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Charge transfer embedded-atom potentials for atomistic simulations of amino acids and proteins

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Please use this identifier to cite or link to this item: http://hdl.handle.net/1928/17330

Charge transfer embedded-atom potentials for atomistic simulations of amino acids and proteins

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Title: Charge transfer embedded-atom potentials for atomistic simulations of amino acids and proteins
Author: Godwin, Amo-Kwao
Advisor(s): Susan, R. Atlas
Committee Member(s): Steven, Koch
David, Dunlap
Department: University of New Mexico. Dept. of Physics & Astronomy
Subject(s): CT-EAM, EAM, molecular dynamics simulation, amino acids, proteins
LC Subject(s): Molecular dynamics--Simulation methods.
Charge transfer in biology.
Amino acids.
Proteins.
Degree Level: Masters
Abstract: The dynamical simulation of biophysical systems requires force fields (interaction potentials) capable of describing bond formation and breaking and reactive charge transfer. Molecular motor proteins such as kinesin, dynein and myosin have the extraordinary ability of converting chemical energy to mechanical energy by the process of ATP hydrolysis used for motility. This work is motivated by the reactive force field developed recently by Valone and Atlas[1–4], the charge-transfer embedded atom method (CT-EAM). CT-EAM is based on the empirical embedded-atom method (EAM) pioneered by Daw and Baskes[5]. CT-EAM extends the EAM to re- active molecular systems, through a formal basis in density functional theory. Here we report results on the development of a database for reparameterizing the earlier CT-EAM water potential developed by Muralidharan et al.[6], and for developing a new CT-EAM potential for the amino acids that are the building blocks of all proteins. The reparametization will involve using this extensive ab initio conformational fitting database for six amino acids: glycine, alanine, cysteine, serine, proline, and lysine. These amino acids were chosen to represent canonical subclasses (polar, charged, hydrophobic, ring) of the 20 naturally-occurring amino acids, thereby incorporating varying degrees of charge transfer and solvent interactions. The conformers for each amino acid, identified using a stochastic search method adapted from the work of Saunders[7], further sample distinct structural and bonding patterns. The full database includes information on the energetics of transition states linking selected amino acid conformers, an extensive survey of local minima for each amino acid, dipole moments for each conformer and includes several hitherto uncharacterized structures including novel unsolvated zwitterionic-like structures. All electronic structure calculations were performed at a high level of theory (electron correlation and high quality basis set, MP2/6-311++G**), in order to distinguish correctly between nearly-isoenergetic conformers. The resulting CT-EAM potential fitted to this database will be assessed by comparison with ab initio results for solvated amino acids and dipeptides.
Graduation Date: December 2011
URI: http://hdl.handle.net/1928/17330

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