Poster abstracts
Poster number 135 submitted by Chobee Sheets
Computational molecular docking of T box antitermination model with aminoglycosides
Chobee L. Sheets (School of Mathematics and Natural Sciences, University of Rio Grande), John A. Means (School of Mathematics and Natural Sciences, University of Rio Grande)
Abstract:
Computational molecular docking provides a quicker, less expensive way to screen the binding of molecules than in vitro binding studies. Using this method, many molecules, ligands, and interaction patterns can be analyzed in a brief period of time. In this case, the T box antitermination system of Gram positive bacteria was investigated with respect to seven different aminoglycosides: amikacin, kanamycin A, kanamycin B, neomycin, paromomycin, streptomycin, and tobramycin. The two structures of focus are the “on” and “off” structures of the T box riboswitch, also known as the antiterminator and terminator, respectively. Since the T box riboswitch is responsible for regulating amino acid availability through mRNA-tRNA interactions, the binding of these aminoglycosides to the antiterminator structure of the T box gene is key to this study. Using PyRx, AutoDock, and AutoDock Vina these model antiterminator RNA-aminoglycoside interactions were virtually screened to evaluate binding scores. These scores were then compared to previous in vitro binding data in order to support the claim that this software is suitable for producing accurate results in regards to modeling the binding of aminoglycosides with targeted antiterminator structures of T box genes.
Keywords: T box riboswitch, docking, aminoglycosides