In Silico-Guided Screening of a High-Affinity PD-L1 Aptamer for the Construction of a Sensitive Electrochemical Aptasensor

Programmed death ligand-1 (PD-L1) is an essential immune checkpoint protein that plays a pivotal role in tumor immune evasion and has emerged as an important biomarker for cancer diagnosis, prognosis, and immunotherapy monitoring. Aptamers have attracted increasing attention as promising molecular recognition elements owing to their high specificity, excellent chemical stability, and facile synthesis. In this study, we developed an in silico-guided aptamer screening strategy that integrates virtual library construction, molecular docking, secondary structure prediction, and structural interaction analysis to identify high-affinity PD-L1-binding aptamers, yielding a dissociation constant (Kd) of 20.73 nM. Based on the optimized aptamer, a reduced graphene oxide (rGO)-modified screen-printed electrode was fabricated to construct a label-free electrochemical aptasensor. The developed aptasensor exhibited a wide linear detection range from 0.01 to 100 nM, with an ultralow detection limit of 7.4 pM. Moreover, the biosensor demonstrated excellent selectivity, satisfactory reproducibility, and good storage stability. The combination of computational aptamer screening with electrochemical sensing provides an efficient strategy for developing high-performance aptamer biosensors and offers considerable potential for rapid PD-L1 determination in clinical liquid biopsy and cancer immunotherapy monitoring.