Creating a biosensor that is sensitive and specific enough to detect small concentrations of a designated target in a complex environment is a challenging endeavor. Aptamer and peptide biorecognition elements (BREs) have been implemented successfully in a variety sensors in the medical fields due to their high specificity and selectivity. However, very little research has been done to identify BREs specific to biomarkers associated with cognitive state and performance. BREs have often been identified through in vitro selection methods, which can take months and result in few high binding sequences. The focus of this research is to combine BRE molecular modeling, in vitro experimental methods, and high throughput microarrays to identify BREs linked to cognitive function. Two approaches run in parallel determined sequences to be implemented in microarray experiments. The first method utilized high throughput sequencing during early rounds of in vitro selection methods to identify hundreds of potentially binding sequences for a specific target. The second method implemented modeling techniques investigating the use of BRE patterned libraries generated computationally, based on structural features that can lead to the design of effective BREs. Microarray slides created using both sequence identification methods were exposed to a fluorescently labeled target and analyzed for binding, including labeling of small molecules, a more challenging task due to the lack of available functional groups. The identified BREs were then characterized by exposing high replicate microarrays to a range of analyte concentrations in order to determine binding constants (Kd). Isothermal titration calorimetry was also used as a non-labeled method to further characterize BRE sequences and supplement Kd determination. BREs with high binding affinity can then be implemented in different sensing platforms, including gold nanoparticle colorimetric assays. This combined method allows for rapid identification of sensitive and selective BREs for use in a multitude of biosensing platforms.

Identification of biorecognition elements specific to biomarkers through a combination modeling, in vitro and, high throughput microarray methods

255th National Meeting (2018)

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