<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-09-22T23:53:08Z</responseDate><request verb="GetRecord" identifier="oai:www.repository.cam.ac.uk:1810/246261" metadataPrefix="uketd_dc">https://api.repository.cam.ac.uk/server/oai/request</request><GetRecord><record><header><identifier>oai:www.repository.cam.ac.uk:1810/246261</identifier><datestamp>2024-06-27T10:47:47Z</datestamp><setSpec>com_1810_198332</setSpec><setSpec>com_1810_256064</setSpec><setSpec>col_1810_214775</setSpec></header><metadata><uketd_dc:uketddc xmlns:uketd_dc="http://naca.central.cranfield.ac.uk/ethos-oai/2.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcterms="http://purl.org/dc/terms/" xmlns:uketdterms="http://naca.central.cranfield.ac.uk/ethos-oai/terms/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://naca.central.cranfield.ac.uk/ethos-oai/2.0/ http://naca.central.cranfield.ac.uk/ethos-oai/2.0/uketd_dc.xsd">
   <dc:title>Large scale quantum mechanical enzymology</dc:title>
   <dc:identifier xsi:type="dcterms:DOI">10.17863/CAM.16613</dc:identifier>
   <dc:creator>Lever, Greg</dc:creator>
   <dcterms:abstract>There exists a concerted and continual effort to simulate systems of genuine biological&#xd;
interest to greater accuracy with methods of increasing transferability. More accurate&#xd;
descriptions of these systems at a truly atomistic and electronic level are irrevocably&#xd;
changing our understanding of biochemical processes. Broadly, classical techniques do not&#xd;
employ enough rigour, while conventional quantum mechanical approaches are too computationally&#xd;
expensive for systems of the requisite size. Linear-scaling density-functional&#xd;
theory (DFT) is an accurate method that can apply the predictive power of quantum mechanics&#xd;
to the system sizes required to study problems in enzymology. This dissertation&#xd;
presents methodological developments and protocols, including best practice, for accurate&#xd;
preparation and optimisation, combined with proof-of-principle calculations demonstrating&#xd;
reliable results for a range of small molecule and large biomolecular systems. Previous&#xd;
authors have shown that DFT calculations yield an unphysical, negligible energy gap between&#xd;
the highest occupied and lowest unoccupied molecular orbitals for proteins and&#xd;
large water clusters, a characteristic reproduced in this dissertation. However, whilst&#xd;
others use this phenomenon to question the applicability of Kohn-Sham DFT to large&#xd;
systems, it is shown within this dissertation that the vanishing gap is, in fact, an electrostatic&#xd;
artefact of the method used to prepare the system. Furthermore, practical solutions&#xd;
are demonstrated for ensuring a physical gap is maintained upon increasing system size.&#xd;
Harnessing these advances, the  rst application using linear-scaling DFT to optimise stationary&#xd;
points in the reaction pathway for the Bacillus subtilis chorismate mutase (CM)&#xd;
enzyme is made. Averaged energies of activation and reaction are presented for the rearrangement&#xd;
of chorismate to prephenate in CM and in water, for system sizes comprising&#xd;
up to 2000 atoms. Compared to the uncatalysed reaction, the calculated activation barrier&#xd;
is lowered by 10.5 kcal mol-1 in the presence of CM, in good agreement with experiment.&#xd;
In addition, a detailed analysis of the interactions between individual active-site residues&#xd;
and the bound substrate is performed, predicting the signi cance of individual enzyme&#xd;
sidechains in CM catalysis. These proof-of-principle applications of powerful large-scale&#xd;
DFT methods to enzyme catalysis will provide new insight into enzymatic principles from&#xd;
an atomistic and electronic perspective.</dcterms:abstract>
   <uketdterms:institution>University of Cambridge</uketdterms:institution>
   <dcterms:issued>2014-10-07</dcterms:issued>
   <dc:type>Thesis</dc:type>
   <uketdterms:qualificationlevel>Doctoral</uketdterms:qualificationlevel>
   <uketdterms:qualificationname>Doctor of Philosophy (PhD)</uketdterms:qualificationname>
   <dc:language>en</dc:language>
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