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Computational Analysis Uncovering Contrasts in G-Quadruplex Propensity and Aptamer Enrichment in SELEX-Derived Libraries

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

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Abstract

G-quadruplexes (G4s) are noncanonical nucleic acid structures with biological and therapeutic significance, and they are found in many aptamer sequences. Using c-kit 1 G4 DNA as a target, systematic evolution of ligands by exponential enrichment (SELEX) has been carried out using an RNA library, resulting in G4-rich aptamers. Herein, this article investigates the relationship between predicted G4-forming potential and aptamer enrichment by analyzing high-throughput SELEX libraries using three G4 prediction tools: G4NN, G4Hunter, and QGRS Mapper. While the tools demonstrate strong internal consistency and overlap in identifying G4-prone sequences, their predictions show limited concordance with experimental abundance and enrichment trends across SELEX rounds. Only a small fraction of sequences display both high G4 scores and consistent enrichment. Experimental validation using electrophoretic mobility shift assays confirmed that strong predicted G4-forming sequences often lack strong binding activity, whereas highly enriched aptamers with strong binding activities may show weaker G4 signatures computationally. These findings suggest that current G4-prediction tools alone are insufficient for aptamer candidate selection and highlight the need for integrative evaluation strategies that combine structural prediction with empirical performance data. © 2025 The Author(s). ChemBioChem published by Wiley-VCH GmbH.
Original languageEnglish
Article numbere202500614
Number of pages13
JournalChemBioChem
Volume27
Issue number1
Online published15 Dec 2025
DOIs
Publication statusPublished - Jan 2026

Funding

G.L. and T.-Y.W. contributed equally to this work. Funding for this work was from Natural Sciences and Engineering Research Council of Canada (NSERC), a New Frontiers in Research Funds (NFRF) Exploration grant and Canada Research Chairs program. The authors also thank a Distinguished Visiting Professor fellowship to the State Key Laboratory of Marine Environmental Health awarded to J.L. to initiate this collaboration. This work is also supported by National Natural Science Foundation of China Projects (32471343, 32222089); Research Grants Council of the Hong Kong SAR, China Projects (CityU 11101525, RFS2425-1S02, CityU 11100123, CityU 11100222, CityU 11100421); Croucher Foundation Project (9509003); State Key Laboratory of Marine Enviromental Health (SCRF/0070); and City University of Hong Kong projects (9680376, 7030001, 9678302) to C.K.K.

Research Keywords

  • aptamers
  • computational analysis
  • G-quadruplex
  • machine learning
  • systematic evolution of ligands by exponential enrichment

Publisher's Copyright Statement

  • This full text is made available under CC-BY-NC 4.0. https://creativecommons.org/licenses/by-nc/4.0/

RGC Funding Information

  • RGC-funded

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