I am an EPSRC funded PhD student from the TMCS (Theory and Modelling in Chemical Sciences) CDT course. My work is focused on applying the new truncated embedding method developed by Bennie et al. to enzyme systems.
Current QM/MM calculations using DFT-level methods in the QM region are limited in accuracy so higher-level methods are needed. However, applying higher-level methods like coupled-cluster to a QM region of reasonable size is computationally expensive. Increasing the QM region size further makes the calculation unaffordable.
Embedding allows for a highly accurate coupled-cluster level method to be embedded within the “lower”-level QM region. In addition, by truncating the number of virtual orbitals available to the coupled-cluster calculation the calculation cost becomes independent of the size of the QM region. This makes truncated embedding an ideal method for high accuracy energy calculations on large systems like proteins.
The first enzyme being studied with embedding is Ketosteroid Isomerase (KSI) which converts Cholesterol to Testerone.
I completed a Masters in Theory and Modelling in Chemical Sciences as part of the training year of the TMCS CDT, a joint CDT between the Universities of Bristol, Oxford and Southampton.
During the final year of my MChem at the University of Southampton I did a computational project in the Essex group. I used ProtoMS to test if the presence of a different water model (SPC, TIP3P, TIP4P and TIP5P) in the binding site of Scytalone Dehyratase (SDT) predicted different binding free energies for water adjacent to inhibitors in the protein.