The development of accurate in silico multiscale physics models of the interface with biology

Student thesis: Doctoral ThesisDoctor of Philosophy


There is an increasing demand for accurate modelling of biological processes where conventional experimental and computational methods break down. In particular, the engineering of biotechnology at the nano-scale makes accurate atomistic and dynamic simulations of complex systems at the bio-nano interface indispensable. This thesis explores the accurate modelling of systems within this domain, where accuracy is applied both in structural characterisation as well as defining the resulting chemical properties. Electronic structure theory calculations are applied for the development of bespoke molecular dynamics forcefield parameters. This work illustrates the capacity for costly quantum-mechanical calculations to be extrapolated to classical molecular dynamics simulations of systems com-posed of hundreds of thousands of atoms while retaining the accuracy ob-served in both experiment and state-of-the-art ab initio methods. Accurate characterisation is studied using different theoretical tools to elucidate both the function and inhibition of proteins. The sensitivity of adsorbed protein denaturing, protein corona formation and the cellular uptake of a protein-nanomaterial complex to nanomaterial functionalisation is studied to ex-plain interfacial interactions that drive unwanted phenomena in biotechnology. Additionally, the accuracy of the dynamic atomistic or electronic char-acter of protein active sites is investigated. In particular, the cessation of proteolytic activity of SARS-CoV-2 is detailed through the disruption of a catalytic dyad in the main protease active site. Finally, the accurate modelling of the strongly correlated electronic ground state of the hemocyanin oxygen transporting protein active site is investigated using a hybrid density functional theory + dynamical mean field theory (DFT+DMFT) quantum-mechanical treatment. These multiscale modelling applications convey the ability to extend preexisting theoretical tools to the burgeoning demand of accurate and large-scale modelling of biological phenomena, both to under-stand the otherwise impenetrable processes using conventional tools and to inform the development of new interdisciplinary tools in bio-nano engineering.
Date of Award1 Oct 2021
Original languageEnglish
Awarding Institution
  • King's College London
SupervisorChris Lorenz (Supervisor), Khuloud Al-Jamal (Supervisor) & Cedric Weber (Supervisor)

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