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Article Abstract

Fluorescently labeled, solute-binding proteins that change their fluorescent output in response to ligand binding are frequently used as biosensors for a wide range of applications. We have previously developed a "Computational Identification of Non-disruptive Conjugation sites" (CINC) approach, an in silico pipeline utilizing molecular dynamics simulations for the rapid design and construction of novel protein-fluorophore conjugate-type biosensors. Here, we report an improved in silico scoring algorithm for use in CINC and its use in the construction of an oligogalacturonide-detecting biosensor set. Using both 4,5-unsaturated and saturated oligogalacturonides, we demonstrate that signal transmission from the ligand-binding pocket of the starting protein scaffold to the CINC-selected reporter positions is effective for multiple different ligands. The utility of an oligogalacturonide-detecting biosensor is shown in Carbohydrate Active Enzyme (CAZyme) activity assays, where the biosensor is used to follow product release upon polygalacturonic acid (PGA) depolymerization in real time. The oligogalacturonide-detecting biosensor set represents a novel enabling tool integral to our rapidly expanding platform for biosensor-based carbohydrate detection, and moving forward, the CINC pipeline will continue to enable the rational design of biomolecular tools to detect additional chemically distinct oligosaccharides and other solutes.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8839585PMC
http://dx.doi.org/10.3390/s22030948DOI Listing

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Article Synopsis
  • Fluorescent biosensors utilize solute-binding proteins with changes in fluorescence upon ligand binding, useful in various applications.
  • The research presents an enhanced scoring algorithm for the CINC approach, which uses molecular dynamics simulations to design protein-fluorophore conjugates for biosensors.
  • An oligogalacturonide-detecting biosensor was developed to track enzyme activity in real-time during polygalacturonic acid depolymerization, showcasing its potential for broader carbohydrate detection.
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