemical Biosensor Loading Nature-Inspired Peptide toward the Widespread Use of COVID-19 Antibody Tests Castro, Ana C. H. electrochemical impedance spectroscopy gold nanoparticle machine learning noncovalent immobilization SARS-CoV-2 |
title_short |
Modular Label-Free Electrochemical Biosensor Loading Nature-Inspired Peptide toward the Widespread Use of COVID-19 Antibody Tests |
title_full |
Modular Label-Free Electrochemical Biosensor Loading Nature-Inspired Peptide toward the Widespread Use of COVID-19 Antibody Tests |
title_fullStr |
Modular Label-Free Electrochemical Biosensor Loading Nature-Inspired Peptide toward the Widespread Use of COVID-19 Antibody Tests |
title_full_unstemmed |
Modular Label-Free Electrochemical Biosensor Loading Nature-Inspired Peptide toward the Widespread Use of COVID-19 Antibody Tests |
title_sort |
Modular Label-Free Electrochemical Biosensor Loading Nature-Inspired Peptide toward the Widespread Use of COVID-19 Antibody Tests |
author |
Castro, Ana C. H. |
author_facet |
Castro, Ana C. H. Bezerra, Ítalo 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. [UNESP] Sanches, Paulo R. S. [UNESP] Santhiago, Murilo Charlie-Silva, Ives Martinez, Diego S. T. Scott, Ana L. Alves, Wendel A. Lima, Renato S. |
author_role |
author |
author2 |
Bezerra, Ítalo 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. [UNESP] Sanches, Paulo R. S. [UNESP] Santhiago, Murilo Charlie-Silva, Ives Martinez, Diego S. T. Scott, Ana L. Alves, Wendel A. Lima, Renato S. |
author2_role |
author author author author author author author author author author author author author author author author author author |
dc.contributor.none.fl_str_mv |
Brazilian Center for Research in Energy and Materials Federal University of ABC Universidade de São Paulo (USP) Universidade Estadual de Campinas (UNICAMP) Universidade Estadual Paulista (UNESP) Harvard University |
dc.contributor.author.fl_str_mv |
Castro, Ana C. H. Bezerra, Ítalo 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. [UNESP] Sanches, Paulo R. S. [UNESP] Santhiago, Murilo Charlie-Silva, Ives Martinez, Diego S. T. Scott, Ana L. Alves, Wendel A. Lima, Renato S. |
dc.subject.por.fl_str_mv |
electrochemical impedance spectroscopy gold nanoparticle machine learning noncovalent immobilization SARS-CoV-2 |
topic |
electrochemical impedance spectroscopy gold nanoparticle machine learning noncovalent immobilization SARS-CoV-2 |
description |
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 screening label-free (LF) biosensors based on a carbon electrode, gold nanoparticles (AuNPs), and electrochemical impedance spectroscopy. 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 °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. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-01-01 2023-03-01T21:17:30Z 2023-03-01T21:17:30Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1021/acsnano.2c04364 ACS Nano. 1936-086X 1936-0851 http://hdl.handle.net/11449/241701 10.1021/acsnano.2c04364 2-s2.0-85136624110 |
url |
http://dx.doi.org/10.1021/acsnano.2c04364 http://hdl.handle.net/11449/241701 |
identifier_str_mv |
ACS Nano. 1936-086X 1936-0851 10.1021/acsnano.2c04364 2-s2.0-85136624110 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
ACS Nano |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808129080311152640 |