Improving DNA aptamers against a heart failure protein biomarker using structure-guided random mutation approaches for colourimetric biosensor development

Abstract

Aptamers are short single-stranded oligonucleotides, which offer several advantages over antibodies as bioreceptors. The widely used method for generating aptamer sequences, SELEX, has some limitations such as a limited oligonucleotide library used and amplification bias of PCR. Bioinformatics approaches have been shown to optimise and increase aptamer affinity. This research aimed to enhance the affinity of the NT-proBNP (N-terminal pro-brain natriuretic peptide, a biomarker for heart failure)-targeting aptamer acquired from SELEX using computational strategies involving sequence truncation and secondary structure-guided random mutations. DNA aptamers and protein structures are predicted by MC-Fold + 3dDNA and Robetta, respectively, whereas the computational evaluations utilize molecular docking, interaction profiles, and molecular dynamics simulations. The structural and energetic analysis revealed that the in silico optimised aptamer had more stable and robust interactions in binding to the NT-proBNP protein than the SELEX-obtained aptamer. Furthermore, our approach was supported and confirmed by in vitro colourimetric assay based on gold nanoparticle aggregation, evidenced by a detection limit of 0.5 ng mL⁻¹ which is lower than the SELEX-obtained aptamer (2.3 ng mL⁻¹).