Natural metallo-enzymes are known for their outstanding catalytic dexterity. The quality modeling of metallo-enzymes is highly desirable, both to understand the mechanism of their proficiency, and to eventually design artificial metallo-enzymes. However, the challenge of this modeling is great, because it is needed to account for both the cooperative dynamic moves of the protein, and electronic structure of the metal. We report a new method that combines an extensive statistical mechanical sampling of the protein, achieved with Discrete Molecular Dynamic (DMD), and the quantum mechanical (QM) description of the active site, QM/DMD. The method is fast and robust. Testing of QM/DMD at several levels was done on Rubredoxin. QM/DMD successfully predicts the structures of the Fe(II) and Fe(III) forms of Rubredoxin, and their mutants, properly describes the unusual weak H-bonds between SCys and aliphatic C-H groups near the active site, and captures the response of the RedOx potential to mutations.

Development of a hybrid method combining quantum mechanical calculations and discrete molecular dynamics for metallo-protein modeling

243rd National Meeting (2012)

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