Speaker
Description
INTRODUCTION: The energy landscape of Shikimate Kinase (SK) was explored using different techniques, including classical and quantum mechanical (QM/MM) simulations. SK is an interesting enzyme because it is found in bacteria but not in humans, making it a good target for stopping several pathogenic diseases. SK catalyses the conversion of ATP and shikimic acid (SKM) into ADP and Shikimate-3-phosphate with the assistance of a Mg$^{2+}$ ion. We studied the catalytic step through free energy calculations and the conformational changes of this enzyme during µs-scale simulations by performing point mutations.
METHODS: We employed classical MD simulations in the NPT ensemble using standard software for solving Newton’s equations. Data production was completed within 4 µs. To study the chemical step, we applied QM/MM simulations using common packages for both types of simulations. The resulting trajectories were analysed using common techniques such as principal component analysis (PCA) and more recent methods from graph neural networks (GNNs).
RESULTS: The free energy computed along a predetermined reaction coordinate shows that the catalytic step proceeds without a well-defined transition state.
DISCUSSION & CONCLUSIONS: We propose that the catalytic step of SK can be affected by local frustration. It can also contribute to the different interaction networks for mutants.