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Primer-Free Aptamer Selection Using A Random DNA Library

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Parameterizing the Binding Properties of XNA Aptamers Isolated from a Low Stringency Selection.

Nandini Kundu¹, Cailen M McCloskey¹, Mohammad Hajjar¹

¹Department of Pharmaceutical Sciences, University of California, Irvine, California 92697-3958, United States.

|November 6, 2023

Summary

This study quantifies aptamer binding affinity, revealing a narrow range (1-15 nM K_D) for threose nucleic acid (TNA) aptamers against a specific target. These findings help define the lower binding limit for aptamer discovery.

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Area of Science:

Biochemistry
Molecular Biology
Bioinformatics

Background:

Machine learning aids aptamer discovery but requires experimental data on binding affinity ranges.
Understanding the lower binding affinity limit is crucial for differentiating aptamers from non-binders.

Purpose of the Study:

To quantitatively explore the diversity of aptamers and define the lower binding affinity limit.
To provide experimental constraints for aptamer discovery algorithms.

Main Methods:

In vitro selection of threose nucleic acid (TNA) aptamers against an aptagenic target over 7 rounds.
High-density sequencing of selected aptamer libraries.
Kinetic analysis of 136 isolated TNA aptamers to determine equilibrium dissociation constants (K_D).

Main Results:

A consistent, narrow range of equilibrium dissociation constants (K_D ≈ 1-15 nM) was observed between two experimental replicates.
The study characterized the binding affinity of TNA aptamers generated under low-stringency conditions.

Conclusions:

The findings provide insights into the lower binding affinity limit for aptamers against aptagenic targets.
This data can inform the development of more effective aptamer discovery algorithms and experimental evaluations.