A high affinity dopamine aptamer: implications of library diversity and negative selections

This dataset supports the discovery and characterization of a high-affinity DNA aptamer for dopamine obtained through a modified capture-SELEX process without negative selection. Dopamine is a critical neurotransmitter involved in regulating reward, motivation, and motor functions, and its dysregulation is associated with neurological disorders such as Parkinson’s disease and addiction. Therefore, the development of highly specific and sensitive recognition elements for dopamine is essential for analytical and biosensing applications. The dataset includes raw and processed experimental data from multiple complementary techniques used to validate aptamer binding and sensing performance. These data comprise isothermal titration calorimetry (ITC) measurements for thermodynamic characterization, thioflavin T (ThT) fluorescence titration assays for binding affinity evaluation, and strand-displacement fluorescence assays for kinetic analysis and sensor performance assessment. Key results derived from this dataset demonstrate that the newly selected aptamer (Dopa-T) exhibits significantly improved binding affinity toward dopamine compared to the previously reported variant (Dopa-A), with a dissociation constant (Kd) of approximately 0.42 μM determined by ITC, representing a ~6-fold enhancement. Fluorescence-based assays yielded comparable apparent Kd values (~0.46 μM), confirming the robustness of the binding interaction. In strand-displacement sensing systems, the Dopa-T aptamer showed faster release kinetics, improved sensitivity, and a lower limit of detection (LOD) of 22 nM, substantially outperforming the previous aptamer. Additional datasets also capture interactions with structurally related molecules (e.g., serotonin), enabling evaluation of selectivity and the influence of negative selection conditions. All experiments were conducted under controlled buffer conditions (1× PBS, 2 mM MgCl₂) at 25 °C. The data are organized in structured formats (e.g., CSV files) corresponding to the main figures (Figures 2–6) and supplementary figures (e.g., Figure S2). The dataset includes fluorescence intensities, integrated heat signals from ITC, kinetic fluorescence traces, binding curves. This dataset provides a comprehensive resource for studying aptamer–target interactions, understanding the role of mutation and selection pressure in aptamer evolution, and developing nucleic acid-based biosensors for small-molecule detection. It also offers insights into optimizing SELEX conditions, particularly the balance between positive and negative selection, which is broadly applicable to the discovery of high-affinity aptamers.