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Understanding Structure, Function and Dynamics of the Enzyme E.coli Alkaline Phosphatase

May 16, 2012 | 05:00 PM

Mari Chikvaidze,Computational Biophysical Chemistry Interdisciplinary Center for Scientific Computing University of Heidelberg

Enzymes are physiologically important biomolecules that accelerate chemical reactions.The rate enhancement by the enzyme E.coli Alkaline Phosphatase (AP), presented here, isup to 10^17, relative to the corresponding reaction of phosphoester hydrolysis in solution.Dimeric quaternary structure of this metalo-enzyme provides remarkable structural featuresenabling the enzyme to achieve its catalytic activity. In order to understand structureand function of the enzyme, we use computational approaches, at different level of complexityand sophistication. A low resolution, coarse grained model of the enzyme, explainsthe influence of the global dynamics, defined by the quaternary structure of the enzyme, onits functionality. Multiple, independent classical molecular dynamics (MD) simulations, ofup to 100ns each, provide an atomistic understanding of local dynamics at the nano secondtime scale. Dimeric form of the enzyme is investigated, and compared to that of an isolatedmonomer. Normal mode and principle component analysis suggest mechanical couplingbetween the motions of the active sites in the wild type dimer, via dimer interface. Correlatedmotions of the monomeric units of the dimer, as well as the dynamics, and the architectureof active sites, seem to play an important role in the functionality of Alkaline Phosphatase.However, in order to account for bond rearrangement events taking place in the active site, during the catalysis, we constructed a small, quantum mechanical model comprisingcatalytic ions and few important active site residues. We went a step further inmodelling enzymatic reactions by taking into account quantum dynamical effects, such astunnelling and zero-point vibrational energies and analytically estimated their contributionto lowering the energy barrier. In particular, we focus on a few important proton transfersteps, out of many such steps that are very difficult to detect experimentally. We then usedtransition networks (TN) methodology to explore a comprehensive collection of protontransfer pathways and calculate the energies associated with every single pathway. Bycombination of different theoretical approaches, we aim to provide a computationalframework needed in order to gain an in-depth understanding of the structure-functiondynamicsrelationship of the enzymes.

Time & Location

May 16, 2012 | 05:00 PM

Seminar Room T1, 1.3.21