title: Optimizing cross-reactivity with evolutionary search for sensors.
abstract: We report a straightforward evolutionary procedure to build an optimal sensor array from a pool of DNA sequences oriented toward three-way junctions. The individual sensors were mined from this pool under separate selection pressures to interact with four steroids, while allowing cross-reactivity, in a manner designed to achieve perfect classification of individual steroids. The resulting sensor array had three sensors and displayed discriminatory capacity between steroid classes over full ranges of concentrations. We propose that similar protocols can be used whenever we have two or more classes of samples, with individual classes being defined through gross differences in ratios of dominant families of responsive components.
authors.affiliation: Division of Experimental Therapeutics, Department of Medicine, Columbia University, New York, New York 10032, USA.
authors.forename: Kyung-Ae
authors.initials: KA
authors.lastname: Yang
authors.forename: Renjun
authors.initials: R
authors.lastname: Pei
authors.forename: Darko
authors.initials: D
authors.lastname: Stefanovic
authors.forename: Milan N
authors.initials: MN
authors.lastname: Stojanovic
mesh_terms: D052157:Aptamers, Nucleotide / Q000737:chemistry* / Q000378:metabolism; D001483:Base Sequence; D015374:Biosensing Techniques / Q000379:methods; D057927:Hydrophobic and Hydrophilic Interactions; D052156:SELEX Aptamer Technique / Q000379:methods; D013256:Steroids / Q000032:analysis* / Q000378:metabolism
chemical_list: D052157:Aptamers, Nucleotide; D013256:Steroids