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Autori principali: Liu, Gefei, Wu, Tian-Ying, Kwok, Chun Kit, Liu, Juewen
Natura: Artículo científico
Lingua:en
Pubblicazione: Chembiochem : a European journal of chemical biology 2026
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Accesso online:https://pubmed.ncbi.nlm.nih.gov/41392711/
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  • Computational Analysis Uncovering Contrasts in G-Quadruplex Propensity and Aptamer Enrichment in SELEX-Derived Libraries. Liu, Gefei Wu, Tian-Ying Kwok, Chun Kit Liu, Juewen G-Quadruplexes Aptamers, Nucleotide SELEX Aptamer Technique Humans Proto-Oncogene Proteins c-kit Computational Biology 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.