In-Silico Prediction of DNA Aptamers against BipD for the Detection of Burkholderia pseudomallei using Computational Method

Melioidosis is an infectious disease caused by the environmental bacterium Burkholderia pseudomallei (B. pseudomallei). Although the culture method is the gold standard, it cannot apply to fast on-site testing because it requires a long time. Therefore, a rapid, sensitive, and cost-effective method is highly desirable to develop for the detection of B. pseudomallei. In recent years, aptasensor has been widely used to detect pathogens as it is a rapid, sensitive, precise, and low-cost detection technique. We aimed to use an in-silico approach to overcome the inevitable shortcoming of SELEX and predict DNA aptamers with high affinity and selectivity against Burkholderia invasion protein D (BipD) for the detection of B. pseudomallei. The complex secondary structure of DNA aptamers was discovered with minimum Gibbs free energy via the mFold webserver to generate a stable tertiary structure for molecular docking. Three DNA aptamer-BipD complex with the lowest binding energy were identified through Vina software and selected for further wet laboratory validation using enzyme-linked oligonucleotide assay (ELONA) and surface plasmon resonance (SPR).