Poster abstracts

Poster number 81 submitted by Samantha Yelley

Computational docking of small molecules with a Bacillus subtilis T box antiterminator model RNA

Samantha J. Yelley (School of Sciences, University of Rio Grande), John A. Means (School of Sciences, University of Rio Grande), Jennifer V. Hines (Department of Chemistry and Biochemistry, Ohio University)

Abstract:
Computational docking of small molecules to RNA may soon be a key concentration in drug discovery. As a result of its highly-conserved primary and secondary sequence elements, the T box riboswitch, which regulates gene expression in many Gram-positive bacteria, is a potential target for pharmacological therapeutics. The riboswitch consists of the leader region of RNA that, depending upon environmental factors, can form either an antiterminator or terminator structure, thus continuing or terminating transcription. By establishing a technique to signal the terminator structure to be formed (i.e. introducing a small molecule), certain processes that are necessary for protein biosynthesis could be halted. In the current work, docking experiments were performed with Autodock 4.2. Autogrid 4.2 and AutoDockTools 1.5.4 were used to ready the ligands and the receptor for docking. In these docking experiments, classes of small molecules docked with an antiterminator model RNA, AM1A, were oxazolidinones and triazole compounds. The ligands were chosen based on fluorescence anisotropy screening data and structural components. All ligands were docked in the unprotonated and monoprotonated forms. While a variety of docking sites were observed, many docked conformations shared a common binding site in AM1A. Based on results from the fluorescence anisotropy data, the ligands were categorized by their likelihood to bind to the RNA. Calculations were performed to find average binding energies of these ligands bound to the AM1A, and trends were observed that supported the previous fluorescence data.

Keywords: riboswitch, small molecules, docking