Please use this identifier to cite or link to this item: http://hdl.handle.net/10267/13747
Title: MP2 and DFT Calculations of Ligand Binding in Acetylcholine Binding Protein's Aromatic Box
Authors: Carter, Erin Elizabeth, Class of 2012
Keywords: Chemistry, Department of;Student research;Honors papers
Issue Date: 23-May-2012
Publisher: Memphis, Tenn. : Rhodes College
Abstract: Acetylcholine Binding Protein’s active site, called the Aromatic Box for its five aromatic amino acid components, is a receptor for nicotine that closely mimics 〈7 Nicotinic Acetylcholine Receptors (nAChRs) in the brain. In this study, several experiments were conducted in order to design novel drug candidates that capitalize on the dispersion-dominated Aromatic Box. To better understand how charge interactions are involved in ligand binding, the migration of partial atomic charges were evaluated for several component structures of the active site using both correlated WFT and select DFT methods and variety of basis sets. Additional ligands (morphine, cocaine, and galantamine) were docked in the Aromatic Box and their interaction energies with the residues were calculated to further map the ligand binding behavior of the Aromatic Box. Electrostatic potential maps were generated to visually evaluate the known ligands’ binding efficacy. Using information from these studies, novel drug candidate molecules have been designed. The interaction energies between these candidates and the Aromatic Box were evaluated. The results from this in silico experiment show that bicyclic molecules with heteroatoms bind more effectively in the Aromatic Box than the known ligands studied. Further improvement can be gained through the addition of hydroxyl and cyano functional groups around the bicylcic portion of the drug candidates. Quantitative Structure Activity Relationship (QSAR) calculations were used to draw correlations between the molecular properties of the known ligands and their literature potency values. Equations were calibrated using known ligands’ QSAR data to predict the potencies of the novel drug candidates.
URI: http://hdl.handle.net/10267/13747
Appears in Collections:Chemistry Department. Honors Papers

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