Characterization and rational design of biomolecular sensors using molecular dynamics simulations

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Date
2023
Authors
Smith, Dustin D.
University of Lethbridge. Faculty of Arts and Science
Journal Title
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Publisher
Lethbridge, Alta. : University of Lethbridge, Dept. of Chemistry and Biochemistry
Abstract
Biosensors are analytical devices that use biological components to detect and report the presence of a target molecule. Although useful for a broad range of purposes, biosensors are conventionally designed using laborious methods limiting development to a small number of applications with large commercial value. To overcome this limitation, computational approaches are needed to streamline rational design of protein-fluorophore conjugate-type biosensors. Here, I report and iteratively improve such a biosensor development pipeline based on protein molecular dynamics simulations, exploiting underlying dynamic properties of proteins for biosensor design. As proof-of-concept, I report the construction of several carbohydrate-detecting biosensors which are advantageous compared to previous carbohydrate detection methods, and I use these biomolecular tools to characterize several Carbohydrate Active Enzymes (CAZymes). This research highlights how underlying dynamic features of proteins can be utilized for the design and mechanistic interpretation of biomolecular function in a broad range of applications.
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Keywords
Biosensor , Molecular Dynamics , Fluorescence , Protein Engineering , Carbohydrate Detection , Rapid Kinetics , Protein Dynamics , Amino Acid Dynamics , CAZyme , Protein-fluorophore conjugate , Carbohydrate Active Enzyme
Citation
Chapter 2: Smith, D.D., Girodat, D., Abbott, D.W., and Wieden, H.-J. (2022) Construction of a highly specific and selective carbohydrate-detecting biosensor utilizing Computational Identification of Non-disruptive Conjugation sites (CINC) for flexible and streamlined biosensor design. Biosensors and Bioelectronics, 200, 113899.; Chapter 3: Smith, D.D., King, J.K., Abbott, D.W., and Wieden, H.-J. (2022). Development of a real-time pectic oligosaccharide-detecting biosensor using the rapid and flexible Computational Identification of Non-disruptive Conjugation sites (CINC) biosensor design platform. Sensors, 22(3), 948.