Dimeric DNA Aptamers for the Spike Protein of SARS‐CoV‐2 Derived from a Structured Library with Dual Random Domains

Multimeric aptamer strategies are often adopted to improve the binding affinity of an aptamer toward its target molecules. In most cases, multimeric aptamers are constructed by connecting pre-identified monomeric aptamers derived from in vitro selection. Although multimerization provides an added benefit of enhanced binding avidity, the characterization of different aptamer pairings adds more steps to an already lengthy procedure. Therefore, an aptamer engineering strategy that directly selects for multimeric aptamers is highly desirable. Here, an in vitro selection strategy is reported on using a pre-structured DNA library that forms dimeric aptamers. Rather than using a library containing a single random region, which is nearly ubiquitous in existing aptamer selections, the library contains two random regions separated by a flexible poly-thymidine linker. Following sixteen rounds of selection against the SARS-CoV-2 spike protein, a relevant model target protein due to the COVID-19 pandemic, the top aptamers displayed superb affinity with K<sub>D</sub> values as low as 150 pM. Further analysis reveals that each random region functions as a distinct binding moiety and works together to achieve higher affinity. The demonstrated strategy provides an accelerated method to obtain high-affinity aptamers, which may prove useful in future aptamer diagnostic and therapeutic applications.

Authors

Institutions

Publication Details

Journal
Small Methods
Published
2024-12-20
DOI
https://doi.org/10.1002/smtd.202401600
Citations
3
Primary Topic
Advanced biosensing and bioanalysis techniques
Type
article
Field-Weighted Citation Impact
0.70

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Dimeric DNA Aptamers for the Spike Protein of SARS‐CoV‐2 Derived from a Structured Library with Dual Random Domains

Leyla Soleymani, Ryan Amini, Yingfu Li, Qing Wang et al.
3 citations
Small Methods
Advanced biosensing and bioanalysis techniques
0.70
article

Dimeric DNA Aptamers for the Spike Protein of SARS‐CoV‐2 Derived from a Structured Library with Dual Random Domains

Leyla Soleymani, Ryan Amini, Yingfu Li, Qing Wang, Jian Ma, Zijie Zhang, Jimmy Gu
article en
3 citations

Abstract

Multimeric aptamer strategies are often adopted to improve the binding affinity of an aptamer toward its target molecules. In most cases, multimeric aptamers are constructed by connecting pre-identified monomeric aptamers derived from in vitro selection. Although multimerization provides an added benefit of enhanced binding avidity, the characterization of different aptamer pairings adds more steps to an already lengthy procedure. Therefore, an aptamer engineering strategy that directly selects for multimeric aptamers is highly desirable. Here, an in vitro selection strategy is reported on using a pre-structured DNA library that forms dimeric aptamers. Rather than using a library containing a single random region, which is nearly ubiquitous in existing aptamer selections, the library contains two random regions separated by a flexible poly-thymidine linker. Following sixteen rounds of selection against the SARS-CoV-2 spike protein, a relevant model target protein due to the COVID-19 pandemic, the top aptamers displayed superb affinity with K<sub>D</sub> values as low as 150 pM. Further analysis reveals that each random region functions as a distinct binding moiety and works together to achieve higher affinity. The demonstrated strategy provides an accelerated method to obtain high-affinity aptamers, which may prove useful in future aptamer diagnostic and therapeutic applications.

Small MethodsVol. 9(6)
McMaster University (CA)
Mitacs, Natural Sciences and Engineering Research Council of Canada
Good health and well-being
Openalex Percentile: Top 28%
Advanced biosensing and bioanalysis techniques
0.70
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.