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 <i>Burkholderia pseudomallei </i>(<i>B. pseudomallei</i>). 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 <i>B. pseudomallei</i>. 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 <i>in-silico </i>approach to overcome the inevitable shortcoming of SELEX and predict DNA aptamers with high affinity and selectivity against <i>Burkholderia </i>invasion protein D (BipD) for the detection of <i>B. pseudomallei</i>. 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).<br>