Literature DB >> 33823114

Electrochemical Resonance of Molecular Motion Enabling Label-, Antibody-, and Enzyme-Free Detection of SARS-CoV-2.

Lei Zhou1,2, Panpan Hao3, Hao Li2, Zhongwen Zhang1.   

Abstract

In this work, we developed a method to detect two viral marker proteins, the main protease and the spike protein (S protein), of SARS-CoV-2, as well as a host marker, chemokine receptor 5 (CCR5), which is associated with the risk of developing the severe acute respiratory syndrome. This assay can be completed in two steps in a label-free fashion, yielding a "signal-on" signal readout, which usually cannot be attained by electrochemical label-free detection using no labels or markers to tag the target protein. The proposed assay also utilizes no antibodies or enzyme-based reagents. The method achieves this performance by moderating the frequency of electrochemical potential scanning such that the scanning rate keeps pace with, or "resonances" with, the molecular motion of the probe molecule. This method has been successfully applied to detect the three target proteins in serum samples collected from patients infected with SARS-CoV-2, and the results indicate a strong correlation with the risk of deteriorating into severe acute conditions after virus infection. Soon, the clinical application of this method may provide a low-cost but effective method for virus surveillance in the general public.

Entities:  

Keywords:  COVID-19; SARS-CoV-2; covalent biosensing; electrochemical resonance; peptide probe

Year:  2021        PMID: 33823114     DOI: 10.1021/acssensors.1c00022

Source DB:  PubMed          Journal:  ACS Sens        ISSN: 2379-3694            Impact factor:   7.711


  2 in total

1.  Amperometric immunosensor developed for sensitive detection of SARS-CoV-2 spike S1 protein in combined with portable device.

Authors:  Arzum Erdem; Huseyin Senturk; Esma Yildiz; Meltem Maral
Journal:  Talanta       Date:  2022-03-29       Impact factor: 6.556

Review 2.  The role of electrochemical biosensors in SARS-CoV-2 detection: a bibliometrics-based analysis and review.

Authors:  Shudan Mao; Li Fu; Chengliang Yin; Xiaozhu Liu; Hassan Karimi-Maleh
Journal:  RSC Adv       Date:  2022-08-12       Impact factor: 4.036

  2 in total

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