Hybrid Dynamics Simulation Engine for Metalloproteins

AbstractQuality computational description of metalloproteins is a great challenge due to the vast span of time- and lengthscales characteristic of their existence. We present an efficient new method that allows for robust characterization of metalloproteins. It combines quantum mechanical (QM) description of the metal-containing active site, and extensive dynamics of the protein captured by discrete molecular dynamics (DMD) (QM/DMD). DMD samples the entire protein, including the backbone, and most of the active site, except for the immediate coordination region of the metal. QM operates on the part of the protein of electronic and chemical significance, which may include tens to hundreds of atoms. The breathing quantum-classical boundary provides a continuous mutual feedback between the two machineries. We test QM/DMD using the Fe-containing electron transporter protein, rubredoxin, and its three mutants as a model. QM/DMD can provide a reliable balanced description of metalloproteins’ structure, dynamics, and electronic structure in a reasonable amount of time. As an illustration of QM/DMD capabilities, we then predict the structure of the Ca2+ form of the enzyme catechol O-methyl transferase, which, unlike the native Mg2+ form, is catalytically inactive. The Mg2+ site is ochtahedral, but the Ca2+ is 7-coordinate and features the misalignment of the reacting parts of the system. The change is facilitated by the backbone adjustment. QM/DMD is ideal and fast for providing this level of structural insight