Construction of a highly selective and sensitive carbohydrate-detecting biosensor utilizing Computational Identification of Non-disruptive Conjugation sites (CINC) for flexible and streamlined biosensor design

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

“…A popular approach to biosensor design is the conjugation of a fluorescent group to a solute-binding protein that harbors specificity for the target molecule, exploiting ligand-induced fluorescence changes in the protein–fluorophore conjugate to detect a target [ 1 , 2 ]. These protein-based biosensors have been utilized for amino acid detection [ 3 , 4 , 5 , 6 ], anion or cation detection [ 4 , 7 , 8 , 9 , 10 ], nucleotide detection [ 11 , 12 , 13 ], and carbohydrate detection [ 4 , 14 , 15 , 16 , 17 , 18 , 19 ]. Protein-based biosensors are often constructed by placing a fluorescent group in close proximity to the ligand-binding site, exploiting ligand-binding events to change the local environment probed by the fluorescent group.…”

“…To this end, we have previously developed CINC, an in silico screening step for the rational selection of fluorophore conjugation sites distal from the ligand-binding site [ 18 ]. CINC was originally designed based on observations in our previous work that the binding of ligands to their respective binding sites altered the localized dynamics at distal sites [ 22 , 23 , 24 , 25 ].…”

“…CINC utilizes the explicit solvent molecular dynamics simulations of proteins in their apo and ligand-bound state to identify changes in localized dynamics as a consequence of ligand binding, and maps these changes to the corresponding amino acids. Changes in amino acid dynamics in response to an input (i.e., ligand binding) are calculated and ranked using our in-house developed “ F Score ” algorithm [ 18 ]. The aforementioned changes in amino acid dynamics upon ligand binding are then exploited for biosensor design via the placement of a fluorescent group at the selected site.…”

“…To generate candidate biosensors, selected amino acid sites are substituted with cysteine and subsequently conjugated with a thiol-reactive fluorophore. CINC was previously used to develop protein-based biosensors for the detection of maltooligosaccharides [ 18 ], and an evaluation of the efficacy of prior design considerations has since been used to improve our scoring algorithm. Here, we present a streamlined and improved version of the CINC pipeline scoring algorithm ( F Score2.0 ), informed by computational and experimental data in our previous report [ 18 ].…”

“…CINC was previously used to develop protein-based biosensors for the detection of maltooligosaccharides [ 18 ], and an evaluation of the efficacy of prior design considerations has since been used to improve our scoring algorithm. Here, we present a streamlined and improved version of the CINC pipeline scoring algorithm ( F Score2.0 ), informed by computational and experimental data in our previous report [ 18 ]. Our prior study with CINC examined ligand-induced changes in Root Mean Square Fluctuation, changes in distance to tryptophan, changes in solvent accessibility, changes in proximity to ligand, and changes in backbone dihedral angles when scoring candidate fluorophore conjugation sites [ 18 ].…”