Reduced-Order Molecular Dynamics Simulation of Large Enzymes


In the state-of-art method, the reactive part of an enzyme is modelled through computational quantum mechanics (QM) methods such as Density Functional Theory (DFT), which can accurately estimate the catalysis reaction, while the faster non-reactive molecular mechanics (MM) describes rest of the system. However, QM is highly computationally expensive. Moreover, its order of complexity is O(N3), where $N$ is the number of atoms. Explicitly, if the size of the system doubles, the computational cost increases by the factor of 8. The simulation of very large scale enzymes with this method is impractical. Thus, a reduced-order computational model is indispensable to analyze the enzyme catalysis.

Molecular dynamics simulation with empirical force field is faster in computation with the cost of accuracy. In practice, molecular simulations with non-reactive force fields are very fast in computation and they can model the structure and the dynamics but cannot reproduce either the catalytic activity or other reaction mechanisms. On the other hand, a reactive force field can model the breaking and forming of bonds and thereby can describe the chemical reactions and catalytic activities. In this project, various kinds of force field will be investigated simultaneously to model the reaction kinetics of large enzymes like ADAM 10/17 towards the goal of better modelling of pharmaceutical substances and eradicating detrimental side effects.

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