Accelerated aptamer selection via SELEX and molecular simulations for lipopolysaccharide detection

Abstract

Lipopolysaccharides (LPS), the major components of Gram-negative bacterial outer membranes, are critical virulence factors that can trigger severe immune responses, leading to sepsis and other inflammatory diseases. Rapid and accurate LPS detection is therefore essential in clinical diagnosis, pharmaceutical safety, and food monitoring. Aptamers represent a promising alternative to antibodies due to their high specificity, stability, and cost-effectiveness. However, the conventional SELEX process for aptamer selection is labor-intensive and time-consuming, often generating numerous candidates requiring costly experimental validation. Herein, we present a computationally assisted post-SELEX refinement pipeline that integrates molecular docking and molecular dynamics simulations to efficiently prioritize and validate aptamer candidates obtained from SELEX. Using LPS from Klebsiella pneumoniae ATCC 15380 as the model target, ten rounds of SELEX yielded candidate ssDNA sequences that were subsequently evaluated through our computational workflow. Among the refined candidates, aptamer seq. 5 exhibited the highest predicted and experimental affinity, with a dissociation constant (K_d) of 6.68 nM, supported by both in vitro assays and molecular simulations. These finding demonstrate that the proposed SELEX-simulation pipeline significantly accelerates post-SELEX aptamer refinement, effectively reducing the number of candidates requiring expensive experimental screening and validation.