COMP 268 |
| We will describe our research that has lead to a successful integration of sequence-based bioinformatics and atomic scale simulation on the Aldehyde Dehydrogenase (ALDH) family. This integration has resulted in compelling hypotheses concerning the molecular basis for two metabolic diseases as well as a novel enzyme mechanism. We developed and applied analyses that identify residues in biological macromolecules that confer specificity of interaction on the members of a paralogous family of molecules. The analysis uses the Kullback-Leibler (KL) distance; an information theory measure of entropy. Residues that have a high KL distance represent positions in the alignment where there are large systematic differences in the kinds of residues present in the two subfamilies (i.e., the defined subfamily under investigation and the rest of the alignment). This KL distance corresponds to the biological question of “What columns in an alignment most completely discriminate the subfamily or group from the rest of the alignment?” We also sought to better understand how these residues impact on the ALDH chemical mechanism. Therefore, we employed molecular dynamics (MD) simulation methods using both Molecular Mechanical (MM) potentials for studies of substrate binding and hybrid Quantum Mechanical (QM)/MM potentials for the subsequent reactions. The results suggest that the intermediate formed upon nucleophilic attack of the enzyme on the substrate is stabilized by a proton transfer from a mainchain amide. This proton transfer is supported by interactions with a residue with high group entropy. Mutating residues that disrupt this “second sphere” interaction could be the molecular basis behind two metabolic diseases. |
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Applications of Information Theory in Chemistry
8:50 AM-11:30 AM, Wednesday, 16 March 2005 Convention Center -- Room 2, Oral
Division of Computers in Chemistry |