From SELEX to Sequencing: Uncovering enriched Aptamers with Next-Generation Sequencing and Bioinformatics

Clicks: 5
ID: 333686
2026
Free PDF
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Emerging

Ranked #959 of 973 articles by views in BMC Bioinformatics

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 973 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
Abstract Motivation The combinatorial chemistry process called systematic evolution of ligands by exponential enrichment (SELEX) enables the selection of aptamers against different targets. The integration of next-generation sequencing (NGS) into SELEX workflows represents a powerful strategy to enhance the identification and prioritization of target-binding aptamers. In this study, we present an optimized computational approach for the NGS-based analysis of enriched aptamer pools generated through SELEX. It encompasses sequencing library preparation, sequence data preprocessing, clustering, multiple sequence alignment, phylogenetic analysis, and secondary structure prediction. Results To identify target-specific aptamers, two comparative analysis strategies were implemented. In the first strategy, sequences detected in the negative selection pool were removed from the positive selection pool to eliminate nonspecific binders, resulting in six distinct sequence clusters. In the second approach, all sequences were retained, and cluster distributions were compared between the positive and negative selection pool, identifying seven clusters in the positive and six in the negative pool. Phylogenetic relationships and structural predictions enabled the selection of promising candidates, which were prioritized based on secondary structure, sequence abundance, and genetic distance from non-specific binders. Binding specificity was assessed through dot blot assays, confirming that the selected aptamers exhibited strong specific binding to the target protein. These results demonstrate the effectiveness of the NGS-guided workflow for aptamer discovery and highlight its value in streamlining candidate selection for downstream functional validation.
Reference Key
openalex_W7223363286 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Melis Güler Girbas, Jennifer Müller, Christian Schlensak, Meltem Avci‐Adali
Journal BMC Bioinformatics
Year 2026
DOI
10.1093/bioinformatics/btag777
URL
https://academic.oup.com/bioinformatics/advance-article-pdf/doi/10.1093/bioinformatics/btag777/72385254/btag777.pdf
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.