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).