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Electronic Tongue Generating Continuous Recognition Patterns for Protein Analysis
Published on: September 16, 2014
Glycoform Differentiation by a Targeted, Self-Assembled, Pattern-Generating Protein Surface Sensor
Ronny Peri-Naor1, Zohar Pode1, Naama Lahav-Mankovski1
1Department of Organic Chemistry, Weizmann Institute of Science, Rehovot 7610001, Israel.
Abstract:
A method for generating targeted, pattern-generating, protein surface sensors via the self-assembly of modified oligodeoxynucleotides (ODNs) is described. The simplicity by which these systems can be created enabled the development of a sensor that can straightforwardly discriminate between distinct glycoform populations. By using this sensor to identify glycosylation states of a therapeutic protein, we demonstrate the diagnostic potential of this approach as well as the feasibility of integrating a wealth of supramolecular receptors and sensors into higher-order molecular analytical devices with advanced properties. For example, the facile device integration was used to attach the well-known anthracene-boronic acid (An-BA) probe to a biomimetic DNA scaffold and consequently, to use the unique photophysical properties of An-BA to improve glycoform differentiation. In addition, the noncovalent assembly enabled us to modify the sensor with a trinitrilotriacetic acid (tri-NTA)-Ni2+ complex, which endows it with selectivity toward a hexa-histidine tag (His-tag). The selective responses of the system to diverse His-tag-labeled proteins further demonstrate the potential applicability of such sensors and validate the mechanism underlying their function.
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