Issue 19, 2024

In silico selection of aptamers against SARS-CoV-2

Abstract

Aptamers are molecular recognition elements that have been extensively deployed in a wide array of applications ranging from diagnostics to therapeutics. Due to their unique properties as compared to antibodies, aptamers were also largely isolated during the COVID-19 pandemic for multiple purposes. Typically generated by conventional SELEX, the inherent drawbacks of the process including the time-consuming, cumbersome and resource-intensive nature catalysed the move to adopt in silico approaches to isolate aptamers. Impressive performances of these in silico-derived aptamers in their respective assays have been documented thus far, bearing testimony to the huge potential of the in silico approaches, akin to the traditional SELEX in isolating aptamers. In this study, we provide an overview of the in silico selection of aptamers against SARS-CoV-2 by providing insights into the basic steps involved, which comprise the selection of the initial single-stranded nucleic acids, determination of the secondary and tertiary structures and in silico approaches that include both rigid docking and molecular dynamics simulations. The different approaches involving aptamers against SARS-CoV-2 were illuminated and the need to verify these aptamers by experimental validation was also emphasized. Cognizant of the need to continuously improve aptamers, the strategies embraced thus far for post-in silico selection modifications were enumerated. Shedding light on the steps involved in the in silico selection can set the stage for further improvisation to augment the functionalities of the aptamers in the future.

Graphical abstract: In silico selection of aptamers against SARS-CoV-2

Article information

Article type
Minireview
Submitted
02 ذو الحجة 1445
Accepted
09 صفر 1446
First published
29 صفر 1446

Analyst, 2024,149, 4770-4788

In silico selection of aptamers against SARS-CoV-2

A. M. Akmal Shukri, S. M. Wang, C. Feng, S. L. Chia, S. F. A. Mohd Nawi and M. Citartan, Analyst, 2024, 149, 4770 DOI: 10.1039/D4AN00812J

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